From d2a46b72638bdcd10d188d681aa9733613d6f074 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Mon, 21 Jul 2025 01:06:13 +0800 Subject: [PATCH 01/32] update for dpa3_dynamic debug code --- .pre-commit-config.yaml | 52 ++++++++++----------- deepmd/pd/model/descriptor/repflows.py | 3 +- deepmd/pd/model/model/transform_output.py | 4 ++ deepmd/pd/train/training.py | 34 +++++++++++++- deepmd/pd/train/wrapper.py | 1 + deepmd/pt/model/model/transform_output.py | 3 ++ deepmd/pt/train/training.py | 55 +++++++++++++++++++++++ deepmd/pt/train/wrapper.py | 1 + 8 files changed, 125 insertions(+), 28 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 0415b6142c..bdb58cb24d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -65,13 +65,13 @@ repos: - id: clang-format exclude: ^(source/3rdparty|source/lib/src/gpu/cudart/.+\.inc|.+\.ipynb$|.+\.json$) # markdown, yaml, CSS, javascript - - repo: https://github.com/pre-commit/mirrors-prettier - rev: v4.0.0-alpha.8 - hooks: - - id: prettier - types_or: [markdown, yaml, css] - # workflow files cannot be modified by pre-commit.ci - exclude: ^(source/3rdparty|\.github/workflows|\.clang-format) + # - repo: https://github.com/pre-commit/mirrors-prettier + # rev: v4.0.0-alpha.8 + # hooks: + # - id: prettier + # types_or: [markdown, yaml, css] + # # workflow files cannot be modified by pre-commit.ci + # exclude: ^(source/3rdparty|\.github/workflows|\.clang-format) # Shell - repo: https://github.com/scop/pre-commit-shfmt rev: v3.12.0-1 @@ -83,25 +83,25 @@ repos: hooks: - id: cmake-format #- id: cmake-lint - - repo: https://github.com/njzjz/mirrors-bibtex-tidy - rev: v1.13.0 - hooks: - - id: bibtex-tidy - args: - - --curly - - --numeric - - --align=13 - - --blank-lines - # disable sort: the order of keys and fields has explict meanings - #- --sort=key - - --duplicates=key,doi,citation,abstract - - --merge=combine - #- --sort-fields - #- --strip-comments - - --trailing-commas - - --encode-urls - - --remove-empty-fields - - --wrap=80 + # - repo: https://github.com/njzjz/mirrors-bibtex-tidy + # rev: v1.13.0 + # hooks: + # - id: bibtex-tidy + # args: + # - --curly + # - --numeric + # - --align=13 + # - --blank-lines + # # disable sort: the order of keys and fields has explict meanings + # #- --sort=key + # - --duplicates=key,doi,citation,abstract + # - --merge=combine + # #- --sort-fields + # #- --strip-comments + # - --trailing-commas + # - --encode-urls + # - --remove-empty-fields + # - --wrap=80 # license header - repo: https://github.com/Lucas-C/pre-commit-hooks rev: v1.5.5 diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index 8d6855e16c..ea6c90cb57 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -5,6 +5,7 @@ Union, ) +import numpy as np import paddle from deepmd.dpmodel.utils.seed import ( @@ -493,7 +494,7 @@ def forward( # nf x nloc x a_nnei x a_nnei # 1 - 1e-6 for paddle.acos stability cosine_ij = paddle.matmul(normalized_diff_i, normalized_diff_j) * (1 - 1e-6) - angle_input = cosine_ij.unsqueeze(-1) / (paddle.pi**0.5) + angle_input = cosine_ij.unsqueeze(-1) / (np.pi**0.5) if not parallel_mode and self.use_loc_mapping: assert mapping is not None diff --git a/deepmd/pd/model/model/transform_output.py b/deepmd/pd/model/model/transform_output.py index 469bfd3168..7207fa68a0 100644 --- a/deepmd/pd/model/model/transform_output.py +++ b/deepmd/pd/model/model/transform_output.py @@ -27,6 +27,7 @@ def atomic_virial_corr( ce = coord * atom_energy sumce0, sumce1, sumce2 = paddle.split(paddle.sum(ce, axis=1), [1, 1, 1], axis=-1) # faked_grad = paddle.ones_like(sumce0) + raise extended_virial_corr0 = paddle.autograd.grad( [sumce0], [extended_coord], @@ -93,6 +94,9 @@ def task_deriv_one( ) else: extended_virial = None + print( + f"extended_force: {extended_force.min().item():.10f} {extended_force.max().item():.10f} {extended_force.mean().item():.10f} {extended_force.std().item():.10f}" + ) return extended_force, extended_virial diff --git a/deepmd/pd/train/training.py b/deepmd/pd/train/training.py index 44d0d16439..95d8292442 100644 --- a/deepmd/pd/train/training.py +++ b/deepmd/pd/train/training.py @@ -760,6 +760,38 @@ def step(_step_id, task_key="Default") -> None: pref_lr = _lr.start_lr else: pref_lr = cur_lr + self.wrapper.load_state_dict(paddle.load("./wrapper_dict.pd")) + print("model loaded") + inp = np.load("./input_dict.npz", allow_pickle=True) + for k, v in inp.items(): + if isinstance(v, np.ndarray): + # print(k, type(v), v.shape, v.dtype) + try: + input_dict[k] = paddle.to_tensor(v) + # print(k) + except Exception: + pass + if isinstance(input_dict[k], paddle.Tensor): + input_dict[k] = input_dict[k].cuda() + print("input_dict loaded") + lab = np.load("./label_dict.npz", allow_pickle=True) + for k, v in lab.items(): + if isinstance(v, np.ndarray): + # print(k, type(v), v.shape, v.dtype) + try: + label_dict[k] = paddle.to_tensor(v) + # print(k) + except Exception: + pass + if isinstance(label_dict[k], paddle.Tensor): + label_dict[k] = label_dict[k].cuda() + print("label_dict loaded") + model_pred, loss, more_loss = self.wrapper( + **input_dict, cur_lr=pref_lr, label=label_dict, task_key=task_key + ) + print({k: float(v) for k, v in more_loss.items()}) + print(f"{loss.item():.10f}") + exit() # disable synchronization in forward-backward manually # as derivatives exist in model forward @@ -779,7 +811,7 @@ def step(_step_id, task_key="Default") -> None: with nvprof_context(enable_profiling, "Backward pass"): loss.backward() - + exit() # fuse + allreduce manually before optimization if use DDP + no_sync # details in https://github.com/PaddlePaddle/Paddle/issues/48898#issuecomment-1343838622 if self.world_size > 1: diff --git a/deepmd/pd/train/wrapper.py b/deepmd/pd/train/wrapper.py index bd28b17c88..2f670758d3 100644 --- a/deepmd/pd/train/wrapper.py +++ b/deepmd/pd/train/wrapper.py @@ -173,6 +173,7 @@ def forward( model_pred = self.model[task_key](**input_dict) return model_pred, None, None else: + print(self.loss) natoms = atype.shape[-1] model_pred, loss, more_loss = self.loss[task_key]( input_dict, diff --git a/deepmd/pt/model/model/transform_output.py b/deepmd/pt/model/model/transform_output.py index b8f1e024e0..7d80c1cde1 100644 --- a/deepmd/pt/model/model/transform_output.py +++ b/deepmd/pt/model/model/transform_output.py @@ -96,6 +96,9 @@ def task_deriv_one( extended_virial = extended_virial.view(list(extended_virial.shape[:-2]) + [9]) # noqa:RUF005 else: extended_virial = None + print( + f"extended_force: {extended_force.min().item():.10f} {extended_force.max().item():.10f} {extended_force.mean().item():.10f} {extended_force.std().item():.10f}" + ) return extended_force, extended_virial diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py index 193dcd8cb9..d63ac07fbe 100644 --- a/deepmd/pt/train/training.py +++ b/deepmd/pt/train/training.py @@ -725,9 +725,64 @@ def step(_step_id, task_key="Default") -> None: pref_lr = _lr.start_lr else: pref_lr = cur_lr + + # save + # torch.save(self.wrapper.state_dict(), "wrapper_dict.pt") + # import paddle + # psd = {} + # for k, v in self.wrapper.state_dict().items(): + # if isinstance(v, torch.Tensor): + # psd[k] = paddle.from_dlpack(v.detach()) + # else: + # psd[k] = v + # paddle.save(psd, "wrapper_dict.pd") + # inp = {} + # for k, v in input_dict.items(): + # if isinstance(v, torch.Tensor): + # inp[k] = v.detach().cpu().numpy() + # else: + # inp[k] = v + # np.savez("./input_dict.npz", **inp) + # lab = {} + # for k, v in label_dict.items(): + # if isinstance(v, torch.Tensor): + # lab[k] = v.detach().cpu().numpy() + # else: + # lab[k] = v + # np.savez("./label_dict.npz", **lab) + + # load + self.wrapper.load_state_dict(torch.load("./wrapper_dict.pt")) + print("model loaded") + inp = np.load("./input_dict.npz", allow_pickle=True) + for k, v in inp.items(): + if isinstance(v, np.ndarray): + # print(k, type(v), v.shape, v.dtype) + try: + input_dict[k] = torch.tensor(v) + except TypeError: + pass + if isinstance(input_dict[k], torch.Tensor): + input_dict[k] = input_dict[k].cuda() + print("input_dict loaded") + lab = np.load("./label_dict.npz", allow_pickle=True) + for k, v in lab.items(): + if isinstance(v, np.ndarray): + # print(k, type(v), v.shape, v.dtype) + try: + label_dict[k] = torch.tensor(v) + except TypeError: + pass + if isinstance(label_dict[k], torch.Tensor): + label_dict[k] = label_dict[k].cuda() + print("label_dict loaded") + model_pred, loss, more_loss = self.wrapper( **input_dict, cur_lr=pref_lr, label=label_dict, task_key=task_key ) + print({k: float(v) for k, v in more_loss.items()}) + print(f"{loss.item():.10f}") + exit() loss.backward() if self.gradient_max_norm > 0.0: torch.nn.utils.clip_grad_norm_( diff --git a/deepmd/pt/train/wrapper.py b/deepmd/pt/train/wrapper.py index 9a2cbff295..9d8216795c 100644 --- a/deepmd/pt/train/wrapper.py +++ b/deepmd/pt/train/wrapper.py @@ -175,6 +175,7 @@ def forward( return model_pred, None, None else: natoms = atype.shape[-1] + print(self.loss) model_pred, loss, more_loss = self.loss[task_key]( input_dict, self.model[task_key], From 8fe0df6325f59f3fa7b359232fdde1cc13185ae0 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 19:16:46 +0800 Subject: [PATCH 02/32] support DPA2/DPA3 inference --- deepmd/pd/entrypoints/main.py | 17 +- deepmd/pd/model/descriptor/dpa2.py | 4 +- deepmd/pd/model/descriptor/repflows.py | 114 ++++- deepmd/pd/model/descriptor/repformer_layer.py | 1 + deepmd/pd/model/descriptor/repformers.py | 117 ++++- deepmd/pd/model/model/transform_output.py | 4 - deepmd/pd/utils/env.py | 2 +- source/CMakeLists.txt | 3 + source/api_cc/include/DeepPotPD.h | 11 + source/api_cc/src/DeepPotPD.cc | 79 +-- source/op/pd/CMakeLists.txt | 82 ++++ source/op/pd/comm.cc | 455 ++++++++++++++++++ 12 files changed, 832 insertions(+), 57 deletions(-) create mode 100644 source/op/pd/CMakeLists.txt create mode 100644 source/op/pd/comm.cc diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py index 8d96c4e6f2..3fee742dbd 100644 --- a/deepmd/pd/entrypoints/main.py +++ b/deepmd/pd/entrypoints/main.py @@ -388,14 +388,25 @@ def freeze( model.forward_lower = paddle.jit.to_static( model.forward_lower, input_spec=[ - InputSpec([1, -1, 3], dtype="float64", name="coord"), # extended_coord - InputSpec([1, -1], dtype="int32", name="atype"), # extended_atype + InputSpec( + [1, -1, 3], dtype="float64", name="extended_coord" + ), # extended_coord + InputSpec( + [1, -1], dtype="int32", name="extended_atype" + ), # extended_atype InputSpec([1, -1, -1], dtype="int32", name="nlist"), # nlist InputSpec([1, -1], dtype="int64", name="mapping"), # mapping None, # fparam None, # aparam True, # do_atomic_virial - None, # comm_dict + [ + InputSpec([-1], "int32", name="send_list"), + InputSpec([-1], "int32", name="send_proc"), + InputSpec([-1], "int32", name="recv_proc"), + InputSpec([-1], "int32", name="send_num"), + InputSpec([-1], "int32", name="recv_num"), + InputSpec([-1], "int64", name="communicator"), + ], # comm_dict ], full_graph=True, ) diff --git a/deepmd/pd/model/descriptor/dpa2.py b/deepmd/pd/model/descriptor/dpa2.py index 44b3229f66..02bfedb33a 100644 --- a/deepmd/pd/model/descriptor/dpa2.py +++ b/deepmd/pd/model/descriptor/dpa2.py @@ -798,8 +798,8 @@ def forward( assert self.tebd_transform is not None g1 = g1 + self.tebd_transform(g1_inp) # mapping g1 - if comm_dict is None: - assert mapping is not None + if comm_dict is None or len(comm_dict) == 0: + assert mapping.numel() > 0 mapping_ext = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index ea6c90cb57..ebab00421e 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -11,6 +11,10 @@ from deepmd.dpmodel.utils.seed import ( child_seed, ) +from deepmd.pd.cxx_op import ( + ENABLE_CUSTOMIZED_OP, + paddle_ops_deepmd, +) from deepmd.pd.model.descriptor.descriptor import ( DescriptorBlock, ) @@ -35,6 +39,9 @@ from deepmd.pd.utils.exclude_mask import ( PairExcludeMask, ) +from deepmd.pd.utils.spin import ( + concat_switch_virtual, +) from deepmd.pd.utils.utils import ( ActivationFn, ) @@ -49,6 +56,29 @@ RepFlowLayer, ) +if not ENABLE_CUSTOMIZED_OP: + + def border_op( + argument0, + argument1, + argument2, + argument3, + argument4, + argument5, + argument6, + argument7, + argument8, + ) -> paddle.Tensor: + raise NotImplementedError( + "border_op is not available since customized Paddle OP library is not built when freezing the model. " + "See documentation for DPA3 for details." + ) + + # Note: this hack cannot actually save a model that can be run using LAMMPS. + paddle_ops_deepmd_border_op = border_op +else: + paddle_ops_deepmd_border_op = paddle_ops_deepmd.border_op + @DescriptorBlock.register("se_repflow") class DescrptBlockRepflows(DescriptorBlock): @@ -418,13 +448,14 @@ def forward( ): parallel_mode = comm_dict is not None if not parallel_mode: - assert mapping is not None + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 nframes, nloc, nnei = nlist.shape nall = extended_coord.reshape([nframes, -1]).shape[1] // 3 atype = extended_atype[:, :nloc] # nb x nloc x nnei exclude_mask = self.emask(nlist, extended_atype) - nlist = paddle.where(exclude_mask != 0, nlist, -1) + nlist = paddle.where(exclude_mask != 0, nlist, paddle.full_like(nlist, -1)) # nb x nloc x nnei x 4, nb x nloc x nnei x 3, nb x nloc x nnei x 1 dmatrix, diff, sw = prod_env_mat( extended_coord, @@ -447,7 +478,7 @@ def forward( :, :, : self.a_sel ] a_nlist = nlist[:, :, : self.a_sel] - a_nlist = paddle.where(a_dist_mask, a_nlist, -1) + a_nlist = paddle.where(a_dist_mask, a_nlist, paddle.full_like(a_nlist, -1)) _, a_diff, a_sw = prod_env_mat( extended_coord, a_nlist, @@ -497,7 +528,8 @@ def forward( angle_input = cosine_ij.unsqueeze(-1) / (np.pi**0.5) if not parallel_mode and self.use_loc_mapping: - assert mapping is not None + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 # convert nlist from nall to nloc index nlist = paddle.take_along_axis( mapping, @@ -542,7 +574,8 @@ def forward( # nb x nall x n_dim if not parallel_mode: - assert mapping is not None + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 mapping = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) @@ -552,14 +585,81 @@ def forward( # node_ebd: nb x nloc x n_dim # node_ebd_ext: nb x nall x n_dim [OR] nb x nloc x n_dim when not parallel_mode if not parallel_mode: - assert mapping is not None + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 node_ebd_ext = ( paddle.take_along_axis(node_ebd, mapping, 1, broadcast=False) if not self.use_loc_mapping else node_ebd ) else: - raise NotImplementedError("Not implemented") + assert len(comm_dict) >= 6 + has_spin = len(comm_dict) >= 7 + if not has_spin: + n_padding = nall - nloc + # node_ebd = paddle.nn.functional.pad( + # node_ebd.squeeze(0), [0, 0, 0, n_padding], value=0.0 + # ) + # [nframes, nloc, tebd_dim] + _shapes = node_ebd.shape[1:] + _shapes[1] = n_padding + node_ebd = paddle.concat( + [node_ebd, paddle.zeros(_shapes, dtype=node_ebd.dtype)], + axis=1, + ) + real_nloc = nloc + real_nall = nall + else: + # for spin + real_nloc = nloc // 2 + real_nall = nall // 2 + real_n_padding = real_nall - real_nloc + node_ebd_real, node_ebd_virtual = paddle.split( + node_ebd, [real_nloc, real_nloc], axis=1 + ) + # mix_node_ebd: nb x real_nloc x (n_dim * 2) + mix_node_ebd = paddle.concat( + [node_ebd_real, node_ebd_virtual], axis=2 + ) + # nb x real_nall x (n_dim * 2) + node_ebd = paddle.nn.functional.pad( + mix_node_ebd.squeeze(0), (0, 0, 0, real_n_padding), value=0.0 + ) + + assert len(comm_dict) >= 6 + # assert "send_list" in comm_dict + # assert "send_proc" in comm_dict + # assert "recv_proc" in comm_dict + # assert "send_num" in comm_dict + # assert "recv_num" in comm_dict + # assert "communicator" in comm_dict + ret = paddle_ops_deepmd_border_op( + comm_dict[0], + comm_dict[1], + comm_dict[2], + comm_dict[3], + comm_dict[4], + node_ebd, + comm_dict[5], + paddle.to_tensor( + real_nloc, + dtype=paddle.int32, + place=paddle.CPUPlace(), + ), # should be int of c++, placed on cpu + paddle.to_tensor( + real_nall - real_nloc, + dtype=paddle.int32, + place=paddle.CPUPlace(), + ), # should be int of c++, placed on cpu + ) + node_ebd_ext = ret[0].unsqueeze(0) + if has_spin: + node_ebd_real_ext, node_ebd_virtual_ext = paddle.split( + node_ebd_ext, [n_dim, n_dim], axis=2 + ) + node_ebd_ext = concat_switch_virtual( + node_ebd_real_ext, node_ebd_virtual_ext, real_nloc + ) node_ebd, edge_ebd, angle_ebd = ll.forward( node_ebd_ext, edge_ebd, diff --git a/deepmd/pd/model/descriptor/repformer_layer.py b/deepmd/pd/model/descriptor/repformer_layer.py index 4dad08fff8..697476e611 100644 --- a/deepmd/pd/model/descriptor/repformer_layer.py +++ b/deepmd/pd/model/descriptor/repformer_layer.py @@ -110,6 +110,7 @@ def _make_nei_g1( # index: nb x (nloc x nnei) x ng1 index = nlist.reshape([nb, nloc * nnei]).unsqueeze(-1).expand([-1, -1, ng1]) # gg1 : nb x (nloc x nnei) x ng1 + # print(g1_ext.shape, index.shape) gg1 = paddle.take_along_axis(g1_ext, indices=index, axis=1, broadcast=False) # gg1 : nb x nloc x nnei x ng1 gg1 = gg1.reshape([nb, nloc, nnei, ng1]) diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index d2fab44c5e..149717831b 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -10,6 +10,10 @@ from deepmd.dpmodel.utils.seed import ( child_seed, ) +from deepmd.pd.cxx_op import ( + ENABLE_CUSTOMIZED_OP, + paddle_ops_deepmd, +) from deepmd.pd.model.descriptor.descriptor import ( DescriptorBlock, ) @@ -31,6 +35,9 @@ from deepmd.pd.utils.exclude_mask import ( PairExcludeMask, ) +from deepmd.pd.utils.spin import ( + concat_switch_virtual, +) from deepmd.pd.utils.utils import ( ActivationFn, ) @@ -45,6 +52,29 @@ RepformerLayer, ) +if not ENABLE_CUSTOMIZED_OP: + + def border_op( + argument0, + argument1, + argument2, + argument3, + argument4, + argument5, + argument6, + argument7, + argument8, + ) -> paddle.Tensor: + raise NotImplementedError( + "border_op is not available since customized Paddle OP library is not built when freezing the model. " + "See documentation for DPA3 for details." + ) + + # Note: this hack cannot actually save a model that can be run using LAMMPS. + paddle_ops_deepmd_border_op = border_op +else: + paddle_ops_deepmd_border_op = paddle_ops_deepmd.border_op + @DescriptorBlock.register("se_repformer") @DescriptorBlock.register("se_uni") @@ -380,9 +410,10 @@ def forward( type_embedding: Optional[paddle.Tensor] = None, comm_dict: Optional[dict[str, paddle.Tensor]] = None, ): - if comm_dict is None: - assert mapping is not None - assert extended_atype_embd is not None + if comm_dict is None or len(comm_dict) == 0: + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 + assert extended_atype_embd is not None or extended_atype_embd.numel() > 0 nframes, nloc, nnei = nlist.shape nall = extended_coord.reshape([nframes, -1]).shape[1] // 3 atype = extended_atype[:, :nloc] @@ -406,7 +437,7 @@ def forward( sw = sw.masked_fill(~nlist_mask, 0.0) # [nframes, nloc, tebd_dim] - if comm_dict is None: + if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): assert isinstance(extended_atype_embd, paddle.Tensor) # for jit atype_embd = extended_atype_embd[:, :nloc, :] @@ -432,8 +463,9 @@ def forward( # if the a neighbor is real or not is indicated by nlist_mask nlist[nlist == -1] = 0 # nb x nall x ng1 - if comm_dict is None: - assert mapping is not None + if comm_dict is None or len(comm_dict) == 0: + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 mapping = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) @@ -442,13 +474,80 @@ def forward( for idx, ll in enumerate(self.layers): # g1: nb x nloc x ng1 # g1_ext: nb x nall x ng1 - if comm_dict is None: - assert mapping is not None + if comm_dict is None or len(comm_dict) == 0: + if paddle.in_dynamic_mode(): + assert mapping is not None and mapping.numel() > 0 g1_ext = paddle.take_along_axis( g1, axis=1, indices=mapping, broadcast=False ) else: - raise NotImplementedError("Not implemented yet") + has_spin = len(comm_dict) >= 7 + if not has_spin: + n_padding = nall - nloc + # g1 = paddle.nn.functional.pad( + # g1.squeeze(0), (0, 0, 0, n_padding), value=0.0 + # ) + _shapes = g1.shape[1:] + _shapes[1] = n_padding + g1 = paddle.concat( + [g1.squeeze(0), paddle.zeros(_shapes, dtype=g1.dtype)], + axis=1, + ) + real_nloc = nloc + real_nall = nall + else: + # for spin + real_nloc = nloc // 2 + real_nall = nall // 2 + real_n_padding = real_nall - real_nloc + g1_real, g1_virtual = paddle.split( + g1, [real_nloc, real_nloc], axis=1 + ) + # mix_g1: nb x real_nloc x (ng1 * 2) + mix_g1 = paddle.concat([g1_real, g1_virtual], axis=2) + # nb x real_nall x (ng1 * 2) + g1 = paddle.nn.functional.pad( + mix_g1.squeeze(0), (0, 0, 0, real_n_padding), value=0.0 + ) + + # assert "send_list" in comm_dict + # assert "send_proc" in comm_dict + # assert "recv_proc" in comm_dict + # assert "send_num" in comm_dict + # assert "recv_num" in comm_dict + # assert "communicator" in comm_dict + # print(f"g1.shape = ", g1.shape) + ret = paddle_ops_deepmd_border_op( + comm_dict[0], + comm_dict[1], + comm_dict[2], + comm_dict[3], + comm_dict[4], + g1, + comm_dict[5], + paddle.to_tensor( + real_nloc, + dtype=paddle.int32, + place=paddle.CPUPlace(), + ), # should be int of c++, placed on cpu + paddle.to_tensor( + real_nall - real_nloc, + dtype=paddle.int32, + place=paddle.CPUPlace(), + ), # should be int of c++, placed on cpu + ) + # print(f"ret.shape = {ret.shape}") + # print(f"ret[0].shape = ", ret[0].shape) + g1_ext = ret.unsqueeze(0) + # print(f"g1_ext.shape = ", g1_ext.shape) + # exit() + if has_spin: + g1_real_ext, g1_virtual_ext = paddle.split( + g1_ext, [ng1, ng1], dim=2 + ) + g1_ext = concat_switch_virtual( + g1_real_ext, g1_virtual_ext, real_nloc + ) g1, g2, h2 = ll.forward( g1_ext, diff --git a/deepmd/pd/model/model/transform_output.py b/deepmd/pd/model/model/transform_output.py index 7207fa68a0..469bfd3168 100644 --- a/deepmd/pd/model/model/transform_output.py +++ b/deepmd/pd/model/model/transform_output.py @@ -27,7 +27,6 @@ def atomic_virial_corr( ce = coord * atom_energy sumce0, sumce1, sumce2 = paddle.split(paddle.sum(ce, axis=1), [1, 1, 1], axis=-1) # faked_grad = paddle.ones_like(sumce0) - raise extended_virial_corr0 = paddle.autograd.grad( [sumce0], [extended_coord], @@ -94,9 +93,6 @@ def task_deriv_one( ) else: extended_virial = None - print( - f"extended_force: {extended_force.min().item():.10f} {extended_force.max().item():.10f} {extended_force.mean().item():.10f} {extended_force.std().item():.10f}" - ) return extended_force, extended_virial diff --git a/deepmd/pd/utils/env.py b/deepmd/pd/utils/env.py index 28606d0945..4a0efde4fd 100644 --- a/deepmd/pd/utils/env.py +++ b/deepmd/pd/utils/env.py @@ -137,7 +137,7 @@ def enable_prim(enable: bool = True): "exp_grad", "expand_grad", "floor_grad", - "gather_grad", + # "gather_grad", "gather_nd_grad", "gelu_grad", "group_norm_grad", diff --git a/source/CMakeLists.txt b/source/CMakeLists.txt index a678802a35..f106b6109a 100644 --- a/source/CMakeLists.txt +++ b/source/CMakeLists.txt @@ -526,6 +526,9 @@ if(NOT DEEPMD_C_ROOT) if(ENABLE_PYTORCH) add_subdirectory(op/pt/) endif() + if(ENABLE_PADDLE) + add_subdirectory(op/pd/) + endif() add_subdirectory(lib/) endif() if(BUILD_PY_IF) diff --git a/source/api_cc/include/DeepPotPD.h b/source/api_cc/include/DeepPotPD.h index ec43300ca0..488e4fe6b5 100644 --- a/source/api_cc/include/DeepPotPD.h +++ b/source/api_cc/include/DeepPotPD.h @@ -392,6 +392,17 @@ class DeepPotPD : public DeepPotBackend { int do_message_passing; // 1:dpa2 model 0:others bool gpu_enabled; std::unique_ptr firstneigh_tensor; + std::vector comm_vec; + paddle_infer::Tensor mapping_tensor = predictor_fl->GetInputHandle("mapping"); + /* comm_vec flatten all the communicatoin tensors below from comm dict: + - send_list + - send_proc + - recv_proc + - send_num + - recv_num + - communicator + */ + // std::unordered_map comm_dict; # Not used yet }; diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 3a3d880c4b..d38ef05276 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -192,11 +192,11 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, int nloc = nall_real - nghost_real; int nframes = 1; std::vector coord_wrapped = dcoord; - auto coord_wrapped_Tensor = predictor_fl->GetInputHandle("coord"); + auto coord_wrapped_Tensor = predictor_fl->GetInputHandle("extended_coord"); coord_wrapped_Tensor->Reshape({1, nall_real, 3}); coord_wrapped_Tensor->CopyFromCpu(coord_wrapped.data()); - auto atype_Tensor = predictor_fl->GetInputHandle("atype"); + auto atype_Tensor = predictor_fl->GetInputHandle("extended_atype"); atype_Tensor->Reshape({1, nall_real}); atype_Tensor->CopyFromCpu(datype.data()); @@ -205,37 +205,54 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, nlist_data.shuffle_exclude_empty(fwd_map); nlist_data.padding(); if (do_message_passing == 1 && nghost > 0) { - throw deepmd::deepmd_exception( - "(do_message_passing == 1 && nghost > 0) is not supported yet."); - // int nswap = lmp_list.nswap; - // auto sendproc_tensor = predictor_fl->GetInputHandle("sendproc"); - // sendproc_tensor->Reshape({nswap}); - // sendproc_tensor->CopyFromCpu(lmp_list.sendproc); - // auto recvproc_tensor = predictor_fl->GetInputHandle("recvproc"); - // recvproc_tensor->Reshape({nswap}); - // recvproc_tensor->CopyFromCpu(lmp_list.recvproc); - // auto firstrecv_tensor = predictor_fl->GetInputHandle("firstrecv"); - // firstrecv_tensor->Reshape({nswap}); - // firstrecv_tensor->CopyFromCpu(lmp_list.firstrecv); - // auto recvnum_tensor = predictor_fl->GetInputHandle("recvnum"); - // recvnum_tensor->Reshape({nswap}); - // recvnum_tensor->CopyFromCpu(lmp_list.recvnum); - // auto sendnum_tensor = predictor_fl->GetInputHandle("sendnum"); - // sendnum_tensor->Reshape({nswap}); - // sendnum_tensor->CopyFromCpu(lmp_list.sendnum); - // auto communicator_tensor = - // predictor_fl->GetInputHandle("communicator"); - // communicator_tensor->Reshape({1}); - // communicator_tensor->CopyFromCpu(static_cast(lmp_list.world)); - // auto sendlist_tensor = predictor_fl->GetInputHandle("sendlist"); - - // int total_send = - // std::accumulate(lmp_list.sendnum, lmp_list.sendnum + nswap, 0); + // throw deepmd::deepmd_exception( + // "(do_message_passing == 1 && nghost > 0) is not supported yet."); + int nswap = lmp_list.nswap; + auto sendproc_tensor = predictor_fl->GetInputHandle("sendproc"); + sendproc_tensor->Reshape({nswap}); + sendproc_tensor->CopyFromCpu(lmp_list.sendproc); + auto recvproc_tensor = predictor_fl->GetInputHandle("recvproc"); + recvproc_tensor->Reshape({nswap}); + recvproc_tensor->CopyFromCpu(lmp_list.recvproc); + auto firstrecv_tensor = predictor_fl->GetInputHandle("firstrecv"); + firstrecv_tensor->Reshape({nswap}); + firstrecv_tensor->CopyFromCpu(lmp_list.firstrecv); + auto recvnum_tensor = predictor_fl->GetInputHandle("recvnum"); + recvnum_tensor->Reshape({nswap}); + recvnum_tensor->CopyFromCpu(lmp_list.recvnum); + auto sendnum_tensor = predictor_fl->GetInputHandle("sendnum"); + sendnum_tensor->Reshape({nswap}); + sendnum_tensor->CopyFromCpu(lmp_list.sendnum); + auto communicator_tensor = predictor_fl->GetInputHandle("communicator"); + communicator_tensor->Reshape({1}); + if (lmp_list.world > 0) { + communicator_tensor->CopyFromCpu(static_cast(lmp_list.world)); + } + int total_send = + std::accumulate(lmp_list.sendnum, lmp_list.sendnum + nswap, 0); + auto sendlist_tensor = predictor_fl->GetInputHandle("sendlist"); + sendlist_tensor->Reshape({total_send}); + sendlist_tensor->CopyFromCpu(lmp_list.sendlist); + + this->comm_vec.emplace_back(sendlist_tensor); + this->comm_vec.emplace_back(sendproc_tensor); + this->comm_vec.emplace_back(recvproc_tensor); + this->comm_vec.emplace_back(sendnum_tensor); + this->comm_vec.emplace_back(recvnum_tensor); + this->comm_vec.emplace_back(communicator_tensor); } - if (do_message_passing == 1 && nghost == 0) { - throw deepmd::deepmd_exception( - "(do_message_passing == 1 && nghost == 0) is not supported yet."); + if (lmp_list.mapping) { + std::vector mapping(nall_real); + for (size_t ii = 0; ii < nall_real; ii++) { + mapping[ii] = lmp_list.mapping[fwd_map[ii]]; + } + this->mapping_tensor->Reshape({1, nall_real}); + this->mapping_tensor->CopyFromCpu(mapping.data()); } + // if (do_message_passing == 1 && nghost == 0) { + // throw deepmd::deepmd_exception( + // "(do_message_passing == 1 && nghost == 0) is not supported yet."); + // } } std::vector firstneigh = createNlistTensorPD(nlist_data.jlist); firstneigh_tensor = predictor_fl->GetInputHandle("nlist"); diff --git a/source/op/pd/CMakeLists.txt b/source/op/pd/CMakeLists.txt new file mode 100644 index 0000000000..8794069213 --- /dev/null +++ b/source/op/pd/CMakeLists.txt @@ -0,0 +1,82 @@ +file(GLOB OP_SRC comm.cc) +add_library(deepmd_op_pd MODULE ${OP_SRC}) + +# ========== 新增：Paddle 配置（路径由用户外部传入） ========== +if(NOT DEFINED PADDLE_LIB) + message( + FATAL_ERROR + "please set PADDLE_LIB with -DPADDLE_LIB=/path/to/paddle_inference") +endif() + +set(PADDLE_LIB_THIRD_PARTY_PATH ${PADDLE_LIB}/third_party/install) +include_directories(${PADDLE_LIB}) +include_directories(${PADDLE_LIB}/paddle/include) +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/include) +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/glog/include) +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/include) +include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/include) + +# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib) +# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib) +# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib) +# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib) +# link_directories(${PADDLE_LIB}/paddle/lib) target_link_libraries(deepmd_op_pd +# PRIVATE ${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib/libglog.a +# ${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib/libgflags.a +# ${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib/libxxhash.a +# ${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib/libprotobuf.a dl pthread) + +# Paddle lib +set(PADDLE_INFER_LIB ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so) +# Math lib（默认用MKL） +set(MKLML_LIB ${PADDLE_LIB_THIRD_PARTY_PATH}/mklml/lib/libmklml_intel.so + ${PADDLE_LIB_THIRD_PARTY_PATH}/mklml/lib/libiomp5.so) + +# ========== 原有逻辑：保持不动 ========== +# target_link_libraries(deepmd_op_pd PRIVATE ${PADDLE_LIBRARIES}) +# if(${OP_CXX_ABI_PT} EQUAL ${OP_CXX_ABI}) target_link_libraries(deepmd_op_pd +# PRIVATE ${LIB_DEEPMD}) else() target_link_libraries(deepmd_op_pd PRIVATE +# ${LIB_DEEPMD}_compat_cxxabi) endif() +# remove_definitions(-D_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI}) +# target_compile_definitions( deepmd_op_pd PUBLIC +# "$<$:_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI_PT}>") +# if(APPLE) set_target_properties(deepmd_op_pd PROPERTIES INSTALL_RPATH +# "@loader_path") else() set_target_properties(deepmd_op_pd PROPERTIES +# INSTALL_RPATH "$ORIGIN") endif() + +find_package(MPI) +if(MPI_FOUND) + include(CheckCXXSymbolExists) + set(CMAKE_REQUIRED_INCLUDES ${MPI_CXX_INCLUDE_DIRS}) + set(CMAKE_REQUIRED_LIBRARIES ${MPI_CXX_LIBRARIES}) + check_cxx_symbol_exists(MPIX_Query_cuda_support "mpi.h" CUDA_AWARE) + if(NOT CUDA_AWARE) + check_cxx_symbol_exists(MPIX_Query_cuda_support "mpi.h;mpi-ext.h" OMP_CUDA) + if(NOT OMP_CUDA) + target_compile_definitions(deepmd_op_pd PRIVATE NO_CUDA_AWARE) + endif() + endif() + target_link_libraries(deepmd_op_pd PRIVATE MPI::MPI_CXX) + target_compile_definitions(deepmd_op_pd PRIVATE USE_MPI) +endif() +if(CMAKE_TESTING_ENABLED) + target_link_libraries(deepmd_op_pd PRIVATE coverage_config) +endif() + +# ========== 新增：链接 Paddle 所需库 ========== +target_link_libraries( + deepmd_op_pd + PRIVATE ${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib/libglog.a + ${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib/libgflags.a + ${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib/libxxhash.a + ${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib/libprotobuf.a + ${PADDLE_INFER_LIB} + dl + pthread) + +# ========== 保持原有安装路径逻辑 ========== +if(BUILD_PY_IF) + install(TARGETS deepmd_op_pd DESTINATION deepmd/lib/) +else(BUILD_PY_IF) + install(TARGETS deepmd_op_pd DESTINATION lib/) +endif(BUILD_PY_IF) diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc new file mode 100644 index 0000000000..26580f25a3 --- /dev/null +++ b/source/op/pd/comm.cc @@ -0,0 +1,455 @@ +// SPDX-License-Identifier: LGPL-3.0-or-later + +#ifdef USE_MPI +#include +#ifdef OMPI_MPI_H +#include +#endif +#endif +// #include +#include + +#include "paddle/extension.h" + +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) +#include "device.h" +#endif + +#ifdef USE_MPI +template +static MPI_Datatype get_mpi_type(); + +template <> +MPI_Datatype get_mpi_type() { + return MPI_FLOAT; +} + +template <> +MPI_Datatype get_mpi_type() { + return MPI_DOUBLE; +} +#endif + +#ifdef USE_MPI +static void unpack_communicator(const paddle::Tensor& communicator_tensor, + MPI_Comm& mpi_comm) { +#ifdef OMPI_MPI_H + const int64_t* communicator = communicator_tensor.data(); +#else + const int64_t* ptr = communicator_tensor.data(); + const int* communicator = reinterpret_cast(ptr); +#endif + mpi_comm = reinterpret_cast(*communicator); +} +#endif + +template +void Border_forward_t(const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + paddle::Tensor& g1, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor) { + int** sendlist = reinterpret_cast((sendlist_tensor + 0).data()); + const int* sendproc = sendproc_tensor.data(); + const int* recvproc = recvproc_tensor.data(); + const int* sendnum = sendnum_tensor.data(); + const int* recvnum = recvnum_tensor.data(); + int tensor_size = g1.dims()[1]; + int nswap = sendproc_tensor.dims()[0]; + + int nlocal = *nlocal_tensor.data(); + int nghost = *nghost_tensor.data(); + int ntotal = nlocal + nghost; + paddle::Tensor recv_g1_tensor = g1; + +#ifdef USE_MPI + int mpi_init = 0; + MPI_Initialized(&mpi_init); + int cuda_aware = 1; + int me = 0; + MPI_Comm world; + int world_size = 0; + if (mpi_init) { + unpack_communicator(communicator_tensor, world); + MPI_Comm_rank(world, &me); + MPI_Comm_size(world, &world_size); + } + MPI_Datatype mpi_type = get_mpi_type(); + MPI_Request request; +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + if (world_size >= 1) { + int version, subversion; + MPI_Get_version(&version, &subversion); + if (version >= 4) { +#ifdef NO_CUDA_AWARE + cuda_aware = 0; +#else + cuda_aware = MPIX_Query_cuda_support(); +#endif + } else { + cuda_aware = 0; + } + if (cuda_aware == 0) { + recv_g1_tensor = paddle::empty_like(g1, g1.dtype(), paddle::CPUPlace()); + recv_g1_tensor = g1.copy_to(recv_g1_tensor.place()); + // recv_g1_tensor.copy_(g1); + } + } +#endif +#endif + FPTYPE* recv_g1 = recv_g1_tensor.data() + nlocal * tensor_size; + // auto int32_options = torch::TensorOptions().dtype(torch::kInt32); + for (int iswap = 0; iswap < nswap; ++iswap) { + int nrecv = recvnum[iswap]; + int nsend = sendnum[iswap]; + paddle::Tensor isendlist; + paddle::Tensor send_g1_tensor; + FPTYPE* send_g1; + if (nsend != 0) { + isendlist = paddle::from_blob( + static_cast(sendlist[iswap]), {nsend}, paddle::DataType::INT32, + phi::DataLayout::NCHW, recv_g1_tensor.place()); + send_g1_tensor = paddle::gather(recv_g1_tensor, isendlist, 0); + send_g1 = send_g1_tensor.data(); + } +#ifdef USE_MPI + if (sendproc[iswap] != me) { + if (nrecv) { + MPI_Irecv(recv_g1, nrecv * tensor_size, mpi_type, recvproc[iswap], 0, + world, &request); + } + if (nsend) { + MPI_Send(send_g1, nsend * tensor_size, mpi_type, sendproc[iswap], 0, + world); + } + if (nrecv) { + MPI_Wait(&request, MPI_STATUS_IGNORE); + } + } else { +#endif +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) +#ifdef USE_MPI + if (cuda_aware == 0) { + memcpy(recv_g1, send_g1, + (unsigned long)nsend * tensor_size * sizeof(FPTYPE)); + } else { + gpuMemcpy(recv_g1, send_g1, + (unsigned long)nsend * tensor_size * sizeof(FPTYPE), + gpuMemcpyDeviceToDevice); + } +#else + gpuMemcpy(recv_g1, send_g1, + (unsigned long)nsend * tensor_size * sizeof(FPTYPE), + gpuMemcpyDeviceToDevice); +#endif +#else + memcpy(recv_g1, send_g1, + (unsigned long)nsend * tensor_size * sizeof(FPTYPE)); +#endif +#ifdef USE_MPI + } +#endif + recv_g1 += nrecv * tensor_size; + } +#ifdef USE_MPI +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + if (cuda_aware == 0) { + g1.copy_(recv_g1_tensor); + } +#endif +#endif + // return {g1}; +} + +void Border_forward(const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + paddle::Tensor& g1, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor) { + bool type_flag = (g1.dtype() == phi::DataType::FLOAT64) ? true : false; + if (type_flag) { + Border_forward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, + sendnum_tensor, recvnum_tensor, g1, + communicator_tensor, nlocal_tensor, nghost_tensor); + } else { + Border_forward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, + sendnum_tensor, recvnum_tensor, g1, + communicator_tensor, nlocal_tensor, nghost_tensor); + } +} + +template +std::vector Border_backward_t( + const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor, + paddle::Tensor& recv_g1_tensor_grad // grad_output[0] +) { +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + gpuDeviceSynchronize(); +#endif + paddle::Tensor d_local_g1_tensor = (recv_g1_tensor_grad + 0).contiguous(); +#ifdef USE_MPI + int mpi_init = 0; + MPI_Initialized(&mpi_init); + int world_size = 0; + int cuda_aware = 1; + int me = 0; + MPI_Comm world; + if (mpi_init) { + unpack_communicator(communicator_tensor, world); + MPI_Comm_rank(world, &me); + MPI_Comm_size(world, &world_size); + } + MPI_Datatype mpi_type = get_mpi_type(); + MPI_Request request; +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + if (world_size >= 1) { + int version, subversion; + MPI_Get_version(&version, &subversion); + if (version >= 4) { +#ifdef NO_CUDA_AWARE + cuda_aware = 0; +#else + cuda_aware = MPIX_Query_cuda_support(); +#endif + } else { + cuda_aware = 0; + } + if (cuda_aware == 0) { + d_local_g1_tensor = paddle::empty_like( + recv_g1_tensor_grad, recv_g1_tensor_grad.dtype(), paddle::CPUPlace()); + d_local_g1_tensor = + recv_g1_tensor_grad.copy_to(d_local_g1_tensor.place()); + } + } +#endif +#endif + int** recvlist = reinterpret_cast((sendlist_tensor + 0).data()); + // swap send and recv here + const int* recvproc = sendproc_tensor.data(); + const int* sendproc = recvproc_tensor.data(); + const int* recvnum = sendnum_tensor.data(); + const int* sendnum = recvnum_tensor.data(); + + FPTYPE* local_g1 = d_local_g1_tensor.data(); + int tensor_size = d_local_g1_tensor.dims()[1]; + int nswap = sendproc_tensor.dims()[0]; + + int nlocal = *nlocal_tensor.data(); + int nghost = *nghost_tensor.data(); + int ntotal = nlocal + nghost; + paddle::Tensor send_g1_tensor; + paddle::Tensor recv_g1_tensor; + FPTYPE* recv_g1; + FPTYPE* send_g1; + if (nswap != 0) { + send_g1_tensor = d_local_g1_tensor; + int max_recvnum = *sendnum_tensor.max().data(); + recv_g1_tensor = + paddle::empty({max_recvnum, tensor_size}, d_local_g1_tensor.dtype(), + d_local_g1_tensor.place()); + recv_g1 = recv_g1_tensor.data(); + send_g1 = send_g1_tensor.data() + ntotal * tensor_size; + } + + int end = ntotal; + // auto int32_options = torch::TensorOptions().dtype(torch::kInt32); + for (int iswap = nswap - 1; iswap >= 0; --iswap) { + int nrecv = recvnum[iswap]; + int nsend = sendnum[iswap]; + + paddle::Tensor irecvlist; + if (nrecv) { + irecvlist = paddle::from_blob( + static_cast(recvlist[iswap]), {nrecv}, paddle::DataType::INT32, + paddle::DataLayout::NCHW, d_local_g1_tensor.place()); + } + if (nsend) { + send_g1 -= nsend * tensor_size; + } +#ifdef USE_MPI + if (sendproc[iswap] != me) { + if (nrecv) { + MPI_Irecv(recv_g1, nrecv * tensor_size, mpi_type, recvproc[iswap], 0, + world, &request); + } + if (nsend) { + MPI_Send(send_g1, nsend * tensor_size, mpi_type, sendproc[iswap], 0, + world); + } + if (nrecv) { + MPI_Wait(&request, MPI_STATUS_IGNORE); + } + } else { +#endif + if (nrecv) { +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) +#ifdef USE_MPI + if (cuda_aware == 0) { + memcpy(recv_g1, send_g1, + (unsigned long)nrecv * tensor_size * sizeof(FPTYPE)); + } else { + gpuMemcpy(recv_g1, send_g1, + (unsigned long)nrecv * tensor_size * sizeof(FPTYPE), + gpuMemcpyDeviceToDevice); + } +#else + gpuMemcpy(recv_g1, send_g1, + (unsigned long)nrecv * tensor_size * sizeof(FPTYPE), + gpuMemcpyDeviceToDevice); +#endif +#else + memcpy(recv_g1, send_g1, + (unsigned long)nrecv * tensor_size * sizeof(FPTYPE)); +#endif + } +#ifdef USE_MPI + } +#endif + if (nrecv) { + d_local_g1_tensor = paddle::experimental::index_add_( + d_local_g1_tensor, irecvlist, recv_g1_tensor.slice(0, nrecv), 0); + } + } +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + gpuDeviceSynchronize(); +#endif +#ifdef USE_MPI +#if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) + if (cuda_aware == 0) { + recv_g1_tensor_grad = + d_local_g1_tensor.copy_to(recv_g1_tensor_grad.place()); + // grad_output[0].copy_(d_local_g1_tensor); + } +#endif +#endif + return {paddle::Tensor(), paddle::Tensor(), paddle::Tensor(), + paddle::Tensor(), paddle::Tensor(), recv_g1_tensor_grad, + paddle::Tensor(), paddle::Tensor(), paddle::Tensor()}; +} + +std::vector Border_backward( + const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor, + paddle::Tensor& recv_g1_tensor_grad) { + bool type_flag = + (sendlist_tensor.dtype() == paddle::DataType::FLOAT64) ? true : false; + if (type_flag) { + return Border_backward_t( + sendlist_tensor, sendproc_tensor, recvproc_tensor, sendnum_tensor, + recvnum_tensor, communicator_tensor, nlocal_tensor, nghost_tensor, + recv_g1_tensor_grad); + } else { + return Border_backward_t( + sendlist_tensor, sendproc_tensor, recvproc_tensor, sendnum_tensor, + recvnum_tensor, communicator_tensor, nlocal_tensor, nghost_tensor, + recv_g1_tensor_grad); + } +} + +std::vector> Border_forwardInferShape( + std::vector sendlist_tensor_shape, + std::vector sendproc_tensor_shape, + std::vector recvproc_tensor_shape, + std::vector sendnum_tensor_shape, + std::vector recvnum_tensor_shape, + std::vector g1_tensor_shape, + std::vector communicator_tensor_shape, + std::vector nlocal_tensor_shape, + std::vector nghost_tenso_shape) { + return {g1_tensor_shape}; +} + +std::vector Border_forwardInferDtype( + paddle::DataType sendlist_tensor_dtype, + paddle::DataType sendproc_tensor_dtype, + paddle::DataType recvproc_tensor_dtype, + paddle::DataType sendnum_tensor_dtype, + paddle::DataType recvnum_tensor_dtype, + paddle::DataType g1_tensor_dtype, + paddle::DataType communicator_tensor_dtype, + paddle::DataType nlocal_tensor_dtype, + paddle::DataType nghost_tenso_dtype) { + return {g1_tensor_dtype}; +} + +std::vector> Border_backwardInferShape( + std::vector sendlist_shape, + std::vector sendproc_shape, + std::vector recvproc_shape, + std::vector sendnum_shape, + std::vector recvnum_shape, + std::vector communicator_shape, + std::vector nlocal_shape, + std::vector nghost_shape, + std::vector recv_g1_grad_shape) { + return {recv_g1_grad_shape}; +} + +std::vector Border_backwardInferDtype( + paddle::DataType sendlist_dtype, + paddle::DataType sendproc_dtype, + paddle::DataType recvproc_dtype, + paddle::DataType sendnum_dtype, + paddle::DataType recvnum_dtype, + paddle::DataType communicator_dtype, + paddle::DataType nlocal_dtype, + paddle::DataType nghost_dtype, + paddle::DataType recv_g1_tens_dtype) { + return {recv_g1_tens_dtype}; +} + +/** + * @brief communicate the latest g1 info to other lmp proc + * @param[out] recv_g1_tensor g1 after communication + * @param[in] sendlist_tensor list of atoms to send in each swap + * @param[in] sendproc_tensor proc to send to at each swap + * @param[in] recvproc_tensor proc to recv from at each swap + * @param[in] sendnum_tensor # of atoms to send in each swap + * @param[in] recvnum_tensor # of atoms to recv in each swap + * @param[in] g1_tensor tensor to store g1 info + * @param[in] communicator_tensor MPI_comm data in lmp + * @param[in] nlocal_tensor # of local atoms + * @param[in] nghost_tensor # of nghost atoms + **/ +PD_BUILD_OP(border_op) + .Inputs({"sendlist_tensor", "sendproc_tensor", "recvproc_tensor", + "sendnum_tensor", "recvnum_tensor", "g1_tensor", + "communicator_tensor", "nlocal_tensor", "nghost_tensor"}) + .Outputs({"recv_g1_tensor"}) + .SetKernelFn(PD_KERNEL(Border_forward)) + .SetInplaceMap({{"g1_tensor", "recv_g1_tensor"}}) + .SetInferShapeFn(PD_INFER_SHAPE(Border_forwardInferShape)) + .SetInferDtypeFn(PD_INFER_DTYPE(Border_forwardInferDtype)); + +PD_BUILD_GRAD_OP(border_op) + .Inputs({"sendlist_tensor", "sendproc_tensor", "recvproc_tensor", + "sendnum_tensor", "recvnum_tensor", "g1_tensor", + "communicator_tensor", "nlocal_tensor", "nghost_tensor", + paddle::Grad("recv_g1_tensor")}) + .Outputs({paddle::Grad("g1_tensor")}) + .SetInplaceMap({{paddle::Grad("recv_g1_tensor"), + paddle::Grad("g1_tensor")}}) + .SetKernelFn(PD_KERNEL(Border_backward)) + .SetInferShapeFn(PD_INFER_SHAPE(Border_backwardInferShape)) + .SetInferDtypeFn(PD_INFER_DTYPE(Border_backwardInferDtype)); From c51081525aa9f8e285bb37033e4cc03f692079a0 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 21:34:42 +0800 Subject: [PATCH 03/32] fix code for view ops --- deepmd/pd/model/descriptor/repflows.py | 7 +++++-- deepmd/pd/model/descriptor/repformers.py | 6 +----- 2 files changed, 6 insertions(+), 7 deletions(-) diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index ebab00421e..351ad98e2d 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -604,7 +604,10 @@ def forward( _shapes = node_ebd.shape[1:] _shapes[1] = n_padding node_ebd = paddle.concat( - [node_ebd, paddle.zeros(_shapes, dtype=node_ebd.dtype)], + [ + node_ebd.squeeze(0), + paddle.zeros(_shapes, dtype=node_ebd.dtype), + ], axis=1, ) real_nloc = nloc @@ -652,7 +655,7 @@ def forward( place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) - node_ebd_ext = ret[0].unsqueeze(0) + node_ebd_ext = paddle.assign(ret).unsqueeze(0) if has_spin: node_ebd_real_ext, node_ebd_virtual_ext = paddle.split( node_ebd_ext, [n_dim, n_dim], axis=2 diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index 149717831b..226a837855 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -536,11 +536,7 @@ def forward( place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) - # print(f"ret.shape = {ret.shape}") - # print(f"ret[0].shape = ", ret[0].shape) - g1_ext = ret.unsqueeze(0) - # print(f"g1_ext.shape = ", g1_ext.shape) - # exit() + g1_ext = paddle.assign(ret).unsqueeze(0) if has_spin: g1_real_ext, g1_virtual_ext = paddle.split( g1_ext, [ng1, ng1], dim=2 From 3effbdb0478a179a516f4f73c46715d264338654 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 21:42:51 +0800 Subject: [PATCH 04/32] refine code --- deepmd/pd/train/training.py | 34 +------------- deepmd/pd/train/wrapper.py | 1 - deepmd/pt/model/model/transform_output.py | 3 -- deepmd/pt/train/training.py | 55 ----------------------- deepmd/pt/train/wrapper.py | 1 - source/api_cc/include/DeepPotPD.h | 18 ++++---- source/api_cc/src/DeepPotPD.cc | 6 --- 7 files changed, 10 insertions(+), 108 deletions(-) diff --git a/deepmd/pd/train/training.py b/deepmd/pd/train/training.py index 95d8292442..44d0d16439 100644 --- a/deepmd/pd/train/training.py +++ b/deepmd/pd/train/training.py @@ -760,38 +760,6 @@ def step(_step_id, task_key="Default") -> None: pref_lr = _lr.start_lr else: pref_lr = cur_lr - self.wrapper.load_state_dict(paddle.load("./wrapper_dict.pd")) - print("model loaded") - inp = np.load("./input_dict.npz", allow_pickle=True) - for k, v in inp.items(): - if isinstance(v, np.ndarray): - # print(k, type(v), v.shape, v.dtype) - try: - input_dict[k] = paddle.to_tensor(v) - # print(k) - except Exception: - pass - if isinstance(input_dict[k], paddle.Tensor): - input_dict[k] = input_dict[k].cuda() - print("input_dict loaded") - lab = np.load("./label_dict.npz", allow_pickle=True) - for k, v in lab.items(): - if isinstance(v, np.ndarray): - # print(k, type(v), v.shape, v.dtype) - try: - label_dict[k] = paddle.to_tensor(v) - # print(k) - except Exception: - pass - if isinstance(label_dict[k], paddle.Tensor): - label_dict[k] = label_dict[k].cuda() - print("label_dict loaded") - model_pred, loss, more_loss = self.wrapper( - **input_dict, cur_lr=pref_lr, label=label_dict, task_key=task_key - ) - print({k: float(v) for k, v in more_loss.items()}) - print(f"{loss.item():.10f}") - exit() # disable synchronization in forward-backward manually # as derivatives exist in model forward @@ -811,7 +779,7 @@ def step(_step_id, task_key="Default") -> None: with nvprof_context(enable_profiling, "Backward pass"): loss.backward() - exit() + # fuse + allreduce manually before optimization if use DDP + no_sync # details in https://github.com/PaddlePaddle/Paddle/issues/48898#issuecomment-1343838622 if self.world_size > 1: diff --git a/deepmd/pd/train/wrapper.py b/deepmd/pd/train/wrapper.py index 2f670758d3..bd28b17c88 100644 --- a/deepmd/pd/train/wrapper.py +++ b/deepmd/pd/train/wrapper.py @@ -173,7 +173,6 @@ def forward( model_pred = self.model[task_key](**input_dict) return model_pred, None, None else: - print(self.loss) natoms = atype.shape[-1] model_pred, loss, more_loss = self.loss[task_key]( input_dict, diff --git a/deepmd/pt/model/model/transform_output.py b/deepmd/pt/model/model/transform_output.py index 7d80c1cde1..b8f1e024e0 100644 --- a/deepmd/pt/model/model/transform_output.py +++ b/deepmd/pt/model/model/transform_output.py @@ -96,9 +96,6 @@ def task_deriv_one( extended_virial = extended_virial.view(list(extended_virial.shape[:-2]) + [9]) # noqa:RUF005 else: extended_virial = None - print( - f"extended_force: {extended_force.min().item():.10f} {extended_force.max().item():.10f} {extended_force.mean().item():.10f} {extended_force.std().item():.10f}" - ) return extended_force, extended_virial diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py index d63ac07fbe..193dcd8cb9 100644 --- a/deepmd/pt/train/training.py +++ b/deepmd/pt/train/training.py @@ -725,64 +725,9 @@ def step(_step_id, task_key="Default") -> None: pref_lr = _lr.start_lr else: pref_lr = cur_lr - - # save - # torch.save(self.wrapper.state_dict(), "wrapper_dict.pt") - # import paddle - # psd = {} - # for k, v in self.wrapper.state_dict().items(): - # if isinstance(v, torch.Tensor): - # psd[k] = paddle.from_dlpack(v.detach()) - # else: - # psd[k] = v - # paddle.save(psd, "wrapper_dict.pd") - # inp = {} - # for k, v in input_dict.items(): - # if isinstance(v, torch.Tensor): - # inp[k] = v.detach().cpu().numpy() - # else: - # inp[k] = v - # np.savez("./input_dict.npz", **inp) - # lab = {} - # for k, v in label_dict.items(): - # if isinstance(v, torch.Tensor): - # lab[k] = v.detach().cpu().numpy() - # else: - # lab[k] = v - # np.savez("./label_dict.npz", **lab) - - # load - self.wrapper.load_state_dict(torch.load("./wrapper_dict.pt")) - print("model loaded") - inp = np.load("./input_dict.npz", allow_pickle=True) - for k, v in inp.items(): - if isinstance(v, np.ndarray): - # print(k, type(v), v.shape, v.dtype) - try: - input_dict[k] = torch.tensor(v) - except TypeError: - pass - if isinstance(input_dict[k], torch.Tensor): - input_dict[k] = input_dict[k].cuda() - print("input_dict loaded") - lab = np.load("./label_dict.npz", allow_pickle=True) - for k, v in lab.items(): - if isinstance(v, np.ndarray): - # print(k, type(v), v.shape, v.dtype) - try: - label_dict[k] = torch.tensor(v) - except TypeError: - pass - if isinstance(label_dict[k], torch.Tensor): - label_dict[k] = label_dict[k].cuda() - print("label_dict loaded") - model_pred, loss, more_loss = self.wrapper( **input_dict, cur_lr=pref_lr, label=label_dict, task_key=task_key ) - print({k: float(v) for k, v in more_loss.items()}) - print(f"{loss.item():.10f}") - exit() loss.backward() if self.gradient_max_norm > 0.0: torch.nn.utils.clip_grad_norm_( diff --git a/deepmd/pt/train/wrapper.py b/deepmd/pt/train/wrapper.py index 9d8216795c..9a2cbff295 100644 --- a/deepmd/pt/train/wrapper.py +++ b/deepmd/pt/train/wrapper.py @@ -175,7 +175,6 @@ def forward( return model_pred, None, None else: natoms = atype.shape[-1] - print(self.loss) model_pred, loss, more_loss = self.loss[task_key]( input_dict, self.model[task_key], diff --git a/source/api_cc/include/DeepPotPD.h b/source/api_cc/include/DeepPotPD.h index 488e4fe6b5..8eaa9a09c0 100644 --- a/source/api_cc/include/DeepPotPD.h +++ b/source/api_cc/include/DeepPotPD.h @@ -392,18 +392,18 @@ class DeepPotPD : public DeepPotBackend { int do_message_passing; // 1:dpa2 model 0:others bool gpu_enabled; std::unique_ptr firstneigh_tensor; - std::vector comm_vec; - paddle_infer::Tensor mapping_tensor = predictor_fl->GetInputHandle("mapping"); + /* comm_vec flatten all the communicatoin tensors below from comm dict: - - send_list - - send_proc - - recv_proc - - send_num - - recv_num - - communicator + - [0] send_list + - [1] send_proc + - [2] recv_proc + - [3] send_num + - [4] recv_num + - [5] communicator */ + std::vector comm_vec; - // std::unordered_map comm_dict; # Not used yet + paddle_infer::Tensor mapping_tensor = predictor_fl->GetInputHandle("mapping"); }; } // namespace deepmd diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index d38ef05276..42f3b89380 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -205,8 +205,6 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, nlist_data.shuffle_exclude_empty(fwd_map); nlist_data.padding(); if (do_message_passing == 1 && nghost > 0) { - // throw deepmd::deepmd_exception( - // "(do_message_passing == 1 && nghost > 0) is not supported yet."); int nswap = lmp_list.nswap; auto sendproc_tensor = predictor_fl->GetInputHandle("sendproc"); sendproc_tensor->Reshape({nswap}); @@ -249,10 +247,6 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, this->mapping_tensor->Reshape({1, nall_real}); this->mapping_tensor->CopyFromCpu(mapping.data()); } - // if (do_message_passing == 1 && nghost == 0) { - // throw deepmd::deepmd_exception( - // "(do_message_passing == 1 && nghost == 0) is not supported yet."); - // } } std::vector firstneigh = createNlistTensorPD(nlist_data.jlist); firstneigh_tensor = predictor_fl->GetInputHandle("nlist"); From 38fb9265d341ca4a893be3f90048034aa51a4bbd Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 21:47:03 +0800 Subject: [PATCH 05/32] refine more code --- deepmd/pd/model/descriptor/dpa2.py | 4 ++- deepmd/pd/model/descriptor/repflows.py | 35 ++++++++----------- deepmd/pd/model/descriptor/repformer_layer.py | 1 - deepmd/pd/model/descriptor/repformers.py | 28 +++++++-------- 4 files changed, 30 insertions(+), 38 deletions(-) diff --git a/deepmd/pd/model/descriptor/dpa2.py b/deepmd/pd/model/descriptor/dpa2.py index 02bfedb33a..de0874eecb 100644 --- a/deepmd/pd/model/descriptor/dpa2.py +++ b/deepmd/pd/model/descriptor/dpa2.py @@ -25,6 +25,7 @@ TypeEmbedNetConsistent, ) from deepmd.pd.utils import ( + decomp, env, ) from deepmd.pd.utils.env import ( @@ -799,7 +800,8 @@ def forward( g1 = g1 + self.tebd_transform(g1_inp) # mapping g1 if comm_dict is None or len(comm_dict) == 0: - assert mapping.numel() > 0 + if paddle.in_dynamic_mode(): + assert decomp.numel(mapping) > 0 mapping_ext = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index 351ad98e2d..9e3f17b632 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -5,7 +5,6 @@ Union, ) -import numpy as np import paddle from deepmd.dpmodel.utils.seed import ( @@ -525,7 +524,7 @@ def forward( # nf x nloc x a_nnei x a_nnei # 1 - 1e-6 for paddle.acos stability cosine_ij = paddle.matmul(normalized_diff_i, normalized_diff_j) * (1 - 1e-6) - angle_input = cosine_ij.unsqueeze(-1) / (np.pi**0.5) + angle_input = cosine_ij.unsqueeze(-1) / (paddle.pi**0.5) if not parallel_mode and self.use_loc_mapping: if paddle.in_dynamic_mode(): @@ -597,19 +596,21 @@ def forward( has_spin = len(comm_dict) >= 7 if not has_spin: n_padding = nall - nloc - # node_ebd = paddle.nn.functional.pad( - # node_ebd.squeeze(0), [0, 0, 0, n_padding], value=0.0 - # ) + if paddle.in_dynamic_mode(): + node_ebd = paddle.nn.functional.pad( + node_ebd.squeeze(0), [0, 0, 0, n_padding], value=0.0 + ) + else: + _fill_shape = node_ebd.shape[1:] + _fill_shape[1] = n_padding + node_ebd = paddle.concat( + [ + node_ebd.squeeze(0), + paddle.zeros(_fill_shape, dtype=node_ebd.dtype), + ], + axis=1, + ) # [nframes, nloc, tebd_dim] - _shapes = node_ebd.shape[1:] - _shapes[1] = n_padding - node_ebd = paddle.concat( - [ - node_ebd.squeeze(0), - paddle.zeros(_shapes, dtype=node_ebd.dtype), - ], - axis=1, - ) real_nloc = nloc real_nall = nall else: @@ -630,12 +631,6 @@ def forward( ) assert len(comm_dict) >= 6 - # assert "send_list" in comm_dict - # assert "send_proc" in comm_dict - # assert "recv_proc" in comm_dict - # assert "send_num" in comm_dict - # assert "recv_num" in comm_dict - # assert "communicator" in comm_dict ret = paddle_ops_deepmd_border_op( comm_dict[0], comm_dict[1], diff --git a/deepmd/pd/model/descriptor/repformer_layer.py b/deepmd/pd/model/descriptor/repformer_layer.py index 697476e611..4dad08fff8 100644 --- a/deepmd/pd/model/descriptor/repformer_layer.py +++ b/deepmd/pd/model/descriptor/repformer_layer.py @@ -110,7 +110,6 @@ def _make_nei_g1( # index: nb x (nloc x nnei) x ng1 index = nlist.reshape([nb, nloc * nnei]).unsqueeze(-1).expand([-1, -1, ng1]) # gg1 : nb x (nloc x nnei) x ng1 - # print(g1_ext.shape, index.shape) gg1 = paddle.take_along_axis(g1_ext, indices=index, axis=1, broadcast=False) # gg1 : nb x nloc x nnei x ng1 gg1 = gg1.reshape([nb, nloc, nnei, ng1]) diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index 226a837855..f1656af6ad 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -484,15 +484,17 @@ def forward( has_spin = len(comm_dict) >= 7 if not has_spin: n_padding = nall - nloc - # g1 = paddle.nn.functional.pad( - # g1.squeeze(0), (0, 0, 0, n_padding), value=0.0 - # ) - _shapes = g1.shape[1:] - _shapes[1] = n_padding - g1 = paddle.concat( - [g1.squeeze(0), paddle.zeros(_shapes, dtype=g1.dtype)], - axis=1, - ) + if paddle.in_dynamic_mode(): + g1 = paddle.nn.functional.pad( + g1.squeeze(0), (0, 0, 0, n_padding), value=0.0 + ) + else: + _fill_shape = g1.shape[1:] + _fill_shape[1] = n_padding + g1 = paddle.concat( + [g1.squeeze(0), paddle.zeros(_fill_shape, dtype=g1.dtype)], + axis=1, + ) real_nloc = nloc real_nall = nall else: @@ -510,13 +512,7 @@ def forward( mix_g1.squeeze(0), (0, 0, 0, real_n_padding), value=0.0 ) - # assert "send_list" in comm_dict - # assert "send_proc" in comm_dict - # assert "recv_proc" in comm_dict - # assert "send_num" in comm_dict - # assert "recv_num" in comm_dict - # assert "communicator" in comm_dict - # print(f"g1.shape = ", g1.shape) + assert len(comm_dict) >= 6 ret = paddle_ops_deepmd_border_op( comm_dict[0], comm_dict[1], From 4d3f99c400109e2bd7b416ec446dbc418729f31a Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 21:59:43 +0800 Subject: [PATCH 06/32] fix typing --- deepmd/pd/model/atomic_model/base_atomic_model.py | 4 ++-- deepmd/pd/model/atomic_model/dp_atomic_model.py | 2 +- deepmd/pd/model/descriptor/dpa1.py | 2 +- deepmd/pd/model/descriptor/dpa2.py | 2 +- deepmd/pd/model/descriptor/dpa3.py | 2 +- deepmd/pd/model/descriptor/repformers.py | 2 +- deepmd/pd/model/descriptor/se_a.py | 2 +- deepmd/pd/model/descriptor/se_t_tebd.py | 2 +- deepmd/pd/model/model/ener_model.py | 2 +- deepmd/pd/model/model/make_model.py | 2 +- 10 files changed, 11 insertions(+), 11 deletions(-) diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py index 1100813fb4..bc25b5e105 100644 --- a/deepmd/pd/model/atomic_model/base_atomic_model.py +++ b/deepmd/pd/model/atomic_model/base_atomic_model.py @@ -191,7 +191,7 @@ def forward_common_atomic( mapping: Optional[paddle.Tensor] = None, fparam: Optional[paddle.Tensor] = None, aparam: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ) -> dict[str, paddle.Tensor]: """Common interface for atomic inference. @@ -274,7 +274,7 @@ def forward( mapping: Optional[paddle.Tensor] = None, fparam: Optional[paddle.Tensor] = None, aparam: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ) -> dict[str, paddle.Tensor]: return self.forward_common_atomic( extended_coord, diff --git a/deepmd/pd/model/atomic_model/dp_atomic_model.py b/deepmd/pd/model/atomic_model/dp_atomic_model.py index 1089b93a68..6d0946afb6 100644 --- a/deepmd/pd/model/atomic_model/dp_atomic_model.py +++ b/deepmd/pd/model/atomic_model/dp_atomic_model.py @@ -250,7 +250,7 @@ def forward_atomic( mapping: Optional[paddle.Tensor] = None, fparam: Optional[paddle.Tensor] = None, aparam: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ) -> dict[str, paddle.Tensor]: """Return atomic prediction. diff --git a/deepmd/pd/model/descriptor/dpa1.py b/deepmd/pd/model/descriptor/dpa1.py index ad45c13d1d..7fd3de02e9 100644 --- a/deepmd/pd/model/descriptor/dpa1.py +++ b/deepmd/pd/model/descriptor/dpa1.py @@ -596,7 +596,7 @@ def forward( extended_atype: paddle.Tensor, nlist: paddle.Tensor, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): """Compute the descriptor. diff --git a/deepmd/pd/model/descriptor/dpa2.py b/deepmd/pd/model/descriptor/dpa2.py index de0874eecb..15a64fbf17 100644 --- a/deepmd/pd/model/descriptor/dpa2.py +++ b/deepmd/pd/model/descriptor/dpa2.py @@ -713,7 +713,7 @@ def forward( extended_atype: paddle.Tensor, nlist: paddle.Tensor, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): """Compute the descriptor. diff --git a/deepmd/pd/model/descriptor/dpa3.py b/deepmd/pd/model/descriptor/dpa3.py index 654b328f76..7754de01e5 100644 --- a/deepmd/pd/model/descriptor/dpa3.py +++ b/deepmd/pd/model/descriptor/dpa3.py @@ -457,7 +457,7 @@ def forward( extended_atype: paddle.Tensor, nlist: paddle.Tensor, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): """Compute the descriptor. diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index f1656af6ad..6f78cc427b 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -408,7 +408,7 @@ def forward( extended_atype_embd: Optional[paddle.Tensor] = None, mapping: Optional[paddle.Tensor] = None, type_embedding: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): diff --git a/deepmd/pd/model/descriptor/se_a.py b/deepmd/pd/model/descriptor/se_a.py index 9cd9f7b0b7..92c010fcf0 100644 --- a/deepmd/pd/model/descriptor/se_a.py +++ b/deepmd/pd/model/descriptor/se_a.py @@ -260,7 +260,7 @@ def forward( atype_ext: paddle.Tensor, nlist: paddle.Tensor, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): """Compute the descriptor. diff --git a/deepmd/pd/model/descriptor/se_t_tebd.py b/deepmd/pd/model/descriptor/se_t_tebd.py index 3ebf62d7a5..2505706a1c 100644 --- a/deepmd/pd/model/descriptor/se_t_tebd.py +++ b/deepmd/pd/model/descriptor/se_t_tebd.py @@ -415,7 +415,7 @@ def forward( extended_atype: paddle.Tensor, nlist: paddle.Tensor, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): """Compute the descriptor. diff --git a/deepmd/pd/model/model/ener_model.py b/deepmd/pd/model/model/ener_model.py index a5b1b9d4b3..cfe31598bc 100644 --- a/deepmd/pd/model/model/ener_model.py +++ b/deepmd/pd/model/model/ener_model.py @@ -99,7 +99,7 @@ def forward_lower( fparam: Optional[paddle.Tensor] = None, aparam: Optional[paddle.Tensor] = None, do_atomic_virial: bool = False, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): model_ret = self.forward_common_lower( extended_coord, diff --git a/deepmd/pd/model/model/make_model.py b/deepmd/pd/model/model/make_model.py index acb237b5ac..e23b0db46e 100644 --- a/deepmd/pd/model/model/make_model.py +++ b/deepmd/pd/model/model/make_model.py @@ -238,7 +238,7 @@ def forward_common_lower( fparam: Optional[paddle.Tensor] = None, aparam: Optional[paddle.Tensor] = None, do_atomic_virial: bool = False, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, extra_nlist_sort: bool = False, ): """Return model prediction. Lower interface that takes From d6a3b1e4795578d7d6f483ccd9b417502f998b80 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 23:02:29 +0800 Subject: [PATCH 07/32] update code --- source/CMakeLists.txt | 2 +- source/api_cc/include/DeepPotPD.h | 3 +- source/api_cc/src/DeepPotPD.cc | 16 +++---- source/op/pd/CMakeLists.txt | 75 +++++++++++++++---------------- source/op/pd/comm.cc | 10 ++--- 5 files changed, 53 insertions(+), 53 deletions(-) diff --git a/source/CMakeLists.txt b/source/CMakeLists.txt index f106b6109a..7e0f180e26 100644 --- a/source/CMakeLists.txt +++ b/source/CMakeLists.txt @@ -520,6 +520,7 @@ if(DEEPMD_C_ROOT) endif() if(NOT DEEPMD_C_ROOT) + add_subdirectory(lib/) if(ENABLE_TENSORFLOW) add_subdirectory(op/tf/) endif() @@ -529,7 +530,6 @@ if(NOT DEEPMD_C_ROOT) if(ENABLE_PADDLE) add_subdirectory(op/pd/) endif() - add_subdirectory(lib/) endif() if(BUILD_PY_IF) add_subdirectory(config/) diff --git a/source/api_cc/include/DeepPotPD.h b/source/api_cc/include/DeepPotPD.h index 8eaa9a09c0..e86a768aa0 100644 --- a/source/api_cc/include/DeepPotPD.h +++ b/source/api_cc/include/DeepPotPD.h @@ -403,7 +403,8 @@ class DeepPotPD : public DeepPotBackend { */ std::vector comm_vec; - paddle_infer::Tensor mapping_tensor = predictor_fl->GetInputHandle("mapping"); + std::unique_ptr mapping_tensor = + predictor_fl->GetInputHandle("mapping"); }; } // namespace deepmd diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 42f3b89380..0efdae6280 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -230,14 +230,14 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, std::accumulate(lmp_list.sendnum, lmp_list.sendnum + nswap, 0); auto sendlist_tensor = predictor_fl->GetInputHandle("sendlist"); sendlist_tensor->Reshape({total_send}); - sendlist_tensor->CopyFromCpu(lmp_list.sendlist); - - this->comm_vec.emplace_back(sendlist_tensor); - this->comm_vec.emplace_back(sendproc_tensor); - this->comm_vec.emplace_back(recvproc_tensor); - this->comm_vec.emplace_back(sendnum_tensor); - this->comm_vec.emplace_back(recvnum_tensor); - this->comm_vec.emplace_back(communicator_tensor); + sendlist_tensor->CopyFromCpu(static_cast(*lmp_list.sendlist)); + + // this->comm_vec.push_back(sendlist_tensor); + // this->comm_vec.push_back(sendproc_tensor); + // this->comm_vec.push_back(recvproc_tensor); + // this->comm_vec.push_back(sendnum_tensor); + // this->comm_vec.push_back(recvnum_tensor); + // this->comm_vec.push_back(communicator_tensor); } if (lmp_list.mapping) { std::vector mapping(nall_real); diff --git a/source/op/pd/CMakeLists.txt b/source/op/pd/CMakeLists.txt index 8794069213..0dc9d6d6f8 100644 --- a/source/op/pd/CMakeLists.txt +++ b/source/op/pd/CMakeLists.txt @@ -1,48 +1,46 @@ file(GLOB OP_SRC comm.cc) + add_library(deepmd_op_pd MODULE ${OP_SRC}) -# ========== 新增：Paddle 配置（路径由用户外部传入） ========== -if(NOT DEFINED PADDLE_LIB) +if(NOT DEFINED PADDLE_INFERENCE_DIR) message( FATAL_ERROR - "please set PADDLE_LIB with -DPADDLE_LIB=/path/to/paddle_inference") + "please set PADDLE_INFERENCE_DIR with -DPADDLE_INFERENCE_DIR=/path/to/paddle_inference" + ) endif() -set(PADDLE_LIB_THIRD_PARTY_PATH ${PADDLE_LIB}/third_party/install) -include_directories(${PADDLE_LIB}) -include_directories(${PADDLE_LIB}/paddle/include) -include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/include) -include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/glog/include) -include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/include) -include_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/include) - -# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib) -# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib) -# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib) -# link_directories(${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib) -# link_directories(${PADDLE_LIB}/paddle/lib) target_link_libraries(deepmd_op_pd -# PRIVATE ${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib/libglog.a -# ${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib/libgflags.a -# ${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib/libxxhash.a -# ${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib/libprotobuf.a dl pthread) +set(PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH + ${PADDLE_INFERENCE_DIR}/third_party/install) +include_directories(${PADDLE_INFERENCE_DIR}) +include_directories(${PADDLE_INFERENCE_DIR}/paddle/include) +include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/protobuf/include) +include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/glog/include) +include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/gflags/include) +include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/xxhash/include) # Paddle lib -set(PADDLE_INFER_LIB ${PADDLE_LIB}/paddle/lib/libpaddle_inference.so) +set(PADDLE_INFER_LIB ${PADDLE_INFERENCE_DIR}/paddle/lib/libpaddle_inference.so) # Math lib（默认用MKL） -set(MKLML_LIB ${PADDLE_LIB_THIRD_PARTY_PATH}/mklml/lib/libmklml_intel.so - ${PADDLE_LIB_THIRD_PARTY_PATH}/mklml/lib/libiomp5.so) +set(MKLML_LIB + ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libmklml_intel.so + ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libiomp5.so) + +# link: libdeepmd paddle - 添加 CXX ABI 兼容性处理 if(${OP_CXX_ABI_PT} EQUAL +# ${OP_CXX_ABI}) +target_link_libraries(deepmd_op_pd PRIVATE ${LIB_DEEPMD}) +# else() target_link_libraries(deepmd_op_pd PRIVATE ${LIB_DEEPMD}_compat_cxxabi) +# endif() -# ========== 原有逻辑：保持不动 ========== -# target_link_libraries(deepmd_op_pd PRIVATE ${PADDLE_LIBRARIES}) -# if(${OP_CXX_ABI_PT} EQUAL ${OP_CXX_ABI}) target_link_libraries(deepmd_op_pd -# PRIVATE ${LIB_DEEPMD}) else() target_link_libraries(deepmd_op_pd PRIVATE -# ${LIB_DEEPMD}_compat_cxxabi) endif() -# remove_definitions(-D_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI}) +# 添加 CXX ABI 编译定义 remove_definitions(-D_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI}) # target_compile_definitions( deepmd_op_pd PUBLIC # "$<$:_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI_PT}>") -# if(APPLE) set_target_properties(deepmd_op_pd PROPERTIES INSTALL_RPATH -# "@loader_path") else() set_target_properties(deepmd_op_pd PROPERTIES -# INSTALL_RPATH "$ORIGIN") endif() + +# 添加 RPATH 设置 +if(APPLE) + set_target_properties(deepmd_op_pd PROPERTIES INSTALL_RPATH "@loader_path") +else() + set_target_properties(deepmd_op_pd PROPERTIES INSTALL_RPATH "$ORIGIN") +endif() find_package(MPI) if(MPI_FOUND) @@ -59,22 +57,23 @@ if(MPI_FOUND) target_link_libraries(deepmd_op_pd PRIVATE MPI::MPI_CXX) target_compile_definitions(deepmd_op_pd PRIVATE USE_MPI) endif() + if(CMAKE_TESTING_ENABLED) target_link_libraries(deepmd_op_pd PRIVATE coverage_config) endif() -# ========== 新增：链接 Paddle 所需库 ========== +# 链接 Paddle 所需库 target_link_libraries( deepmd_op_pd - PRIVATE ${PADDLE_LIB_THIRD_PARTY_PATH}/glog/lib/libglog.a - ${PADDLE_LIB_THIRD_PARTY_PATH}/gflags/lib/libgflags.a - ${PADDLE_LIB_THIRD_PARTY_PATH}/xxhash/lib/libxxhash.a - ${PADDLE_LIB_THIRD_PARTY_PATH}/protobuf/lib/libprotobuf.a + PRIVATE ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/glog/lib/libglog.a + ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/gflags/lib/libgflags.a + ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/xxhash/lib/libxxhash.a + ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/protobuf/lib/libprotobuf.a ${PADDLE_INFER_LIB} + ${MKLML_LIB} dl pthread) -# ========== 保持原有安装路径逻辑 ========== if(BUILD_PY_IF) install(TARGETS deepmd_op_pd DESTINATION deepmd/lib/) else(BUILD_PY_IF) diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc index 26580f25a3..9cff358957 100644 --- a/source/op/pd/comm.cc +++ b/source/op/pd/comm.cc @@ -95,7 +95,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, } if (cuda_aware == 0) { recv_g1_tensor = paddle::empty_like(g1, g1.dtype(), paddle::CPUPlace()); - recv_g1_tensor = g1.copy_to(recv_g1_tensor.place()); + recv_g1_tensor = g1.copy_to(recv_g1_tensor.place(), true); // recv_g1_tensor.copy_(g1); } } @@ -158,7 +158,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, #ifdef USE_MPI #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (cuda_aware == 0) { - g1.copy_(recv_g1_tensor); + g1 = recv_g1_tensor; } #endif #endif @@ -233,7 +233,7 @@ std::vector Border_backward_t( d_local_g1_tensor = paddle::empty_like( recv_g1_tensor_grad, recv_g1_tensor_grad.dtype(), paddle::CPUPlace()); d_local_g1_tensor = - recv_g1_tensor_grad.copy_to(d_local_g1_tensor.place()); + recv_g1_tensor_grad.copy_to(d_local_g1_tensor.place(), true); } } #endif @@ -331,8 +331,8 @@ std::vector Border_backward_t( #ifdef USE_MPI #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (cuda_aware == 0) { - recv_g1_tensor_grad = - d_local_g1_tensor.copy_to(recv_g1_tensor_grad.place()); + recv_g1_tensor_grad = d_local_g1_tensor; + // d_local_g1_tensor.copy_to(recv_g1_tensor_grad.place(), true); // grad_output[0].copy_(d_local_g1_tensor); } #endif From 55aeab356939d9bca6d14f86377d042798c62a41 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 22 Jul 2025 23:06:08 +0800 Subject: [PATCH 08/32] update build_cc_pd.sh --- source/install/build_cc_pd.sh | 69 +++++++++++++++++++++++++++++++++++ 1 file changed, 69 insertions(+) create mode 100644 source/install/build_cc_pd.sh diff --git a/source/install/build_cc_pd.sh b/source/install/build_cc_pd.sh new file mode 100644 index 0000000000..a94438815d --- /dev/null +++ b/source/install/build_cc_pd.sh @@ -0,0 +1,69 @@ +set -ex + +if [ "$DP_VARIANT" = "cuda" ]; then + CUDA_ARGS="-DUSE_CUDA_TOOLKIT=TRUE" +elif [ "$DP_VARIANT" = "rocm" ]; then + CUDA_ARGS="-DUSE_ROCM_TOOLKIT=TRUE" +fi +#------------------ + +SCRIPT_PATH=$(dirname $(realpath -s $0)) +if [ -z "$INSTALL_PREFIX" ]; then + INSTALL_PREFIX=$(realpath -s ${SCRIPT_PATH}/../../dp) +fi +mkdir -p ${INSTALL_PREFIX} +echo "Installing DeePMD-kit to ${INSTALL_PREFIX}" +NPROC=$(nproc --all) + +#------------------ + +BUILD_TMP_DIR=${SCRIPT_PATH}/../build +mkdir -p ${BUILD_TMP_DIR} +cd ${BUILD_TMP_DIR} +DP_VARIANT=cuda DP_ENABLE_TENSORFLOW=0 DP_ENABLE_PYTORCH=0 cmake -D ENABLE_TENSORFLOW=OFF \ + -D ENABLE_IPI=FALSE \ + -D USE_CUDA_TOOLKIT=TRUE \ + -D ENABLE_PYTORCH=OFF \ + -D ENABLE_PADDLE=ON \ + -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ + -D USE_TF_PYTHON_LIBS=FALSE \ + ${CUDA_ARGS} \ + -D LAMMPS_VERSION=stable_29Aug2024_update1 \ + .. +cmake --build . -j${NPROC} +cmake --install . + +#------------------ +echo "Congratulations! DeePMD-kit has been installed at ${INSTALL_PREFIX}" + +cd ${BUILD_TMP_DIR} +make lammps +export LAMMPS_SOURCE_ROOT=${BUILD_TMP_DIR}/_deps/lammps_download-src/ +cd ${BUILD_TMP_DIR}/_deps/lammps_download-src/src/ +\cp -r ${BUILD_TMP_DIR}/USER-DEEPMD . +make no-kspace +make yes-kspace +make no-extra-fix +make yes-extra-fix +# make no-user-deepmdin +make yes-user-deepmd +make serial -j +# make mpi -j 10 + +cd ${BUILD_TMP_DIR}/../../examples/water/lmp + +echo "START INFERENCE..." + +# export FLAGS_prim_all=true +# export FLAGS_enable_pir_in_executor=1 +# export FLAGS_prim_enable_dynamic=true +# export FLAGS_use_cinn=true + +export PATH=/workspace/hesensen/deepmd_partx/deepmd-kit-tmp/source/build/_deps/lammps_download-src/src:$PATH +CUDA_VISIBLE_DEVICES=0 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log +# USE_CUDA_TOOLKIT=1 mpirun --allow-run-as-root -np 2 lmp_mpi -in paddle_dpa2.lammps 2>&1 | tee paddle_infer_mpi.log From d967dfc9a68fd403ec90440c368bf2795f803cb4 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 23 Jul 2025 10:54:37 +0800 Subject: [PATCH 09/32] update file --- deepmd/pd/cxx_op.py | 45 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 deepmd/pd/cxx_op.py diff --git a/deepmd/pd/cxx_op.py b/deepmd/pd/cxx_op.py new file mode 100644 index 0000000000..02ce62d70f --- /dev/null +++ b/deepmd/pd/cxx_op.py @@ -0,0 +1,45 @@ +# SPDX-License-Identifier: LGPL-3.0-or-later +from pathlib import ( + Path, +) +from types import ( + ModuleType, +) + +from paddle.utils.cpp_extension import ( + load, +) + + +def load_library(module_name: str) -> tuple[bool, ModuleType]: + """Load OP library and return the module if success. + + Parameters + ---------- + module_name : str + Name of the module + + Returns + ------- + bool + Whether the library is loaded successfully + ModuleType + loaded custom operator module + """ + current_file = Path(__file__).resolve() + base_dir = current_file.parents[2] + + module_file = base_dir / "source" / "op" / "pd" / "comm.cc" + paddle_ops_deepmd = load( + name="deepmd_op_pd", + sources=[str(module_file)], + ) + return True, paddle_ops_deepmd + + +ENABLE_CUSTOMIZED_OP, paddle_ops_deepmd = load_library("deepmd_op_pd") + +__all__ = [ + "ENABLE_CUSTOMIZED_OP", + "paddle_ops_deepmd", +] From 94e5b7bf5c45815d8fa4f96fb00accbd8c47650a Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 23 Jul 2025 13:07:49 +0800 Subject: [PATCH 10/32] update code --- source/CMakeLists.txt | 6 ++---- source/install/build_cc_pd.sh | 3 ++- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/source/CMakeLists.txt b/source/CMakeLists.txt index 7e0f180e26..98db4e4ecb 100644 --- a/source/CMakeLists.txt +++ b/source/CMakeLists.txt @@ -544,10 +544,8 @@ if(BUILD_CPP_IF) add_subdirectory(lmp/) endif() if(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 4.8) - # add_subdirectory (md/) - if(ENABLE_IPI OR NOT BUILD_PY_IF) - add_subdirectory(ipi/) - endif() + # add_subdirectory (md/) if(ENABLE_IPI OR NOT BUILD_PY_IF) + # add_subdirectory(ipi/) endif() if(NOT BUILD_PY_IF) add_subdirectory(gmx/) endif() diff --git a/source/install/build_cc_pd.sh b/source/install/build_cc_pd.sh index a94438815d..ea3e9a21a1 100644 --- a/source/install/build_cc_pd.sh +++ b/source/install/build_cc_pd.sh @@ -23,6 +23,7 @@ cd ${BUILD_TMP_DIR} DP_VARIANT=cuda DP_ENABLE_TENSORFLOW=0 DP_ENABLE_PYTORCH=0 cmake -D ENABLE_TENSORFLOW=OFF \ -D ENABLE_IPI=FALSE \ -D USE_CUDA_TOOLKIT=TRUE \ + -D PADDLE_INFERENCE_DIR=/workspace/hesensen/PaddleScience_enn_debug/Paddle/build/paddle_inference_install_dir \ -D ENABLE_PYTORCH=OFF \ -D ENABLE_PADDLE=ON \ -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ @@ -60,7 +61,7 @@ echo "START INFERENCE..." # export FLAGS_use_cinn=true export PATH=/workspace/hesensen/deepmd_partx/deepmd-kit-tmp/source/build/_deps/lammps_download-src/src:$PATH -CUDA_VISIBLE_DEVICES=0 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log +GLOG_v=4 CUDA_VISIBLE_DEVICES=0 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log From a1ebcde92a6ab5bb3d30ef054a96a38630e33ab8 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 23 Jul 2025 13:14:30 +0800 Subject: [PATCH 11/32] fix fetch name --- source/api_cc/src/DeepPotPD.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 0efdae6280..c1680797d7 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -359,12 +359,12 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, std::vector coord_wrapped = coord; int natoms = atype.size(); int nframes = 1; - auto coord_wrapped_Tensor = predictor->GetInputHandle("coord"); + auto coord_wrapped_Tensor = predictor->GetInputHandle("extended_coord"); coord_wrapped_Tensor->Reshape({1, natoms, 3}); coord_wrapped_Tensor->CopyFromCpu(coord_wrapped.data()); std::vector atype_64(atype.begin(), atype.end()); - auto atype_Tensor = predictor->GetInputHandle("atype"); + auto atype_Tensor = predictor->GetInputHandle("extended_atype"); atype_Tensor->Reshape({1, natoms}); atype_Tensor->CopyFromCpu(atype_64.data()); From 443230a9fd5b8f046da8ccc0c734b5dad614783a Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 23 Jul 2025 13:17:36 +0800 Subject: [PATCH 12/32] fix deeppotpd.cc --- source/api_cc/src/DeepPotPD.cc | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 0efdae6280..33ef0ae1f0 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -35,6 +35,7 @@ DeepPotPD::DeepPotPD(const std::string& model, void DeepPotPD::init(const std::string& model, const int& gpu_rank, const std::string& file_content) { + std::cout << "[DeepPotPD::init]" << std::endl; if (inited) { std::cerr << "WARNING: deepmd-kit should not be initialized twice, do " "nothing at the second call of initializer" @@ -54,7 +55,7 @@ void DeepPotPD::init(const std::string& model, // initialize inference config config = std::make_shared(); - config->DisableGlogInfo(); + // config->DisableGlogInfo(); config->EnableNewExecutor(true); config->EnableNewIR(true); config->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, @@ -62,7 +63,7 @@ void DeepPotPD::init(const std::string& model, // initialize inference config_fl config_fl = std::make_shared(); - config_fl->DisableGlogInfo(); + // config_fl->DisableGlogInfo(); config_fl->EnableNewExecutor(true); config_fl->EnableNewIR(true); config_fl->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, @@ -223,7 +224,7 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, sendnum_tensor->CopyFromCpu(lmp_list.sendnum); auto communicator_tensor = predictor_fl->GetInputHandle("communicator"); communicator_tensor->Reshape({1}); - if (lmp_list.world > 0) { + if (lmp_list.world) { communicator_tensor->CopyFromCpu(static_cast(lmp_list.world)); } int total_send = From ef21ec12d019ac1110b5b30b19ece4833bf86086 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 23 Jul 2025 16:08:14 +0800 Subject: [PATCH 13/32] update code --- deepmd/pd/entrypoints/main.py | 10 +-- deepmd/pd/model/model/ener_model.py | 4 ++ deepmd/pd/model/model/transform_output.py | 2 +- source/api_cc/include/DeepPotPD.h | 7 +-- source/api_cc/src/DeepPotPD.cc | 77 +++++++++++++++++++++-- source/install/build_cc_pd.sh | 7 ++- source/op/pd/comm.cc | 5 ++ 7 files changed, 95 insertions(+), 17 deletions(-) diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py index 3fee742dbd..236e594989 100644 --- a/deepmd/pd/entrypoints/main.py +++ b/deepmd/pd/entrypoints/main.py @@ -373,7 +373,8 @@ def freeze( InputSpec([1, 9], dtype="float64", name="box"), # box None, # fparam None, # aparam - True, # do_atomic_virial + # InputSpec([], dtype="bool", name="do_atomic_virial"), # do_atomic_virial + False, # do_atomic_virial ], full_graph=True, ) @@ -398,15 +399,16 @@ def freeze( InputSpec([1, -1], dtype="int64", name="mapping"), # mapping None, # fparam None, # aparam - True, # do_atomic_virial - [ + # InputSpec([], dtype="bool", name="do_atomic_virial"), # do_atomic_virial + False, # do_atomic_virial + ( InputSpec([-1], "int32", name="send_list"), InputSpec([-1], "int32", name="send_proc"), InputSpec([-1], "int32", name="recv_proc"), InputSpec([-1], "int32", name="send_num"), InputSpec([-1], "int32", name="recv_num"), InputSpec([-1], "int64", name="communicator"), - ], # comm_dict + ), # comm_dict ], full_graph=True, ) diff --git a/deepmd/pd/model/model/ener_model.py b/deepmd/pd/model/model/ener_model.py index cfe31598bc..f6922f3f28 100644 --- a/deepmd/pd/model/model/ener_model.py +++ b/deepmd/pd/model/model/ener_model.py @@ -81,6 +81,8 @@ def forward( model_predict["atom_virial"] = model_ret["energy_derv_c"].squeeze( -3 ) + else: + model_predict["atom_virial"] = paddle.zeros([ model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64) else: model_predict["force"] = model_ret["dforce"] if "mask" in model_ret: @@ -124,6 +126,8 @@ def forward_lower( model_predict["extended_virial"] = model_ret[ "energy_derv_c" ].squeeze(-3) + else: + model_predict["extended_virial"] = paddle.zeros([model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64) else: assert model_ret["dforce"] is not None model_predict["dforce"] = model_ret["dforce"] diff --git a/deepmd/pd/model/model/transform_output.py b/deepmd/pd/model/model/transform_output.py index 469bfd3168..04984c953c 100644 --- a/deepmd/pd/model/model/transform_output.py +++ b/deepmd/pd/model/model/transform_output.py @@ -256,7 +256,7 @@ def communicate_extended_output( new_ret[kk_derv_c + "_redu"] = paddle.sum( new_ret[kk_derv_c].to(redu_prec), axis=1 ) - if not do_atomic_virial: + if not do_atomic_virial and paddle.in_dynamic_mode(): # pop atomic virial, because it is not correctly calculated. new_ret.pop(kk_derv_c) return new_ret diff --git a/source/api_cc/include/DeepPotPD.h b/source/api_cc/include/DeepPotPD.h index e86a768aa0..86bc11603d 100644 --- a/source/api_cc/include/DeepPotPD.h +++ b/source/api_cc/include/DeepPotPD.h @@ -392,7 +392,8 @@ class DeepPotPD : public DeepPotBackend { int do_message_passing; // 1:dpa2 model 0:others bool gpu_enabled; std::unique_ptr firstneigh_tensor; - + std::unique_ptr mapping_tensor; + // std::vector comm_vec; /* comm_vec flatten all the communicatoin tensors below from comm dict: - [0] send_list - [1] send_proc @@ -401,10 +402,6 @@ class DeepPotPD : public DeepPotBackend { - [4] recv_num - [5] communicator */ - std::vector comm_vec; - - std::unique_ptr mapping_tensor = - predictor_fl->GetInputHandle("mapping"); }; } // namespace deepmd diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 2bfbc3832e..341edc01b4 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -35,7 +35,7 @@ DeepPotPD::DeepPotPD(const std::string& model, void DeepPotPD::init(const std::string& model, const int& gpu_rank, const std::string& file_content) { - std::cout << "[DeepPotPD::init]" << std::endl; + // std::cout << "[DeepPotPD::init]" << std::endl; if (inited) { std::cerr << "WARNING: deepmd-kit should not be initialized twice, do " "nothing at the second call of initializer" @@ -60,6 +60,39 @@ void DeepPotPD::init(const std::string& model, config->EnableNewIR(true); config->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, true); + config->DeletePass("dead_code_elimination_pass"); + config->DeletePass("inplace_pass"); + config->DeletePass("remove_shadow_feed_pass"); + config->DeletePass("constant_folding_pass"); + config->DeletePass("replace_fetch_with_shadow_output_pass"); + config->DeletePass("params_sync_among_devices_pass"); + config->DeletePass("common_subexpression_elimination_pass"); + config->DeletePass("transfer_layout_pass"); + // config->DeletePass("add_shadow_output_after_dead_parameter_pass"); + config->DeletePass("horizontal_fuse_pass"); + config->DeletePass("remove_redundant_transpose_pass"); + config->DeletePass("transpose_flatten_concat_fuse_pass"); + config->DeletePass("matmul_transpose_fuse_pass"); + config->DeletePass("matmul_scale_fuse_pass"); + config->DeletePass("group_norm_silu_fuse_pass"); + config->DeletePass("add_norm_fuse_pass"); + config->DeletePass("fc_elementwise_layernorm_fuse_pass"); + config->DeletePass("matmul_add_act_fuse_pass"); + config->DeletePass("multihead_matmul_fuse_pass"); + config->DeletePass("fused_flash_attn_pass"); + config->DeletePass("fused_rotary_position_embedding_pass"); + config->DeletePass("embedding_eltwise_layernorm_fuse_pass"); + config->DeletePass("conv2d_add_fuse_pass"); + config->DeletePass("conv2d_add_act_fuse_pass"); + config->DeletePass("conv2d_bn_fuse_pass"); + config->DeletePass("silu_fuse_pass"); + config->DeletePass("identity_op_clean_pass"); + config->DeletePass("map_op_to_another_pass"); + config->DeletePass("delete_weight_dequant_linear_op_pass"); + config->DeletePass("delete_quant_dequant_linear_op_pass"); + // config->EnableCustomPasses({}, true); + + // config->SwitchIrOptim(false); // initialize inference config_fl config_fl = std::make_shared(); @@ -68,6 +101,39 @@ void DeepPotPD::init(const std::string& model, config_fl->EnableNewIR(true); config_fl->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, true); + config_fl->DeletePass("dead_code_elimination_pass"); + config_fl->DeletePass("inplace_pass"); + config_fl->DeletePass("remove_shadow_feed_pass"); + config_fl->DeletePass("constant_folding_pass"); + config_fl->DeletePass("replace_fetch_with_shadow_output_pass"); + config_fl->DeletePass("params_sync_among_devices_pass"); + config_fl->DeletePass("common_subexpression_elimination_pass"); + config_fl->DeletePass("transfer_layout_pass"); + // config_fl->DeletePass("add_shadow_output_after_dead_parameter_pass"); + config_fl->DeletePass("horizontal_fuse_pass"); + config_fl->DeletePass("remove_redundant_transpose_pass"); + config_fl->DeletePass("transpose_flatten_concat_fuse_pass"); + config_fl->DeletePass("matmul_transpose_fuse_pass"); + config_fl->DeletePass("matmul_scale_fuse_pass"); + config_fl->DeletePass("group_norm_silu_fuse_pass"); + config_fl->DeletePass("add_norm_fuse_pass"); + config_fl->DeletePass("fc_elementwise_layernorm_fuse_pass"); + config_fl->DeletePass("matmul_add_act_fuse_pass"); + config_fl->DeletePass("multihead_matmul_fuse_pass"); + config_fl->DeletePass("fused_flash_attn_pass"); + config_fl->DeletePass("fused_rotary_position_embedding_pass"); + config_fl->DeletePass("embedding_eltwise_layernorm_fuse_pass"); + config_fl->DeletePass("conv2d_add_fuse_pass"); + config_fl->DeletePass("conv2d_add_act_fuse_pass"); + config_fl->DeletePass("conv2d_bn_fuse_pass"); + config_fl->DeletePass("silu_fuse_pass"); + config_fl->DeletePass("identity_op_clean_pass"); + config_fl->DeletePass("map_op_to_another_pass"); + config_fl->DeletePass("delete_weight_dequant_linear_op_pass"); + config_fl->DeletePass("delete_quant_dequant_linear_op_pass"); + // config_fl->EnableCustomPasses({}, true); + + // config_fl->SwitchIrOptim(false); // loading inference model std::string pdmodel_path, fl_pdmodel_path; @@ -152,7 +218,9 @@ void DeepPotPD::init(const std::string& model, } predictor = paddle_infer::CreatePredictor(*config); + std::cout << "Setup model.forward model" << std::endl; predictor_fl = paddle_infer::CreatePredictor(*config_fl); + std::cout << "Setup model.forward_lower model" << std::endl; // initialize hyper params from model buffers ntypes_spin = 0; @@ -245,14 +313,15 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, for (size_t ii = 0; ii < nall_real; ii++) { mapping[ii] = lmp_list.mapping[fwd_map[ii]]; } + this->mapping_tensor = predictor_fl->GetInputHandle("mapping"); this->mapping_tensor->Reshape({1, nall_real}); this->mapping_tensor->CopyFromCpu(mapping.data()); } } std::vector firstneigh = createNlistTensorPD(nlist_data.jlist); - firstneigh_tensor = predictor_fl->GetInputHandle("nlist"); - firstneigh_tensor->Reshape({1, nloc, (int)firstneigh.size() / (int)nloc}); - firstneigh_tensor->CopyFromCpu(firstneigh.data()); + this->firstneigh_tensor = predictor_fl->GetInputHandle("nlist"); + this->firstneigh_tensor->Reshape({1, nloc, (int)firstneigh.size() / (int)nloc}); + this->firstneigh_tensor->CopyFromCpu(firstneigh.data()); bool do_atom_virial_tensor = atomic; std::unique_ptr fparam_tensor; if (!fparam.empty()) { diff --git a/source/install/build_cc_pd.sh b/source/install/build_cc_pd.sh index ea3e9a21a1..c25bc096bc 100644 --- a/source/install/build_cc_pd.sh +++ b/source/install/build_cc_pd.sh @@ -23,7 +23,7 @@ cd ${BUILD_TMP_DIR} DP_VARIANT=cuda DP_ENABLE_TENSORFLOW=0 DP_ENABLE_PYTORCH=0 cmake -D ENABLE_TENSORFLOW=OFF \ -D ENABLE_IPI=FALSE \ -D USE_CUDA_TOOLKIT=TRUE \ - -D PADDLE_INFERENCE_DIR=/workspace/hesensen/PaddleScience_enn_debug/Paddle/build/paddle_inference_install_dir \ + -D PADDLE_INFERENCE_DIR=/work/Paddle/build/paddle_inference_install_dir \ -D ENABLE_PYTORCH=OFF \ -D ENABLE_PADDLE=ON \ -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ @@ -60,8 +60,9 @@ echo "START INFERENCE..." # export FLAGS_prim_enable_dynamic=true # export FLAGS_use_cinn=true -export PATH=/workspace/hesensen/deepmd_partx/deepmd-kit-tmp/source/build/_deps/lammps_download-src/src:$PATH -GLOG_v=4 CUDA_VISIBLE_DEVICES=0 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps +export PATH=${LAMMPS_SOURCE_ROOT}/src:$PATH +# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps +FLAGS_benchmark=1 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc index 9cff358957..b961878f92 100644 --- a/source/op/pd/comm.cc +++ b/source/op/pd/comm.cc @@ -95,6 +95,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, } if (cuda_aware == 0) { recv_g1_tensor = paddle::empty_like(g1, g1.dtype(), paddle::CPUPlace()); + std::cout << "[1]" << std::endl; recv_g1_tensor = g1.copy_to(recv_g1_tensor.place(), true); // recv_g1_tensor.copy_(g1); } @@ -110,6 +111,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, paddle::Tensor send_g1_tensor; FPTYPE* send_g1; if (nsend != 0) { + std::cout << "[2]" << std::endl; isendlist = paddle::from_blob( static_cast(sendlist[iswap]), {nsend}, paddle::DataType::INT32, phi::DataLayout::NCHW, recv_g1_tensor.place()); @@ -232,6 +234,7 @@ std::vector Border_backward_t( if (cuda_aware == 0) { d_local_g1_tensor = paddle::empty_like( recv_g1_tensor_grad, recv_g1_tensor_grad.dtype(), paddle::CPUPlace()); + std::cout << "[3]" << std::endl; d_local_g1_tensor = recv_g1_tensor_grad.copy_to(d_local_g1_tensor.place(), true); } @@ -259,6 +262,7 @@ std::vector Border_backward_t( if (nswap != 0) { send_g1_tensor = d_local_g1_tensor; int max_recvnum = *sendnum_tensor.max().data(); + std::cout << "[4]" << std::endl; recv_g1_tensor = paddle::empty({max_recvnum, tensor_size}, d_local_g1_tensor.dtype(), d_local_g1_tensor.place()); @@ -274,6 +278,7 @@ std::vector Border_backward_t( paddle::Tensor irecvlist; if (nrecv) { + std::cout << "[5]" << std::endl; irecvlist = paddle::from_blob( static_cast(recvlist[iswap]), {nrecv}, paddle::DataType::INT32, paddle::DataLayout::NCHW, d_local_g1_tensor.place()); From 8c106c767f49fcc24f0a8cd746a42af8b7f63d6a Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 16:50:17 +0800 Subject: [PATCH 14/32] update code for successfully run dpa2 C++ inference --- deepmd/pd/cxx_op.py | 22 +- deepmd/pd/entrypoints/main.py | 11 +- .../model/atomic_model/base_atomic_model.py | 38 +- .../pd/model/atomic_model/dp_atomic_model.py | 29 +- deepmd/pd/model/descriptor/dpa2.py | 14 +- deepmd/pd/model/descriptor/env_mat.py | 4 +- deepmd/pd/model/descriptor/repflows.py | 25 +- deepmd/pd/model/descriptor/repformer_layer.py | 11 +- deepmd/pd/model/descriptor/repformers.py | 50 ++- deepmd/pd/model/descriptor/se_atten.py | 15 +- deepmd/pd/model/descriptor/se_t_tebd.py | 6 +- deepmd/pd/model/model/make_model.py | 14 +- deepmd/pd/model/model/transform_output.py | 10 +- deepmd/pd/model/network/network.py | 8 +- deepmd/pd/model/task/fitting.py | 134 ++++++- deepmd/pd/utils/exclude_mask.py | 20 +- deepmd/pd/utils/nlist.py | 76 ++-- deepmd/pd/utils/stat.py | 70 ++-- source/api_cc/CMakeLists.txt | 1 - source/api_cc/src/DeepPotPD.cc | 136 ++----- source/api_cc/src/common.cc | 7 +- source/op/pd/CMakeLists.txt | 15 +- source/op/pd/comm.cc | 375 +++++++++++------- 23 files changed, 644 insertions(+), 447 deletions(-) diff --git a/deepmd/pd/cxx_op.py b/deepmd/pd/cxx_op.py index 02ce62d70f..9962bc0d24 100644 --- a/deepmd/pd/cxx_op.py +++ b/deepmd/pd/cxx_op.py @@ -1,15 +1,9 @@ # SPDX-License-Identifier: LGPL-3.0-or-later -from pathlib import ( - Path, -) +import importlib from types import ( ModuleType, ) -from paddle.utils.cpp_extension import ( - load, -) - def load_library(module_name: str) -> tuple[bool, ModuleType]: """Load OP library and return the module if success. @@ -26,15 +20,11 @@ def load_library(module_name: str) -> tuple[bool, ModuleType]: ModuleType loaded custom operator module """ - current_file = Path(__file__).resolve() - base_dir = current_file.parents[2] - - module_file = base_dir / "source" / "op" / "pd" / "comm.cc" - paddle_ops_deepmd = load( - name="deepmd_op_pd", - sources=[str(module_file)], - ) - return True, paddle_ops_deepmd + if importlib.util.find_spec(module_name) is not None: + module = importlib.import_module(module_name) + return True, module + + return False, None ENABLE_CUSTOMIZED_OP, paddle_ops_deepmd = load_library("deepmd_op_pd") diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py index 236e594989..2a83cd9f14 100644 --- a/deepmd/pd/entrypoints/main.py +++ b/deepmd/pd/entrypoints/main.py @@ -390,24 +390,25 @@ def freeze( model.forward_lower, input_spec=[ InputSpec( - [1, -1, 3], dtype="float64", name="extended_coord" + [-1, -1, 3], dtype="float64", name="extended_coord" ), # extended_coord InputSpec( - [1, -1], dtype="int32", name="extended_atype" + [-1, -1], dtype="int32", name="extended_atype" ), # extended_atype - InputSpec([1, -1, -1], dtype="int32", name="nlist"), # nlist - InputSpec([1, -1], dtype="int64", name="mapping"), # mapping + InputSpec([-1, -1, -1], dtype="int32", name="nlist"), # nlist + InputSpec([-1, -1], dtype="int64", name="mapping"), # mapping None, # fparam None, # aparam # InputSpec([], dtype="bool", name="do_atomic_virial"), # do_atomic_virial False, # do_atomic_virial ( - InputSpec([-1], "int32", name="send_list"), + InputSpec([-1], "int64", name="send_list"), InputSpec([-1], "int32", name="send_proc"), InputSpec([-1], "int32", name="recv_proc"), InputSpec([-1], "int32", name="send_num"), InputSpec([-1], "int32", name="recv_num"), InputSpec([-1], "int64", name="communicator"), + # InputSpec([1], "int64", name="has_spin"), ), # comm_dict ], full_graph=True, diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py index bc25b5e105..b87d65194b 100644 --- a/deepmd/pd/model/atomic_model/base_atomic_model.py +++ b/deepmd/pd/model/atomic_model/base_atomic_model.py @@ -1,9 +1,9 @@ # SPDX-License-Identifier: LGPL-3.0-or-later -import copy import logging from typing import ( Callable, + NoReturn, Optional, Union, ) @@ -79,7 +79,8 @@ def __init__( pair_exclude_types: list[tuple[int, int]] = [], rcond: Optional[float] = None, preset_out_bias: Optional[dict[str, np.ndarray]] = None, - ): + data_stat_protect: float = 1e-2, + ) -> None: paddle.nn.Layer.__init__(self) BaseAtomicModel_.__init__(self) self.type_map = type_map @@ -87,8 +88,9 @@ def __init__( self.reinit_pair_exclude(pair_exclude_types) self.rcond = rcond self.preset_out_bias = preset_out_bias + self.data_stat_protect = data_stat_protect - def init_out_stat(self): + def init_out_stat(self) -> None: """Initialize the output bias.""" ntypes = self.get_ntypes() self.bias_keys: list[str] = list(self.fitting_output_def().keys()) @@ -104,7 +106,7 @@ def init_out_stat(self): def set_out_bias(self, out_bias: paddle.Tensor) -> None: self.out_bias = out_bias - def __setitem__(self, key, value): + def __setitem__(self, key, value) -> None: if key in ["out_bias"]: self.out_bias = value elif key in ["out_std"]: @@ -124,10 +126,18 @@ def get_type_map(self) -> list[str]: """Get the type map.""" return self.type_map + def get_compute_stats_distinguish_types(self) -> bool: + """Get whether the fitting net computes stats which are not distinguished between different types of atoms.""" + return True + + def get_intensive(self) -> bool: + """Whether the fitting property is intensive.""" + return False + def reinit_atom_exclude( self, exclude_types: list[int] = [], - ): + ) -> None: self.atom_exclude_types = exclude_types if exclude_types == []: self.atom_excl = None @@ -137,7 +147,7 @@ def reinit_atom_exclude( def reinit_pair_exclude( self, exclude_types: list[tuple[int, int]] = [], - ): + ) -> None: self.pair_exclude_types = exclude_types if exclude_types == []: self.pair_excl = None @@ -232,7 +242,7 @@ def forward_common_atomic( if self.pair_excl is not None: pair_mask = self.pair_excl(nlist, extended_atype) # exclude neighbors in the nlist - nlist = paddle.where(pair_mask == 1, nlist, -1) + nlist = paddle.where(pair_mask == 1, nlist, paddle.full_like(nlist, -1)) ext_atom_mask = self.make_atom_mask(extended_atype) ret_dict = self.forward_atomic( @@ -260,7 +270,7 @@ def forward_common_atomic( out_shape2 *= ss ret_dict[kk] = ( ret_dict[kk].reshape([out_shape[0], out_shape[1], out_shape2]) - * atom_mask.unsqueeze(2).astype(ret_dict[kk].dtype) + * atom_mask[:, :, None].astype(ret_dict[kk].dtype) ).reshape(out_shape) ret_dict["mask"] = atom_mask @@ -332,7 +342,7 @@ def serialize(self) -> dict: @classmethod def deserialize(cls, data: dict) -> "BaseAtomicModel": - data = copy.deepcopy(data) + data = data.copy() variables = data.pop("@variables", None) variables = ( {"out_bias": None, "out_std": None} if variables is None else variables @@ -354,7 +364,7 @@ def compute_or_load_stat( self, merged: Union[Callable[[], list[dict]], list[dict]], stat_file_path: Optional[DPPath] = None, - ): + ) -> NoReturn: """ Compute the output statistics (e.g. energy bias) for the fitting net from packed data. @@ -377,7 +387,7 @@ def compute_or_load_out_stat( self, merged: Union[Callable[[], list[dict]], list[dict]], stat_file_path: Optional[DPPath] = None, - ): + ) -> None: """ Compute the output statistics (e.g. energy bias) for the fitting net from packed data. @@ -457,7 +467,6 @@ def change_out_bias( model_forward=self._get_forward_wrapper_func(), rcond=self.rcond, preset_bias=self.preset_out_bias, - atomic_output=self.atomic_output_def(), ) self._store_out_stat(delta_bias, out_std, add=True) elif bias_adjust_mode == "set-by-statistic": @@ -468,7 +477,8 @@ def change_out_bias( stat_file_path=stat_file_path, rcond=self.rcond, preset_bias=self.preset_out_bias, - atomic_output=self.atomic_output_def(), + stats_distinguish_types=self.get_compute_stats_distinguish_types(), + intensive=self.get_intensive(), ) self._store_out_stat(bias_out, std_out) else: @@ -544,7 +554,7 @@ def _store_out_stat( out_bias: dict[str, paddle.Tensor], out_std: dict[str, paddle.Tensor], add: bool = False, - ): + ) -> None: ntypes = self.get_ntypes() out_bias_data = paddle.clone(self.out_bias) out_std_data = paddle.clone(self.out_std) diff --git a/deepmd/pd/model/atomic_model/dp_atomic_model.py b/deepmd/pd/model/atomic_model/dp_atomic_model.py index 6d0946afb6..00fefa4e2b 100644 --- a/deepmd/pd/model/atomic_model/dp_atomic_model.py +++ b/deepmd/pd/model/atomic_model/dp_atomic_model.py @@ -62,7 +62,9 @@ def __init__( self.fitting_net = fitting super().init_out_stat() self.enable_eval_descriptor_hook = False + self.enable_eval_fitting_last_layer_hook = False self.eval_descriptor_list = [] + self.eval_fitting_last_layer_list = [] # register 'type_map' as buffer def _string_to_array(s: str) -> list[int]: @@ -112,16 +114,29 @@ def _string_to_array(s: str) -> list[int]: self.buffer_aparam_nall.name = "buffer_aparam_nall" eval_descriptor_list: list[paddle.Tensor] + eval_fitting_last_layer_list: list[paddle.Tensor] def set_eval_descriptor_hook(self, enable: bool) -> None: """Set the hook for evaluating descriptor and clear the cache for descriptor list.""" self.enable_eval_descriptor_hook = enable - self.eval_descriptor_list = [] + # = [] does not work; See #4533 + self.eval_descriptor_list.clear() def eval_descriptor(self) -> paddle.Tensor: """Evaluate the descriptor.""" return paddle.concat(self.eval_descriptor_list) + def set_eval_fitting_last_layer_hook(self, enable: bool) -> None: + """Set the hook for evaluating fitting last layer output and clear the cache for fitting last layer output list.""" + self.enable_eval_fitting_last_layer_hook = enable + self.fitting_net.set_return_middle_output(enable) + # = [] does not work; See #4533 + self.eval_fitting_last_layer_list.clear() + + def eval_fitting_last_layer(self) -> paddle.Tensor: + """Evaluate the fitting last layer output.""" + return paddle.concat(self.eval_fitting_last_layer_list) + def fitting_output_def(self) -> FittingOutputDef: """Get the output def of the fitting net.""" return ( @@ -288,7 +303,7 @@ def forward_atomic( ) assert descriptor is not None if self.enable_eval_descriptor_hook: - self.eval_descriptor_list.append(descriptor) + self.eval_descriptor_list.append(descriptor.detach()) # energy, force fit_ret = self.fitting_net( descriptor, @@ -299,6 +314,13 @@ def forward_atomic( fparam=fparam, aparam=aparam, ) + if self.enable_eval_fitting_last_layer_hook: + assert "middle_output" in fit_ret, ( + "eval_fitting_last_layer not supported for this fitting net!" + ) + self.eval_fitting_last_layer_list.append( + fit_ret.pop("middle_output").detach() + ) return fit_ret def get_out_bias(self) -> paddle.Tensor: @@ -343,6 +365,9 @@ def wrapped_sampler(): return sampled self.descriptor.compute_input_stats(wrapped_sampler, stat_file_path) + self.fitting_net.compute_input_stats( + wrapped_sampler, protection=self.data_stat_protect + ) self.compute_or_load_out_stat(wrapped_sampler, stat_file_path) def get_dim_fparam(self) -> int: diff --git a/deepmd/pd/model/descriptor/dpa2.py b/deepmd/pd/model/descriptor/dpa2.py index 15a64fbf17..a82065513f 100644 --- a/deepmd/pd/model/descriptor/dpa2.py +++ b/deepmd/pd/model/descriptor/dpa2.py @@ -748,7 +748,7 @@ def forward( """ # cast the input to internal precsion - extended_coord = extended_coord.to(dtype=self.prec) + extended_coord = extended_coord.astype(dtype=self.prec) use_three_body = self.use_three_body nframes, nloc, nnei = nlist.shape @@ -807,7 +807,7 @@ def forward( .unsqueeze(-1) .expand([-1, -1, g1.shape[-1]]) ) - g1_ext = paddle.take_along_axis(g1, mapping_ext, 1) + g1_ext = paddle.take_along_axis(g1, mapping_ext, 1, broadcast=False) g1 = g1_ext # repformer g1, g2, h2, rot_mat, sw = self.repformers( @@ -825,11 +825,11 @@ def forward( if self.concat_output_tebd: g1 = paddle.concat([g1, g1_inp], axis=-1) return ( - g1.to(dtype=env.GLOBAL_PD_FLOAT_PRECISION), - rot_mat.to(dtype=env.GLOBAL_PD_FLOAT_PRECISION), - g2.to(dtype=env.GLOBAL_PD_FLOAT_PRECISION), - h2.to(dtype=env.GLOBAL_PD_FLOAT_PRECISION), - sw.to(dtype=env.GLOBAL_PD_FLOAT_PRECISION), + g1.astype(dtype=env.GLOBAL_PD_FLOAT_PRECISION), + rot_mat.astype(dtype=env.GLOBAL_PD_FLOAT_PRECISION), + g2.astype(dtype=env.GLOBAL_PD_FLOAT_PRECISION), + h2.astype(dtype=env.GLOBAL_PD_FLOAT_PRECISION), + sw.astype(dtype=env.GLOBAL_PD_FLOAT_PRECISION), ) @classmethod diff --git a/deepmd/pd/model/descriptor/env_mat.py b/deepmd/pd/model/descriptor/env_mat.py index 214fb593de..2cc23fcadf 100644 --- a/deepmd/pd/model/descriptor/env_mat.py +++ b/deepmd/pd/model/descriptor/env_mat.py @@ -23,11 +23,11 @@ def _make_env_mat( nall = coord.shape[1] mask = nlist >= 0 # nlist = nlist * mask ## this impl will contribute nans in Hessian calculation. - nlist = paddle.where(mask, nlist, nall - 1) + nlist = paddle.where(mask, nlist, paddle.full_like(nlist, nall - 1)) coord_l = coord[:, :natoms].reshape([bsz, -1, 1, 3]) index = nlist.reshape([bsz, -1]).unsqueeze(-1).expand([-1, -1, 3]) coord_pad = paddle.concat([coord, coord[:, -1:, :] + rcut], axis=1) - coord_r = paddle.take_along_axis(coord_pad, axis=1, indices=index) + coord_r = paddle.take_along_axis(coord_pad, axis=1, indices=index, broadcast=False) coord_r = coord_r.reshape([bsz, natoms, nnei, 3]) diff = coord_r - coord_l length = paddle.linalg.norm(diff, axis=-1, keepdim=True) diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index 9e3f17b632..f92dc02f58 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -602,13 +602,13 @@ def forward( ) else: _fill_shape = node_ebd.shape[1:] - _fill_shape[1] = n_padding + _fill_shape[0] = n_padding node_ebd = paddle.concat( [ node_ebd.squeeze(0), paddle.zeros(_fill_shape, dtype=node_ebd.dtype), ], - axis=1, + axis=0, ) # [nframes, nloc, tebd_dim] real_nloc = nloc @@ -626,9 +626,22 @@ def forward( [node_ebd_real, node_ebd_virtual], axis=2 ) # nb x real_nall x (n_dim * 2) - node_ebd = paddle.nn.functional.pad( - mix_node_ebd.squeeze(0), (0, 0, 0, real_n_padding), value=0.0 - ) + if paddle.in_dynamic_mode(): + node_ebd = paddle.nn.functional.pad( + mix_node_ebd.squeeze(0), + (0, 0, 0, real_n_padding), + value=0.0, + ) + else: + _fill_shape = mix_node_ebd.shape[1:] + _fill_shape[0] = real_n_padding + node_ebd = paddle.concat( + [ + mix_node_ebd.squeeze(0), + paddle.zeros(_fill_shape, dtype=mix_node_ebd.dtype), + ], + axis=0, + ) assert len(comm_dict) >= 6 ret = paddle_ops_deepmd_border_op( @@ -650,7 +663,7 @@ def forward( place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) - node_ebd_ext = paddle.assign(ret).unsqueeze(0) + node_ebd_ext = ret.unsqueeze(0) if has_spin: node_ebd_real_ext, node_ebd_virtual_ext = paddle.split( node_ebd_ext, [n_dim, n_dim], axis=2 diff --git a/deepmd/pd/model/descriptor/repformer_layer.py b/deepmd/pd/model/descriptor/repformer_layer.py index 4dad08fff8..e4fb99511e 100644 --- a/deepmd/pd/model/descriptor/repformer_layer.py +++ b/deepmd/pd/model/descriptor/repformer_layer.py @@ -954,9 +954,7 @@ def _update_g1_conv( ).unsqueeze(-1) else: gg1 = _apply_switch(gg1, sw) - invnnei = (1.0 / float(nnei)) * paddle.ones( - (nb, nloc, 1), dtype=gg1.dtype - ).to(device=gg1.place) + invnnei = (1.0 / float(nnei)) * paddle.ones((nb, nloc, 1), dtype=gg1.dtype) if not self.g1_out_conv: # nb x nloc x ng2 g1_11 = paddle.sum(g2 * gg1, axis=2) * invnnei @@ -1026,11 +1024,10 @@ def _cal_hg( if not use_sqrt_nnei: invnnei = (1.0 / float(nnei)) * paddle.ones( (nb, nloc, 1, 1), dtype=g2.dtype - ).to(device=g2.place) + ) else: invnnei = paddle.rsqrt( - float(nnei) - * paddle.ones([nb, nloc, 1, 1], dtype=g2.dtype).to(device=g2.place) + float(nnei) * paddle.ones([nb, nloc, 1, 1], dtype=g2.dtype) ) # nb x nloc x 3 x ng2 h2g2 = paddle.matmul(paddle.transpose(h2, [0, 1, 3, 2]), g2) * invnnei @@ -1056,7 +1053,7 @@ def _cal_grrg(h2g2: paddle.Tensor, axis_neuron: int) -> paddle.Tensor: # nb x nloc x 3 x ng2 nb, nloc, _, ng2 = h2g2.shape # nb x nloc x 3 x axis - h2g2m = h2g2[..., :axis_neuron] # use slice instead of split + h2g2m = h2g2[..., :axis_neuron] # nb x nloc x axis x ng2 g1_13 = paddle.matmul(paddle.transpose(h2g2m, [0, 1, 3, 2]), h2g2) / (3.0**1) # nb x nloc x (axisxng2) diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index 6f78cc427b..d501772360 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -204,8 +204,8 @@ def __init__( The epsilon value for layer normalization. seed : int, optional Random seed for parameter initialization. - trainable : bool, default: True - Whether this block is trainable + trainable : bool + Whether the block is trainable """ super().__init__() self.rcut = float(rcut) @@ -412,8 +412,8 @@ def forward( ): if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 - assert extended_atype_embd is not None or extended_atype_embd.numel() > 0 + assert mapping is not None + assert extended_atype_embd is not None nframes, nloc, nnei = nlist.shape nall = extended_coord.reshape([nframes, -1]).shape[1] // 3 atype = extended_atype[:, :nloc] @@ -445,8 +445,8 @@ def forward( assert list(atype_embd.shape) == [nframes, nloc, self.g1_dim] else: atype_embd = extended_atype_embd - if paddle.in_dynamic_mode(): - assert isinstance(atype_embd, paddle.Tensor) # for jit + if paddle.in_dynamic_mode(): + assert isinstance(atype_embd, paddle.Tensor) # for jit g1 = self.act(atype_embd) ng1 = g1.shape[-1] # nb x nloc x nnei x 1, nb x nloc x nnei x 3 @@ -486,14 +486,17 @@ def forward( n_padding = nall - nloc if paddle.in_dynamic_mode(): g1 = paddle.nn.functional.pad( - g1.squeeze(0), (0, 0, 0, n_padding), value=0.0 + g1.squeeze(0), + (0, 0, 0, n_padding), + value=0.0, + pad_from_left_axis=False, ) else: _fill_shape = g1.shape[1:] - _fill_shape[1] = n_padding + _fill_shape[0] = n_padding g1 = paddle.concat( [g1.squeeze(0), paddle.zeros(_fill_shape, dtype=g1.dtype)], - axis=1, + axis=0, ) real_nloc = nloc real_nall = nall @@ -508,9 +511,23 @@ def forward( # mix_g1: nb x real_nloc x (ng1 * 2) mix_g1 = paddle.concat([g1_real, g1_virtual], axis=2) # nb x real_nall x (ng1 * 2) - g1 = paddle.nn.functional.pad( - mix_g1.squeeze(0), (0, 0, 0, real_n_padding), value=0.0 - ) + if paddle.in_dynamic_mode(): + g1 = paddle.nn.functional.pad( + mix_g1.squeeze(0), + (0, 0, 0, real_n_padding), + value=0.0, + pad_from_left_axis=False, + ) + else: + _fill_shape = mix_g1.shape[1:] + _fill_shape[0] = real_n_padding + g1 = paddle.concat( + [ + mix_g1.squeeze(0), + paddle.zeros(_fill_shape, dtype=mix_g1.dtype), + ], + axis=0, + ) assert len(comm_dict) >= 6 ret = paddle_ops_deepmd_border_op( @@ -522,25 +539,24 @@ def forward( g1, comm_dict[5], paddle.to_tensor( - real_nloc, + [real_nloc], dtype=paddle.int32, place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu paddle.to_tensor( - real_nall - real_nloc, + [real_nall - real_nloc], dtype=paddle.int32, place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) - g1_ext = paddle.assign(ret).unsqueeze(0) + g1_ext = ret.unsqueeze(0) if has_spin: g1_real_ext, g1_virtual_ext = paddle.split( - g1_ext, [ng1, ng1], dim=2 + g1_ext, [ng1, ng1], axis=2 ) g1_ext = concat_switch_virtual( g1_real_ext, g1_virtual_ext, real_nloc ) - g1, g2, h2 = ll.forward( g1_ext, g2, diff --git a/deepmd/pd/model/descriptor/se_atten.py b/deepmd/pd/model/descriptor/se_atten.py index 788ab211a7..39c3e6ace4 100644 --- a/deepmd/pd/model/descriptor/se_atten.py +++ b/deepmd/pd/model/descriptor/se_atten.py @@ -525,7 +525,10 @@ def forward( index = nlist.reshape([nb, nloc * nnei]).unsqueeze(-1).expand([-1, -1, nt]) # nb x (nloc x nnei) x nt atype_tebd_nlist = paddle.take_along_axis( - atype_tebd_ext, axis=1, indices=index + atype_tebd_ext, + axis=1, + indices=index, + broadcast=False, ) # j # nb x nloc x nnei x nt atype_tebd_nlist = atype_tebd_nlist.reshape([nb, nloc, nnei, nt]) @@ -563,14 +566,16 @@ def forward( nlist_index = nlist.reshape([nb, nloc * nnei]) # nf x (nl x nnei) nei_type = paddle.take_along_axis( - extended_atype, indices=nlist_index, axis=1 + extended_atype, indices=nlist_index, axis=1, broadcast=False ) # (nf x nl x nnei) x ng nei_type_index = nei_type.reshape([-1, 1]).expand([-1, ng]).to(paddle.int64) if self.type_one_side: tt_full = self.filter_layers_strip.networks[0](type_embedding) # (nf x nl x nnei) x ng - gg_t = paddle.take_along_axis(tt_full, indices=nei_type_index, axis=0) + gg_t = paddle.take_along_axis( + tt_full, indices=nei_type_index, axis=0, broadcast=False + ) else: idx_i = paddle.tile( atype.reshape([-1, 1]) * ntypes_with_padding, [1, nnei] @@ -594,7 +599,9 @@ def forward( ).reshape([-1, nt * 2]) tt_full = self.filter_layers_strip.networks[0](two_side_type_embedding) # (nf x nl x nnei) x ng - gg_t = paddle.take_along_axis(tt_full, axis=0, indices=idx) + gg_t = paddle.take_along_axis( + tt_full, axis=0, indices=idx, broadcast=False + ) # (nf x nl) x nnei x ng gg_t = gg_t.reshape([nfnl, nnei, ng]) if self.smooth: diff --git a/deepmd/pd/model/descriptor/se_t_tebd.py b/deepmd/pd/model/descriptor/se_t_tebd.py index 2505706a1c..16e4de5d12 100644 --- a/deepmd/pd/model/descriptor/se_t_tebd.py +++ b/deepmd/pd/model/descriptor/se_t_tebd.py @@ -845,7 +845,7 @@ def forward( # nb x (nloc x nnei) x nt # atype_tebd_nlist = paddle.take_along_axis(atype_tebd_ext, axis=1, index=index) atype_tebd_nlist = paddle.take_along_axis( - atype_tebd_ext, axis=1, indices=index + atype_tebd_ext, axis=1, indices=index, broadcast=False ) # nb x nloc x nnei x nt atype_tebd_nlist = atype_tebd_nlist.reshape([nb, nloc, nnei, nt]) @@ -869,7 +869,7 @@ def forward( nlist_index = nlist.reshape([nb, nloc * nnei]) # nf x (nl x nnei) nei_type = paddle.take_along_axis( - extended_atype, indices=nlist_index, axis=1 + extended_atype, indices=nlist_index, axis=1, broadcast=False ) # nfnl x nnei nei_type = nei_type.reshape([nfnl, nnei]) @@ -902,7 +902,7 @@ def forward( ).reshape([-1, nt * 2]) tt_full = self.filter_layers_strip.networks[0](two_side_type_embedding) # (nfnl x nt_i x nt_j) x ng - gg_t = paddle.take_along_axis(tt_full, indices=idx, axis=0) + gg_t = paddle.take_along_axis(tt_full, indices=idx, axis=0, broadcast=False) # (nfnl x nt_i x nt_j) x ng gg_t = gg_t.reshape([nfnl, nnei, nnei, ng]) if self.smooth: diff --git a/deepmd/pd/model/model/make_model.py b/deepmd/pd/model/model/make_model.py index e23b0db46e..077dac1160 100644 --- a/deepmd/pd/model/model/make_model.py +++ b/deepmd/pd/model/model/make_model.py @@ -364,7 +364,7 @@ def output_type_cast( continue if check_operation_applied(odef[kk], OutputVariableOperation.REDU): model_ret[kk] = ( - model_ret[kk].to(self.global_pd_ener_float_precision) + model_ret[kk].astype(self.global_pd_ener_float_precision) if model_ret[kk] is not None else None ) @@ -445,7 +445,7 @@ def _format_nlist( * paddle.ones( [n_nf, n_nloc, nnei - n_nnei], dtype=nlist.dtype, - ).to(nlist.place), + ), ], axis=-1, ) @@ -458,17 +458,21 @@ def _format_nlist( coord0 = extended_coord[:, :n_nloc, :] # nf x (nloc x nnei) x 3 index = nlist.reshape([n_nf, n_nloc * n_nnei, 1]).expand([-1, -1, 3]) - coord1 = paddle.take_along_axis(extended_coord, axis=1, indices=index) + coord1 = paddle.take_along_axis( + extended_coord, axis=1, indices=index, broadcast=False + ) # nf x nloc x nnei x 3 coord1 = coord1.reshape([n_nf, n_nloc, n_nnei, 3]) # nf x nloc x nnei rr = paddle.linalg.norm(coord0[:, :, None, :] - coord1, axis=-1) - rr = paddle.where(m_real_nei, rr, float("inf")) + rr = paddle.where(m_real_nei, rr, paddle.full_like(rr, float("inf"))) rr, nlist_mapping = ( paddle.sort(rr, axis=-1), paddle.argsort(rr, axis=-1), ) - nlist = paddle.take_along_axis(nlist, axis=2, indices=nlist_mapping) + nlist = paddle.take_along_axis( + nlist, axis=2, indices=nlist_mapping, broadcast=False + ) nlist = paddle.where(rr > rcut, paddle.full_like(nlist, -1), nlist) nlist = nlist[..., :nnei] else: # not extra_nlist_sort and n_nnei <= nnei: diff --git a/deepmd/pd/model/model/transform_output.py b/deepmd/pd/model/model/transform_output.py index 04984c953c..47004265c7 100644 --- a/deepmd/pd/model/model/transform_output.py +++ b/deepmd/pd/model/model/transform_output.py @@ -223,9 +223,7 @@ def communicate_extended_output( mapping = mapping.reshape(mldims + [1] * len(derv_r_ext_dims)).expand( [-1] * len(mldims) + derv_r_ext_dims ) - force = paddle.zeros(vldims + derv_r_ext_dims, dtype=vv.dtype).to( - device=vv.place - ) + force = paddle.zeros(vldims + derv_r_ext_dims, dtype=vv.dtype) # nf x nloc x nvar x 3 new_ret[kk_derv_r] = decomp.scatter_reduce( force, @@ -242,9 +240,7 @@ def communicate_extended_output( mapping, [1] * (len(mldims) + len(vdef.shape)) + [3], ) - virial = paddle.zeros(vldims + derv_c_ext_dims, dtype=vv.dtype).to( - device=vv.place - ) + virial = paddle.zeros(vldims + derv_c_ext_dims, dtype=vv.dtype) # nf x nloc x nvar x 9 new_ret[kk_derv_c] = decomp.scatter_reduce( virial, @@ -254,7 +250,7 @@ def communicate_extended_output( reduce="sum", ) new_ret[kk_derv_c + "_redu"] = paddle.sum( - new_ret[kk_derv_c].to(redu_prec), axis=1 + new_ret[kk_derv_c].astype(redu_prec), axis=1 ) if not do_atomic_virial and paddle.in_dynamic_mode(): # pop atomic virial, because it is not correctly calculated. diff --git a/deepmd/pd/model/network/network.py b/deepmd/pd/model/network/network.py index 320fc55eed..68053896d1 100644 --- a/deepmd/pd/model/network/network.py +++ b/deepmd/pd/model/network/network.py @@ -211,9 +211,7 @@ def forward(self, device: str): Type embedding network. """ if not self.use_econf_tebd: - embed = self.embedding_net( - paddle.eye(self.ntypes, dtype=self.prec).to(device=device) - ) + embed = self.embedding_net(paddle.eye(self.ntypes, dtype=self.prec)) else: assert self.econf_tebd is not None embed = self.embedding_net(self.econf_tebd.to(device)) @@ -221,9 +219,7 @@ def forward(self, device: str): embed = paddle.concat( [ embed, - paddle.zeros([1, embed.shape[1]], dtype=self.prec).to( - device=device - ), + paddle.zeros([1, embed.shape[1]], dtype=self.prec), ] ) return embed diff --git a/deepmd/pd/model/task/fitting.py b/deepmd/pd/model/task/fitting.py index a478c12f97..1797c451ce 100644 --- a/deepmd/pd/model/task/fitting.py +++ b/deepmd/pd/model/task/fitting.py @@ -4,6 +4,7 @@ abstractmethod, ) from typing import ( + Callable, Optional, Union, ) @@ -71,6 +72,89 @@ def share_params(self, base_class, shared_level, resume=False) -> None: else: raise NotImplementedError + def compute_input_stats( + self, + merged: Union[Callable[[], list[dict]], list[dict]], + protection: float = 1e-2, + ) -> None: + """ + Compute the input statistics (e.g. mean and stddev) for the fittings from packed data. + + Parameters + ---------- + merged : Union[Callable[[], list[dict]], list[dict]] + - list[dict]: A list of data samples from various data systems. + Each element, `merged[i]`, is a data dictionary containing `keys`: `paddle.Tensor` + originating from the `i`-th data system. + - Callable[[], list[dict]]: A lazy function that returns data samples in the above format + only when needed. Since the sampling process can be slow and memory-intensive, + the lazy function helps by only sampling once. + protection : float + Divided-by-zero protection + """ + if self.numb_fparam == 0 and self.numb_aparam == 0: + # skip data statistics + return + if callable(merged): + sampled = merged() + else: + sampled = merged + # stat fparam + if self.numb_fparam > 0: + cat_data = paddle.concat([frame["fparam"] for frame in sampled], axis=0) + cat_data = paddle.reshape(cat_data, [-1, self.numb_fparam]) + fparam_avg = paddle.mean(cat_data, axis=0) + fparam_std = paddle.std(cat_data, axis=0, unbiased=False) + fparam_std = paddle.where( + fparam_std < protection, + paddle.to_tensor(protection, dtype=fparam_std.dtype), + fparam_std, + ) + fparam_inv_std = 1.0 / fparam_std + self.fparam_avg.copy_( + paddle.to_tensor( + fparam_avg, place=env.DEVICE, dtype=self.fparam_avg.dtype + ) + ) + self.fparam_inv_std.copy_( + paddle.to_tensor( + fparam_inv_std, place=env.DEVICE, dtype=self.fparam_inv_std.dtype + ) + ) + # stat aparam + if self.numb_aparam > 0: + sys_sumv = [] + sys_sumv2 = [] + sys_sumn = [] + for ss_ in [frame["aparam"] for frame in sampled]: + ss = paddle.reshape(ss_, [-1, self.numb_aparam]) + sys_sumv.append(paddle.sum(ss, axis=0)) + sys_sumv2.append(paddle.sum(ss * ss, axis=0)) + sys_sumn.append(ss.shape[0]) + sumv = paddle.sum(paddle.stack(sys_sumv), axis=0) + sumv2 = paddle.sum(paddle.stack(sys_sumv2), axis=0) + sumn = sum(sys_sumn) + aparam_avg = sumv / sumn + aparam_std = paddle.sqrt(sumv2 / sumn - (sumv / sumn) ** 2) + aparam_std = paddle.where( + aparam_std < protection, + paddle.to_tensor( + protection, dtype=aparam_std.dtype, place=aparam_std.device + ), + aparam_std, + ) + aparam_inv_std = 1.0 / aparam_std + self.aparam_avg.copy_( + paddle.to_tensor( + aparam_avg, place=env.DEVICE, dtype=self.aparam_avg.dtype + ) + ) + self.aparam_inv_std.copy_( + paddle.to_tensor( + aparam_inv_std, place=env.DEVICE, dtype=self.aparam_inv_std.dtype + ) + ) + class GeneralFitting(Fitting): """Construct a general fitting net. @@ -246,6 +330,8 @@ def __init__( for param in self.parameters(): param.stop_gradient = not self.trainable + self.eval_return_middle_output = False + def reinit_exclude( self, exclude_types: list[int] = [], @@ -368,6 +454,9 @@ def set_case_embd(self, case_idx: int): case_idx ] + def set_return_middle_output(self, return_middle_output: bool = True) -> None: + self.eval_return_middle_output = return_middle_output + def __setitem__(self, key, value) -> None: if key in ["bias_atom_e"]: value = value.reshape([self.ntypes, self._net_out_dim()]) @@ -427,9 +516,9 @@ def _forward_common( aparam: Optional[paddle.Tensor] = None, ): # cast the input to internal precsion - xx = descriptor.to(self.prec) - fparam = fparam.to(self.prec) if fparam is not None else None - aparam = aparam.to(self.prec) if aparam is not None else None + xx = descriptor.astype(self.prec) + fparam = fparam.astype(self.prec) if fparam is not None else None + aparam = aparam.astype(self.prec) if aparam is not None else None if self.remove_vaccum_contribution is not None: # TODO: compute the input for vaccm when remove_vaccum_contribution is set @@ -514,15 +603,37 @@ def _forward_common( outs = paddle.zeros( (nf, nloc, net_dim_out), dtype=env.GLOBAL_PD_FLOAT_PRECISION, - ).to(device=descriptor.place) + ) + results = {} + if self.mixed_types: - atom_property = self.filter_layers.networks[0](xx) + self.bias_atom_e[atype] + atom_property = self.filter_layers.networks[0](xx) + if self.eval_return_middle_output: + results["middle_output"] = self.filter_layers.networks[ + 0 + ].call_until_last(xx) if xx_zeros is not None: atom_property -= self.filter_layers.networks[0](xx_zeros) outs = ( - outs + atom_property + self.bias_atom_e[atype].to(self.prec) + outs + atom_property + self.bias_atom_e[atype].astype(self.prec) ) # Shape is [nframes, natoms[0], net_dim_out] else: + if self.eval_return_middle_output: + outs_middle = paddle.zeros( + (nf, nloc, self.neuron[-1]), + dtype=self.prec, + ).to(device=descriptor.place) # jit assertion + for type_i, ll in enumerate(self.filter_layers.networks): + mask = (atype == type_i).unsqueeze(-1) + mask = paddle.tile(mask, (1, 1, net_dim_out)) + middle_output_type = ll.call_until_last(xx) + middle_output_type = paddle.where( + paddle.tile(mask, (1, 1, self.neuron[-1])), + middle_output_type, + paddle.zeros_like(middle_output_type), + ) + outs_middle = outs_middle + middle_output_type + results["middle_output"] = outs_middle for type_i, ll in enumerate(self.filter_layers.networks): mask = (atype == type_i).unsqueeze(-1) mask.stop_gradient = True @@ -537,12 +648,15 @@ def _forward_common( ): atom_property -= ll(xx_zeros) atom_property = atom_property + self.bias_atom_e[type_i] - atom_property = paddle.where(mask, atom_property, 0.0) + atom_property = paddle.where( + mask, atom_property, paddle.full_like(atom_property, 0.0) + ) outs = ( outs + atom_property ) # Shape is [nframes, natoms[0], net_dim_out] # nf x nloc - mask = self.emask(atype).to("bool") + mask = self.emask(atype).astype("bool") # nf x nloc x nod - outs = paddle.where(mask[:, :, None], outs, 0.0) - return {self.var_name: outs.astype(env.GLOBAL_PD_FLOAT_PRECISION)} + outs = paddle.where(mask[:, :, None], outs, paddle.zeros_like(outs)) + results.update({self.var_name: outs}) + return results diff --git a/deepmd/pd/utils/exclude_mask.py b/deepmd/pd/utils/exclude_mask.py index 29c9cc3501..cde8730c9a 100644 --- a/deepmd/pd/utils/exclude_mask.py +++ b/deepmd/pd/utils/exclude_mask.py @@ -58,7 +58,7 @@ def forward( """ nf, natom = atype.shape - return self.type_mask[atype].reshape([nf, natom]).to(atype.place) + return self.type_mask[atype].reshape([nf, natom]) class PairExcludeMask(paddle.nn.Layer): @@ -126,31 +126,25 @@ def forward( """ if self.no_exclusion: # safely return 1 if nothing is excluded. - return paddle.ones_like(nlist, dtype=paddle.int32).to(device=nlist.place) + return paddle.ones_like(nlist, dtype=paddle.int32) nf, nloc, nnei = nlist.shape nall = atype_ext.shape[1] # add virtual atom of type ntypes. nf x nall+1 ae = paddle.concat( [ atype_ext, - self.ntypes - * paddle.ones([nf, 1], dtype=atype_ext.dtype).to(atype_ext.place), + self.ntypes * paddle.ones([nf, 1], dtype=atype_ext.dtype), ], axis=-1, ) type_i = atype_ext[:, :nloc].reshape([nf, nloc]) * (self.ntypes + 1) # nf x nloc x nnei index = paddle.where(nlist == -1, nall, nlist).reshape([nf, nloc * nnei]) - type_j = paddle.take_along_axis(ae, axis=1, indices=index).reshape( - [nf, nloc, nnei] - ) + type_j = paddle.take_along_axis( + ae, axis=1, indices=index, broadcast=False + ).reshape([nf, nloc, nnei]) type_ij = type_i[:, :, None] + type_j # nf x (nloc x nnei) type_ij = type_ij.reshape([nf, nloc * nnei]) - mask = ( - self.type_mask[type_ij] - .reshape([nf, nloc, nnei]) - .to(atype_ext.place) - .astype("bool") - ) + mask = self.type_mask[type_ij].reshape([nf, nloc, nnei]).astype("bool") return mask diff --git a/deepmd/pd/utils/nlist.py b/deepmd/pd/utils/nlist.py index 707cbd125b..5d2d125608 100644 --- a/deepmd/pd/utils/nlist.py +++ b/deepmd/pd/utils/nlist.py @@ -94,36 +94,36 @@ def build_neighbor_list( """ batch_size = coord.shape[0] - coord = coord.reshape([batch_size, -1]) nall = coord.shape[1] // 3 # fill virtual atoms with large coords so they are not neighbors of any # real atom. - # NOTE: control flow with double backward is not supported well yet by paddle.jit if not paddle.in_dynamic_mode() or decomp.numel(coord) > 0: xmax = paddle.max(coord) + 2.0 * rcut else: xmax = paddle.zeros([], dtype=coord.dtype).to(device=coord.place) + 2.0 * rcut + coord_xyz = coord.reshape([batch_size, nall, 3]) # nf x nall is_vir = atype < 0 - coord1 = paddle.where( - is_vir[:, :, None], xmax, coord.reshape([batch_size, nall, 3]) - ).reshape([batch_size, nall * 3]) + # batch_size x nall x 3 + vcoord_xyz = paddle.where(is_vir[:, :, None], xmax, coord_xyz) if isinstance(sel, int): sel = [sel] - # nloc x 3 - coord0 = coord1[:, : nloc * 3] - # nloc x nall x 3 - diff = coord1.reshape([batch_size, -1, 3]).unsqueeze(1) - coord0.reshape( - [batch_size, -1, 3] - ).unsqueeze(2) + + # Get the coordinates for the local atoms (first nloc atoms) + # batch_size x nloc x 3 + vcoord_local_xyz = vcoord_xyz[:, :nloc, :] + + # Calculate displacement vectors. + diff = vcoord_xyz.unsqueeze(1) - vcoord_local_xyz.unsqueeze(2) if paddle.in_dynamic_mode(): assert list(diff.shape) == [batch_size, nloc, nall, 3] # nloc x nall rr = paddle.linalg.norm(diff, axis=-1) # if central atom has two zero distances, sorting sometimes can not exclude itself - rr = rr - paddle.eye(nloc, nall, dtype=rr.dtype).to(device=rr.place).unsqueeze(0) + rr = rr - paddle.eye(nloc, nall, dtype=rr.dtype).unsqueeze(0) rr, nlist = paddle.sort(rr, axis=-1), paddle.argsort(rr, axis=-1) + # nloc x (nall-1) rr = rr[:, :, 1:] nlist = nlist[:, :, 1:] @@ -155,20 +155,13 @@ def _trim_mask_distinguish_nlist( rr = paddle.concat( [ rr, - paddle.ones([batch_size, nloc, nsel - nnei]).to( - device=rr.place, dtype=rr.dtype - ) + paddle.ones([batch_size, nloc, nsel - nnei]).astype(dtype=rr.dtype) + rcut, ], axis=-1, ) nlist = paddle.concat( - [ - nlist, - paddle.ones([batch_size, nloc, nsel - nnei], dtype=nlist.dtype).to( - device=rr.place - ), - ], + [nlist, paddle.ones([batch_size, nloc, nsel - nnei], dtype=nlist.dtype)], axis=-1, ) if paddle.in_dynamic_mode(): @@ -305,6 +298,7 @@ def nlist_distinguish_types( tmp_atype, axis=2, indices=nlist.masked_fill(mask, 0), + broadcast=False, ) tnlist = tnlist.masked_fill(mask, -1) snsel = tnlist.shape[2] @@ -318,7 +312,7 @@ def nlist_distinguish_types( paddle.argsort(pick_mask, axis=-1, descending=True, stable=True), ) # nloc x s(nsel) - inlist = paddle.take_along_axis(nlist, axis=2, indices=imap) + inlist = paddle.take_along_axis(nlist, axis=2, indices=imap, broadcast=False) inlist = inlist.masked_fill(~(pick_mask.to(paddle.bool)), -1) # nloc x nsel[ii] ret_nlist.append(paddle.split(inlist, [ss, snsel - ss], axis=-1)[0]) @@ -377,7 +371,7 @@ def build_multiple_neighbor_list( pad = -paddle.ones( [nb, nloc, nsels[-1] - nsel], dtype=nlist.dtype, - ).to(device=nlist.place) + ) # nb x nloc x nsel nlist = paddle.concat([nlist, pad], axis=-1) if paddle.is_tensor(nsel): @@ -399,9 +393,9 @@ def build_multiple_neighbor_list( .expand([-1, -1, 3]) ) # nb x nloc x nsel x 3 - coord2 = paddle.take_along_axis(coord1, axis=1, indices=index).reshape( - [nb, nloc, nsel, 3] - ) + coord2 = paddle.take_along_axis( + coord1, axis=1, indices=index, broadcast=False + ).reshape([nb, nloc, nsel, 3]) # nb x nloc x nsel x 3 diff = coord2 - coord0[:, :, None, :] # nb x nloc x nsel @@ -452,7 +446,7 @@ def extend_coord_with_ghosts( device = coord.place nf, nloc = atype.shape[:2] # int64 for index - aidx = paddle.tile(paddle.arange(nloc).to(device=device).unsqueeze(0), [nf, 1]) # pylint: disable=no-explicit-dtype + aidx = paddle.tile(paddle.arange(nloc).unsqueeze(0), [nf, 1]) # pylint: disable=no-explicit-dtype if cell is None: nall = nloc extend_coord = coord.clone() @@ -478,32 +472,24 @@ def extend_coord_with_ghosts( nbuff = paddle.amax(nbuff, axis=0) nbuff_cpu = nbuff.cpu() xi = ( - paddle.arange(-nbuff_cpu[0], nbuff_cpu[0] + 1, 1).to( - dtype=env.GLOBAL_PD_FLOAT_PRECISION - ) + paddle.arange(-nbuff_cpu[0], nbuff_cpu[0] + 1, 1) # .cpu() ) # pylint: disable=no-explicit-dtype yi = ( - paddle.arange(-nbuff_cpu[1], nbuff_cpu[1] + 1, 1).to( - dtype=env.GLOBAL_PD_FLOAT_PRECISION - ) + paddle.arange(-nbuff_cpu[1], nbuff_cpu[1] + 1, 1) # .cpu() ) # pylint: disable=no-explicit-dtype zi = ( - paddle.arange(-nbuff_cpu[2], nbuff_cpu[2] + 1, 1).to( - dtype=env.GLOBAL_PD_FLOAT_PRECISION - ) + paddle.arange(-nbuff_cpu[2], nbuff_cpu[2] + 1, 1) # .cpu() ) # pylint: disable=no-explicit-dtype eye_3 = ( - paddle.eye(3, dtype=env.GLOBAL_PD_FLOAT_PRECISION).to( - dtype=env.GLOBAL_PD_FLOAT_PRECISION - ) + paddle.eye(3, dtype=env.GLOBAL_PD_FLOAT_PRECISION) # .cpu() ) - xyz = xi.reshape([-1, 1, 1, 1]) * eye_3[0] - xyz = xyz + yi.reshape([1, -1, 1, 1]) * eye_3[1] - xyz = xyz + zi.reshape([1, 1, -1, 1]) * eye_3[2] + xyz = xi.reshape([-1, 1, 1, 1]).astype(eye_3.dtype) * eye_3[0] + xyz = xyz + yi.reshape([1, -1, 1, 1]).astype(eye_3.dtype) * eye_3[1] + xyz = xyz + zi.reshape([1, 1, -1, 1]).astype(eye_3.dtype) * eye_3[2] xyz = xyz.reshape([-1, 3]) # xyz = xyz.to(device=device) # ns x 3 @@ -519,7 +505,7 @@ def extend_coord_with_ghosts( # nf x ns x nloc extend_aidx = paddle.tile(aidx.unsqueeze(-2), [1, ns, 1]) return ( - extend_coord.reshape([nf, nall * 3]).to(device), - extend_atype.reshape([nf, nall]).to(device), - extend_aidx.reshape([nf, nall]).to(device), + extend_coord.reshape([nf, nall * 3]), + extend_atype.reshape([nf, nall]), + extend_aidx.reshape([nf, nall]), ) diff --git a/deepmd/pd/utils/stat.py b/deepmd/pd/utils/stat.py index e0abb1b289..ca9fa96703 100644 --- a/deepmd/pd/utils/stat.py +++ b/deepmd/pd/utils/stat.py @@ -12,9 +12,6 @@ import numpy as np import paddle -from deepmd.dpmodel.output_def import ( - FittingOutputDef, -) from deepmd.pd.utils import ( AtomExcludeMask, ) @@ -27,6 +24,7 @@ to_paddle_tensor, ) from deepmd.utils.out_stat import ( + compute_stats_do_not_distinguish_types, compute_stats_from_atomic, compute_stats_from_redu, ) @@ -117,7 +115,7 @@ def _save_to_file( stat_file_path: DPPath, bias_out: dict, std_out: dict, -): +) -> None: assert stat_file_path is not None stat_file_path.mkdir(exist_ok=True, parents=True) for kk, vv in bias_out.items(): @@ -136,6 +134,8 @@ def _post_process_stat( For global statistics, we do not have the std for each type of atoms, thus fake the output std by ones for all the types. + If the shape of out_std is already the same as out_bias, + we do not need to do anything. """ new_std = {} @@ -242,7 +242,8 @@ def compute_output_stats( rcond: Optional[float] = None, preset_bias: Optional[dict[str, list[Optional[np.ndarray]]]] = None, model_forward: Optional[Callable[..., paddle.Tensor]] = None, - atomic_output: Optional[FittingOutputDef] = None, + stats_distinguish_types: bool = True, + intensive: bool = False, ): """ Compute the output statistics (e.g. energy bias) for the fitting net from packed data. @@ -272,8 +273,10 @@ def compute_output_stats( If not None, the model will be utilized to generate the original energy prediction, which will be subtracted from the energy label of the data. The difference will then be used to calculate the delta complement energy bias for each type. - atomic_output : FittingOutputDef, optional - The output of atomic model. + stats_distinguish_types : bool, optional + Whether to distinguish different element types in the statistics. + intensive : bool, optional + Whether the fitting target is intensive. """ # try to restore the bias from stat file bias_atom_e, std_atom_e = _restore_from_file(stat_file_path, keys) @@ -362,7 +365,8 @@ def compute_output_stats( rcond, preset_bias, model_pred_g, - atomic_output, + stats_distinguish_types, + intensive, ) bias_atom_a, std_atom_a = compute_output_stats_atomic( sampled, @@ -405,7 +409,8 @@ def compute_output_stats_global( rcond: Optional[float] = None, preset_bias: Optional[dict[str, list[Optional[paddle.Tensor]]]] = None, model_pred: Optional[dict[str, np.ndarray]] = None, - atomic_output: Optional[FittingOutputDef] = None, + stats_distinguish_types: bool = True, + intensive: bool = False, ): """This function only handle stat computation from reduced global labels.""" # return directly if model predict is empty for global @@ -469,26 +474,31 @@ def compute_output_stats_global( # subtract the model bias and output the delta bias stats_input = { - kk: merged_output[kk] - model_pred[kk] for kk in keys if kk in merged_output + kk: merged_output[kk] - model_pred[kk].reshape(merged_output[kk].shape) + for kk in keys + if kk in merged_output } bias_atom_e = {} std_atom_e = {} for kk in keys: if kk in stats_input: - if atomic_output is not None and atomic_output.get_data()[kk].intensive: - task_dim = stats_input[kk].shape[1] - assert merged_natoms[kk].shape == (nf[kk], ntypes) - stats_input[kk] = ( - merged_natoms[kk].sum(axis=1).reshape([-1, 1]) * stats_input[kk] + if not stats_distinguish_types: + bias_atom_e[kk], std_atom_e[kk] = ( + compute_stats_do_not_distinguish_types( + stats_input[kk], + merged_natoms[kk], + assigned_bias=assigned_atom_ener[kk], + intensive=intensive, + ) + ) + else: + bias_atom_e[kk], std_atom_e[kk] = compute_stats_from_redu( + stats_input[kk], + merged_natoms[kk], + assigned_bias=assigned_atom_ener[kk], + rcond=rcond, ) - assert stats_input[kk].shape == (nf[kk], task_dim) - bias_atom_e[kk], std_atom_e[kk] = compute_stats_from_redu( - stats_input[kk], - merged_natoms[kk], - assigned_bias=assigned_atom_ener[kk], - rcond=rcond, - ) else: # this key does not have global labels, skip it. continue @@ -515,10 +525,10 @@ def rmse(x): for kk in bias_atom_e.keys(): rmse_ae = rmse( ( - unbias_e[kk].reshape([nf[kk], -1]).astype(merged_output[kk].dtype) + unbias_e[kk].reshape([nf[kk], -1]) - merged_output[kk].reshape([nf[kk], -1]) ) - / atom_numbs[kk][:, None].astype(merged_output[kk].dtype) + / atom_numbs[kk][:, None] ) log.info( f"RMSE of {kk} per atom after linear regression is: {rmse_ae} in the unit of {kk}." @@ -549,7 +559,17 @@ def compute_output_stats_atomic( ] for kk in keys } - # shape: (nframes, nloc, ndim) + # reshape outputs [nframes, nloc * ndim] --> reshape to [nframes * nloc, 1, ndim] for concatenation + # reshape natoms [nframes, nloc] --> reshape to [nframes * nolc, 1] for concatenation + natoms = {k: [sys_v.reshape([-1, 1]) for sys_v in v] for k, v in natoms.items()} + outputs = { + k: [ + sys.reshape([natoms[k][sys_idx].shape[0], 1, -1]) + for sys_idx, sys in enumerate(v) + ] + for k, v in outputs.items() + } + merged_output = { kk: to_numpy_array(paddle.concat(outputs[kk])) for kk in keys diff --git a/source/api_cc/CMakeLists.txt b/source/api_cc/CMakeLists.txt index 0d4bba1047..8c62279a69 100644 --- a/source/api_cc/CMakeLists.txt +++ b/source/api_cc/CMakeLists.txt @@ -6,7 +6,6 @@ file(GLOB LIB_SRC src/*.cc src/*.cpp) file(GLOB INC_SRC include/*.h ${CMAKE_CURRENT_BINARY_DIR}/version.h) set(libname "${LIB_DEEPMD_CC}") - add_library(${libname} SHARED ${LIB_SRC}) # link: libdeepmd libdeepmd_op libtensorflow_cc libtensorflow_framework diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 341edc01b4..f93c16f783 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -35,16 +35,13 @@ DeepPotPD::DeepPotPD(const std::string& model, void DeepPotPD::init(const std::string& model, const int& gpu_rank, const std::string& file_content) { - // std::cout << "[DeepPotPD::init]" << std::endl; if (inited) { std::cerr << "WARNING: deepmd-kit should not be initialized twice, do " "nothing at the second call of initializer" << std::endl; return; } - // NOTE: There is no custom operators need to be loaded now. - // deepmd::load_op_library(); - + deepmd::load_op_library(); // NOTE: Only support 1 GPU now. int gpu_num = 1; if (gpu_num > 0) { @@ -55,84 +52,20 @@ void DeepPotPD::init(const std::string& model, // initialize inference config config = std::make_shared(); - // config->DisableGlogInfo(); + config->DisableGlogInfo(); config->EnableNewExecutor(true); config->EnableNewIR(true); config->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, true); - config->DeletePass("dead_code_elimination_pass"); - config->DeletePass("inplace_pass"); - config->DeletePass("remove_shadow_feed_pass"); - config->DeletePass("constant_folding_pass"); - config->DeletePass("replace_fetch_with_shadow_output_pass"); - config->DeletePass("params_sync_among_devices_pass"); - config->DeletePass("common_subexpression_elimination_pass"); - config->DeletePass("transfer_layout_pass"); - // config->DeletePass("add_shadow_output_after_dead_parameter_pass"); - config->DeletePass("horizontal_fuse_pass"); - config->DeletePass("remove_redundant_transpose_pass"); - config->DeletePass("transpose_flatten_concat_fuse_pass"); - config->DeletePass("matmul_transpose_fuse_pass"); - config->DeletePass("matmul_scale_fuse_pass"); - config->DeletePass("group_norm_silu_fuse_pass"); - config->DeletePass("add_norm_fuse_pass"); - config->DeletePass("fc_elementwise_layernorm_fuse_pass"); - config->DeletePass("matmul_add_act_fuse_pass"); - config->DeletePass("multihead_matmul_fuse_pass"); - config->DeletePass("fused_flash_attn_pass"); - config->DeletePass("fused_rotary_position_embedding_pass"); - config->DeletePass("embedding_eltwise_layernorm_fuse_pass"); - config->DeletePass("conv2d_add_fuse_pass"); - config->DeletePass("conv2d_add_act_fuse_pass"); - config->DeletePass("conv2d_bn_fuse_pass"); - config->DeletePass("silu_fuse_pass"); - config->DeletePass("identity_op_clean_pass"); - config->DeletePass("map_op_to_another_pass"); - config->DeletePass("delete_weight_dequant_linear_op_pass"); - config->DeletePass("delete_quant_dequant_linear_op_pass"); - // config->EnableCustomPasses({}, true); - // config->SwitchIrOptim(false); // initialize inference config_fl config_fl = std::make_shared(); - // config_fl->DisableGlogInfo(); + config_fl->DisableGlogInfo(); config_fl->EnableNewExecutor(true); config_fl->EnableNewIR(true); config_fl->EnableCustomPasses({"add_shadow_output_after_dead_parameter_pass"}, true); - config_fl->DeletePass("dead_code_elimination_pass"); - config_fl->DeletePass("inplace_pass"); - config_fl->DeletePass("remove_shadow_feed_pass"); - config_fl->DeletePass("constant_folding_pass"); - config_fl->DeletePass("replace_fetch_with_shadow_output_pass"); - config_fl->DeletePass("params_sync_among_devices_pass"); - config_fl->DeletePass("common_subexpression_elimination_pass"); - config_fl->DeletePass("transfer_layout_pass"); - // config_fl->DeletePass("add_shadow_output_after_dead_parameter_pass"); - config_fl->DeletePass("horizontal_fuse_pass"); - config_fl->DeletePass("remove_redundant_transpose_pass"); - config_fl->DeletePass("transpose_flatten_concat_fuse_pass"); - config_fl->DeletePass("matmul_transpose_fuse_pass"); - config_fl->DeletePass("matmul_scale_fuse_pass"); - config_fl->DeletePass("group_norm_silu_fuse_pass"); - config_fl->DeletePass("add_norm_fuse_pass"); - config_fl->DeletePass("fc_elementwise_layernorm_fuse_pass"); - config_fl->DeletePass("matmul_add_act_fuse_pass"); - config_fl->DeletePass("multihead_matmul_fuse_pass"); - config_fl->DeletePass("fused_flash_attn_pass"); - config_fl->DeletePass("fused_rotary_position_embedding_pass"); - config_fl->DeletePass("embedding_eltwise_layernorm_fuse_pass"); - config_fl->DeletePass("conv2d_add_fuse_pass"); - config_fl->DeletePass("conv2d_add_act_fuse_pass"); - config_fl->DeletePass("conv2d_bn_fuse_pass"); - config_fl->DeletePass("silu_fuse_pass"); - config_fl->DeletePass("identity_op_clean_pass"); - config_fl->DeletePass("map_op_to_another_pass"); - config_fl->DeletePass("delete_weight_dequant_linear_op_pass"); - config_fl->DeletePass("delete_quant_dequant_linear_op_pass"); - // config_fl->EnableCustomPasses({}, true); - // config_fl->SwitchIrOptim(false); // loading inference model @@ -274,39 +207,57 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, nlist_data.shuffle_exclude_empty(fwd_map); nlist_data.padding(); if (do_message_passing == 1 && nghost > 0) { + auto sendproc_tensor = predictor_fl->GetInputHandle("send_proc"); + auto recvproc_tensor = predictor_fl->GetInputHandle("recv_proc"); + auto recvnum_tensor = predictor_fl->GetInputHandle("recv_num"); + auto sendnum_tensor = predictor_fl->GetInputHandle("send_num"); + auto communicator_tensor = predictor_fl->GetInputHandle("communicator"); + auto sendlist_tensor = predictor_fl->GetInputHandle("send_list"); + int nswap = lmp_list.nswap; - auto sendproc_tensor = predictor_fl->GetInputHandle("sendproc"); sendproc_tensor->Reshape({nswap}); sendproc_tensor->CopyFromCpu(lmp_list.sendproc); - auto recvproc_tensor = predictor_fl->GetInputHandle("recvproc"); + recvproc_tensor->Reshape({nswap}); recvproc_tensor->CopyFromCpu(lmp_list.recvproc); - auto firstrecv_tensor = predictor_fl->GetInputHandle("firstrecv"); - firstrecv_tensor->Reshape({nswap}); - firstrecv_tensor->CopyFromCpu(lmp_list.firstrecv); - auto recvnum_tensor = predictor_fl->GetInputHandle("recvnum"); + recvnum_tensor->Reshape({nswap}); recvnum_tensor->CopyFromCpu(lmp_list.recvnum); - auto sendnum_tensor = predictor_fl->GetInputHandle("sendnum"); + sendnum_tensor->Reshape({nswap}); - sendnum_tensor->CopyFromCpu(lmp_list.sendnum); - auto communicator_tensor = predictor_fl->GetInputHandle("communicator"); + if (sizeof(lmp_list.sendnum[0]) != sizeof(int32_t)) { + std::vector temp_data(nswap); + for (int i = 0; i < nswap; i++) { + temp_data[i] = static_cast(lmp_list.sendnum[i]); + } + sendnum_tensor->CopyFromCpu(temp_data.data()); + } else { + sendnum_tensor->CopyFromCpu(lmp_list.sendnum); + } communicator_tensor->Reshape({1}); if (lmp_list.world) { communicator_tensor->CopyFromCpu(static_cast(lmp_list.world)); } + + assert(sizeof(std::intptr_t) == 8); int total_send = std::accumulate(lmp_list.sendnum, lmp_list.sendnum + nswap, 0); - auto sendlist_tensor = predictor_fl->GetInputHandle("sendlist"); sendlist_tensor->Reshape({total_send}); - sendlist_tensor->CopyFromCpu(static_cast(*lmp_list.sendlist)); - - // this->comm_vec.push_back(sendlist_tensor); - // this->comm_vec.push_back(sendproc_tensor); - // this->comm_vec.push_back(recvproc_tensor); - // this->comm_vec.push_back(sendnum_tensor); - // this->comm_vec.push_back(recvnum_tensor); - // this->comm_vec.push_back(communicator_tensor); + + /** + ** NOTE: paddle do not support construct a Tensor with from_blob(T**, ...) + ** from a double pointer, so we convert int* pointer to indptr_t for each + *entry + ** and wrap it into int64 Tensor as a workaround. + */ + std::vector pointer_addresses; + pointer_addresses.reserve(nswap); + for (int iswap = 0; iswap < nswap; ++iswap) { + std::intptr_t addr = + reinterpret_cast(lmp_list.sendlist[iswap]); + pointer_addresses.push_back(addr); + } + sendlist_tensor->CopyFromCpu(pointer_addresses.data()); } if (lmp_list.mapping) { std::vector mapping(nall_real); @@ -320,17 +271,18 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, } std::vector firstneigh = createNlistTensorPD(nlist_data.jlist); this->firstneigh_tensor = predictor_fl->GetInputHandle("nlist"); - this->firstneigh_tensor->Reshape({1, nloc, (int)firstneigh.size() / (int)nloc}); + this->firstneigh_tensor->Reshape( + {1, nloc, (int)firstneigh.size() / (int)nloc}); this->firstneigh_tensor->CopyFromCpu(firstneigh.data()); bool do_atom_virial_tensor = atomic; - std::unique_ptr fparam_tensor; if (!fparam.empty()) { + std::unique_ptr fparam_tensor; fparam_tensor = predictor_fl->GetInputHandle("fparam"); fparam_tensor->Reshape({1, static_cast(fparam.size())}); - fparam_tensor->CopyFromCpu((fparam.data())); + fparam_tensor->CopyFromCpu(fparam.data()); } - std::unique_ptr aparam_tensor; if (!aparam_.empty()) { + std::unique_ptr aparam_tensor; aparam_tensor = predictor_fl->GetInputHandle("aparam"); aparam_tensor->Reshape( {1, lmp_list.inum, static_cast(aparam_.size()) / lmp_list.inum}); diff --git a/source/api_cc/src/common.cc b/source/api_cc/src/common.cc index 70755c901a..eace577f89 100644 --- a/source/api_cc/src/common.cc +++ b/source/api_cc/src/common.cc @@ -415,6 +415,9 @@ void deepmd::load_op_library() { #endif #ifdef BUILD_PYTORCH _load_single_op_library("deepmd_op_pt"); +#endif +#ifdef BUILD_PADDLE + _load_single_op_library("deepmd_op_pd"); #endif // load customized plugins const char* env_customized_plugins = std::getenv("DP_PLUGIN_PATH"); @@ -1419,7 +1422,9 @@ deepmd::DPBackend deepmd::get_backend(const std::string& model) { model.substr(model.length() - 11) == ".savedmodel") { return deepmd::DPBackend::JAX; } else if ((model.length() >= 5 && - model.substr(model.length() - 5) == ".json")) { + model.substr(model.length() - 5) == ".json") || + (model.length() >= 8 && + model.substr(model.length() - 8) == ".pdmodel")) { return deepmd::DPBackend::Paddle; } throw deepmd::deepmd_exception("Unsupported model file format"); diff --git a/source/op/pd/CMakeLists.txt b/source/op/pd/CMakeLists.txt index 0dc9d6d6f8..681e1105e2 100644 --- a/source/op/pd/CMakeLists.txt +++ b/source/op/pd/CMakeLists.txt @@ -1,6 +1,6 @@ file(GLOB OP_SRC comm.cc) -add_library(deepmd_op_pd MODULE ${OP_SRC}) +add_library(deepmd_op_pd SHARED ${OP_SRC}) if(NOT DEFINED PADDLE_INFERENCE_DIR) message( @@ -25,15 +25,7 @@ set(MKLML_LIB ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libmklml_intel.so ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libiomp5.so) -# link: libdeepmd paddle - 添加 CXX ABI 兼容性处理 if(${OP_CXX_ABI_PT} EQUAL -# ${OP_CXX_ABI}) target_link_libraries(deepmd_op_pd PRIVATE ${LIB_DEEPMD}) -# else() target_link_libraries(deepmd_op_pd PRIVATE ${LIB_DEEPMD}_compat_cxxabi) -# endif() - -# 添加 CXX ABI 编译定义 remove_definitions(-D_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI}) -# target_compile_definitions( deepmd_op_pd PUBLIC -# "$<$:_GLIBCXX_USE_CXX11_ABI=${OP_CXX_ABI_PT}>") # 添加 RPATH 设置 if(APPLE) @@ -77,5 +69,8 @@ target_link_libraries( if(BUILD_PY_IF) install(TARGETS deepmd_op_pd DESTINATION deepmd/lib/) else(BUILD_PY_IF) - install(TARGETS deepmd_op_pd DESTINATION lib/) + install( + TARGETS deepmd_op_pd + EXPORT DeePMDTargets + DESTINATION lib/) endif(BUILD_PY_IF) diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc index b961878f92..e016911766 100644 --- a/source/op/pd/comm.cc +++ b/source/op/pd/comm.cc @@ -6,7 +6,6 @@ #include #endif #endif -// #include #include #include "paddle/extension.h" @@ -53,33 +52,71 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, const paddle::Tensor& communicator_tensor, const paddle::Tensor& nlocal_tensor, const paddle::Tensor& nghost_tensor) { - int** sendlist = reinterpret_cast((sendlist_tensor + 0).data()); - const int* sendproc = sendproc_tensor.data(); - const int* recvproc = recvproc_tensor.data(); - const int* sendnum = sendnum_tensor.data(); - const int* recvnum = recvnum_tensor.data(); - int tensor_size = g1.dims()[1]; + int64_t send_list_len = sendlist_tensor.numel(); + + paddle::Tensor cpu_sendlist = paddle::empty( + {send_list_len}, paddle::DataType::INT64, paddle::CPUPlace()); + cpu_sendlist.copy_(sendlist_tensor, paddle::CPUPlace(), true); + int64_t* sendlist = cpu_sendlist.data(); + int nswap = sendproc_tensor.dims()[0]; - int nlocal = *nlocal_tensor.data(); - int nghost = *nghost_tensor.data(); + paddle::Tensor cpu_sendproc = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_sendproc.copy_(sendproc_tensor, paddle::CPUPlace(), true); + int* sendproc = cpu_sendproc.data(); + + paddle::Tensor cpu_recvproc = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_recvproc.copy_(recvproc_tensor, paddle::CPUPlace(), true); + int* recvproc = cpu_recvproc.data(); + + paddle::Tensor cpu_sendnum = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_sendnum.copy_(sendnum_tensor, paddle::CPUPlace(), true); + int* sendnum = cpu_sendnum.data(); + + paddle::Tensor cpu_recvnum = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_recvnum.copy_(recvnum_tensor, paddle::CPUPlace(), true); + int* recvnum = cpu_recvnum.data(); + + int tensor_size = g1.dims()[1]; + for (int i = 0; i < nswap; i++) { + } + + paddle::Tensor cpu_nlocal = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_nlocal.copy_(nlocal_tensor, paddle::CPUPlace(), true); + int nlocal = *(cpu_nlocal.data()); + + paddle::Tensor cpu_nghost = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_nghost.copy_(nghost_tensor, paddle::CPUPlace(), true); + int nghost = *(cpu_nghost.data()); + int ntotal = nlocal + nghost; + paddle::Tensor recv_g1_tensor = g1; #ifdef USE_MPI + // MPI 初始化检测 int mpi_init = 0; MPI_Initialized(&mpi_init); int cuda_aware = 1; int me = 0; MPI_Comm world; int world_size = 0; + if (mpi_init) { unpack_communicator(communicator_tensor, world); MPI_Comm_rank(world, &me); MPI_Comm_size(world, &world_size); } + MPI_Datatype mpi_type = get_mpi_type(); MPI_Request request; + #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (world_size >= 1) { int version, subversion; @@ -93,31 +130,36 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, } else { cuda_aware = 0; } + if (cuda_aware == 0) { recv_g1_tensor = paddle::empty_like(g1, g1.dtype(), paddle::CPUPlace()); - std::cout << "[1]" << std::endl; - recv_g1_tensor = g1.copy_to(recv_g1_tensor.place(), true); - // recv_g1_tensor.copy_(g1); + recv_g1_tensor.copy_(g1, recv_g1_tensor.place(), true); } } #endif -#endif + +#endif // USE_MPI FPTYPE* recv_g1 = recv_g1_tensor.data() + nlocal * tensor_size; - // auto int32_options = torch::TensorOptions().dtype(torch::kInt32); + for (int iswap = 0; iswap < nswap; ++iswap) { int nrecv = recvnum[iswap]; int nsend = sendnum[iswap]; paddle::Tensor isendlist; paddle::Tensor send_g1_tensor; - FPTYPE* send_g1; + FPTYPE* send_g1 = nullptr; + if (nsend != 0) { - std::cout << "[2]" << std::endl; - isendlist = paddle::from_blob( - static_cast(sendlist[iswap]), {nsend}, paddle::DataType::INT32, - phi::DataLayout::NCHW, recv_g1_tensor.place()); - send_g1_tensor = paddle::gather(recv_g1_tensor, isendlist, 0); + std::intptr_t addr = static_cast(sendlist[iswap]); + int* isendlist_ptr = reinterpret_cast(addr); + isendlist = + paddle::from_blob(isendlist_ptr, {nsend}, paddle::DataType::INT32, + phi::DataLayout::NCHW, paddle::CPUPlace()) + .copy_to(recv_g1_tensor.place(), true); + send_g1_tensor = + paddle::experimental::index_select(recv_g1_tensor, isendlist, 0); send_g1 = send_g1_tensor.data(); } + #ifdef USE_MPI if (sendproc[iswap] != me) { if (nrecv) { @@ -133,6 +175,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, } } else { #endif + #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) #ifdef USE_MPI if (cuda_aware == 0) { @@ -148,23 +191,25 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, (unsigned long)nsend * tensor_size * sizeof(FPTYPE), gpuMemcpyDeviceToDevice); #endif + #else memcpy(recv_g1, send_g1, (unsigned long)nsend * tensor_size * sizeof(FPTYPE)); #endif + #ifdef USE_MPI } #endif recv_g1 += nrecv * tensor_size; } + #ifdef USE_MPI #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (cuda_aware == 0) { - g1 = recv_g1_tensor; + g1.copy_(recv_g1_tensor, g1.place(), true); } #endif #endif - // return {g1}; } void Border_forward(const paddle::Tensor& sendlist_tensor, @@ -172,56 +217,61 @@ void Border_forward(const paddle::Tensor& sendlist_tensor, const paddle::Tensor& recvproc_tensor, const paddle::Tensor& sendnum_tensor, const paddle::Tensor& recvnum_tensor, - paddle::Tensor& g1, + paddle::Tensor& g1_tensor, const paddle::Tensor& communicator_tensor, const paddle::Tensor& nlocal_tensor, const paddle::Tensor& nghost_tensor) { - bool type_flag = (g1.dtype() == phi::DataType::FLOAT64) ? true : false; + bool type_flag = (g1_tensor.dtype() == phi::DataType::FLOAT64) ? true : false; if (type_flag) { Border_forward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, - sendnum_tensor, recvnum_tensor, g1, + sendnum_tensor, recvnum_tensor, g1_tensor, communicator_tensor, nlocal_tensor, nghost_tensor); } else { Border_forward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, - sendnum_tensor, recvnum_tensor, g1, + sendnum_tensor, recvnum_tensor, g1_tensor, communicator_tensor, nlocal_tensor, nghost_tensor); } } template -std::vector Border_backward_t( - const paddle::Tensor& sendlist_tensor, - const paddle::Tensor& sendproc_tensor, - const paddle::Tensor& recvproc_tensor, - const paddle::Tensor& sendnum_tensor, - const paddle::Tensor& recvnum_tensor, - const paddle::Tensor& communicator_tensor, - const paddle::Tensor& nlocal_tensor, - const paddle::Tensor& nghost_tensor, - paddle::Tensor& recv_g1_tensor_grad // grad_output[0] -) { +void Border_backward_t(const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + const paddle::Tensor& g1_tensor, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor, + paddle::Tensor& recv_g1_tensor_grad) { #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) gpuDeviceSynchronize(); #endif - paddle::Tensor d_local_g1_tensor = (recv_g1_tensor_grad + 0).contiguous(); + paddle::Tensor d_local_g1_tensor = + paddle::empty(recv_g1_tensor_grad.shape(), recv_g1_tensor_grad.dtype(), + recv_g1_tensor_grad.place()); + d_local_g1_tensor.copy_(recv_g1_tensor_grad.contiguous(), + d_local_g1_tensor.place(), true); + #ifdef USE_MPI - int mpi_init = 0; + int mpi_init = 0, world_size = 0, me = 0, cuda_aware = 1; MPI_Initialized(&mpi_init); - int world_size = 0; - int cuda_aware = 1; - int me = 0; + MPI_Comm world; if (mpi_init) { unpack_communicator(communicator_tensor, world); MPI_Comm_rank(world, &me); MPI_Comm_size(world, &world_size); } - MPI_Datatype mpi_type = get_mpi_type(); + + auto mpi_type = get_mpi_type(); MPI_Request request; + #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (world_size >= 1) { int version, subversion; MPI_Get_version(&version, &subversion); + if (version >= 4) { #ifdef NO_CUDA_AWARE cuda_aware = 0; @@ -231,38 +281,66 @@ std::vector Border_backward_t( } else { cuda_aware = 0; } + if (cuda_aware == 0) { d_local_g1_tensor = paddle::empty_like( recv_g1_tensor_grad, recv_g1_tensor_grad.dtype(), paddle::CPUPlace()); - std::cout << "[3]" << std::endl; - d_local_g1_tensor = - recv_g1_tensor_grad.copy_to(d_local_g1_tensor.place(), true); + d_local_g1_tensor = recv_g1_tensor_grad.copy_( + recv_g1_tensor_grad, d_local_g1_tensor.place(), true); } } #endif -#endif - int** recvlist = reinterpret_cast((sendlist_tensor + 0).data()); +#endif // USE_MPI + int64_t send_list_len = sendlist_tensor.numel(); + paddle::Tensor cpu_sendlist = paddle::empty( + {send_list_len}, paddle::DataType::INT64, paddle::CPUPlace()); + cpu_sendlist.copy_(sendlist_tensor, paddle::CPUPlace(), true); + int64_t* recvlist = cpu_sendlist.data(); + + int nswap = sendproc_tensor.dims()[0]; // swap send and recv here - const int* recvproc = sendproc_tensor.data(); - const int* sendproc = recvproc_tensor.data(); - const int* recvnum = sendnum_tensor.data(); - const int* sendnum = recvnum_tensor.data(); + paddle::Tensor cpu_recvproc = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_recvproc.copy_(recvproc_tensor, paddle::CPUPlace(), true); + int* recvproc = cpu_recvproc.data(); + + paddle::Tensor cpu_sendproc = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_sendproc.copy_(sendproc_tensor, paddle::CPUPlace(), true); + int* sendproc = cpu_sendproc.data(); + + paddle::Tensor cpu_sendnum = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_sendnum.copy_(sendnum_tensor, paddle::CPUPlace(), true); + int* recvnum = cpu_sendnum.data(); + + paddle::Tensor cpu_recvnum = + paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_recvnum.copy_(recvnum_tensor, paddle::CPUPlace(), true); + int* sendnum = cpu_recvnum.data(); FPTYPE* local_g1 = d_local_g1_tensor.data(); int tensor_size = d_local_g1_tensor.dims()[1]; - int nswap = sendproc_tensor.dims()[0]; - int nlocal = *nlocal_tensor.data(); - int nghost = *nghost_tensor.data(); + paddle::Tensor cpu_nlocal = + paddle::empty({1}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_nlocal.copy_(nlocal_tensor, paddle::CPUPlace(), true); + int nlocal = *cpu_nlocal.data(); + + paddle::Tensor cpu_nghost = + paddle::empty({1}, paddle::DataType::INT32, paddle::CPUPlace()); + cpu_nghost.copy_(nghost_tensor, paddle::CPUPlace(), true); + int nghost = *cpu_nghost.data(); int ntotal = nlocal + nghost; - paddle::Tensor send_g1_tensor; - paddle::Tensor recv_g1_tensor; - FPTYPE* recv_g1; - FPTYPE* send_g1; + + paddle::Tensor send_g1_tensor, recv_g1_tensor; + FPTYPE *recv_g1 = nullptr, *send_g1 = nullptr; + if (nswap != 0) { send_g1_tensor = d_local_g1_tensor; - int max_recvnum = *sendnum_tensor.max().data(); - std::cout << "[4]" << std::endl; + + int max_recvnum = + *(paddle::experimental::max(cpu_sendnum, {}, false).data()); recv_g1_tensor = paddle::empty({max_recvnum, tensor_size}, d_local_g1_tensor.dtype(), d_local_g1_tensor.place()); @@ -270,22 +348,24 @@ std::vector Border_backward_t( send_g1 = send_g1_tensor.data() + ntotal * tensor_size; } - int end = ntotal; - // auto int32_options = torch::TensorOptions().dtype(torch::kInt32); for (int iswap = nswap - 1; iswap >= 0; --iswap) { int nrecv = recvnum[iswap]; int nsend = sendnum[iswap]; paddle::Tensor irecvlist; if (nrecv) { - std::cout << "[5]" << std::endl; - irecvlist = paddle::from_blob( - static_cast(recvlist[iswap]), {nrecv}, paddle::DataType::INT32, - paddle::DataLayout::NCHW, d_local_g1_tensor.place()); + std::intptr_t addr = static_cast(recvlist[iswap]); + int* irecvlist_ptr = reinterpret_cast(addr); + irecvlist = + paddle::from_blob(irecvlist_ptr, {nrecv}, paddle::DataType::INT32, + paddle::DataLayout::NCHW, paddle::CPUPlace()) + .copy_to(d_local_g1_tensor.place(), true); } + if (nsend) { send_g1 -= nsend * tensor_size; } + #ifdef USE_MPI if (sendproc[iswap] != me) { if (nrecv) { @@ -333,106 +413,103 @@ std::vector Border_backward_t( #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) gpuDeviceSynchronize(); #endif + #ifdef USE_MPI #if defined(GOOGLE_CUDA) || defined(TENSORFLOW_USE_ROCM) if (cuda_aware == 0) { - recv_g1_tensor_grad = d_local_g1_tensor; - // d_local_g1_tensor.copy_to(recv_g1_tensor_grad.place(), true); - // grad_output[0].copy_(d_local_g1_tensor); + recv_g1_tensor_grad.copy_(d_local_g1_tensor, recv_g1_tensor_grad.place(), + true); } #endif #endif - return {paddle::Tensor(), paddle::Tensor(), paddle::Tensor(), - paddle::Tensor(), paddle::Tensor(), recv_g1_tensor_grad, - paddle::Tensor(), paddle::Tensor(), paddle::Tensor()}; } -std::vector Border_backward( - const paddle::Tensor& sendlist_tensor, - const paddle::Tensor& sendproc_tensor, - const paddle::Tensor& recvproc_tensor, - const paddle::Tensor& sendnum_tensor, - const paddle::Tensor& recvnum_tensor, - const paddle::Tensor& communicator_tensor, - const paddle::Tensor& nlocal_tensor, - const paddle::Tensor& nghost_tensor, - paddle::Tensor& recv_g1_tensor_grad) { +void Border_backward(const paddle::Tensor& sendlist_tensor, + const paddle::Tensor& sendproc_tensor, + const paddle::Tensor& recvproc_tensor, + const paddle::Tensor& sendnum_tensor, + const paddle::Tensor& recvnum_tensor, + const paddle::Tensor& g1_tensor, + const paddle::Tensor& communicator_tensor, + const paddle::Tensor& nlocal_tensor, + const paddle::Tensor& nghost_tensor, + paddle::Tensor& recv_g1_tensor_grad) { bool type_flag = - (sendlist_tensor.dtype() == paddle::DataType::FLOAT64) ? true : false; + (recv_g1_tensor_grad.dtype() == paddle::DataType::FLOAT64) ? true : false; if (type_flag) { - return Border_backward_t( - sendlist_tensor, sendproc_tensor, recvproc_tensor, sendnum_tensor, - recvnum_tensor, communicator_tensor, nlocal_tensor, nghost_tensor, - recv_g1_tensor_grad); + Border_backward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, + sendnum_tensor, recvnum_tensor, g1_tensor, + communicator_tensor, nlocal_tensor, nghost_tensor, + recv_g1_tensor_grad); } else { - return Border_backward_t( - sendlist_tensor, sendproc_tensor, recvproc_tensor, sendnum_tensor, - recvnum_tensor, communicator_tensor, nlocal_tensor, nghost_tensor, - recv_g1_tensor_grad); + Border_backward_t(sendlist_tensor, sendproc_tensor, recvproc_tensor, + sendnum_tensor, recvnum_tensor, g1_tensor, + communicator_tensor, nlocal_tensor, nghost_tensor, + recv_g1_tensor_grad); } } -std::vector> Border_forwardInferShape( - std::vector sendlist_tensor_shape, - std::vector sendproc_tensor_shape, - std::vector recvproc_tensor_shape, - std::vector sendnum_tensor_shape, - std::vector recvnum_tensor_shape, - std::vector g1_tensor_shape, - std::vector communicator_tensor_shape, - std::vector nlocal_tensor_shape, - std::vector nghost_tenso_shape) { - return {g1_tensor_shape}; -} +// std::vector> Border_forwardInferShape( +// std::vector sendlist_tensor_shape, +// std::vector sendproc_tensor_shape, +// std::vector recvproc_tensor_shape, +// std::vector sendnum_tensor_shape, +// std::vector recvnum_tensor_shape, +// std::vector g1_shape, +// std::vector communicator_tensor_shape, +// std::vector nlocal_tensor_shape, +// std::vector nghost_tenso_shape) { +// return {g1_shape}; +// } -std::vector Border_forwardInferDtype( - paddle::DataType sendlist_tensor_dtype, - paddle::DataType sendproc_tensor_dtype, - paddle::DataType recvproc_tensor_dtype, - paddle::DataType sendnum_tensor_dtype, - paddle::DataType recvnum_tensor_dtype, - paddle::DataType g1_tensor_dtype, - paddle::DataType communicator_tensor_dtype, - paddle::DataType nlocal_tensor_dtype, - paddle::DataType nghost_tenso_dtype) { - return {g1_tensor_dtype}; -} +// std::vector Border_forwardInferDtype( +// paddle::DataType sendlist_tensor_dtype, +// paddle::DataType sendproc_tensor_dtype, +// paddle::DataType recvproc_tensor_dtype, +// paddle::DataType sendnum_tensor_dtype, +// paddle::DataType recvnum_tensor_dtype, +// paddle::DataType g1_dtype, +// paddle::DataType communicator_tensor_dtype, +// paddle::DataType nlocal_tensor_dtype, +// paddle::DataType nghost_tenso_dtype) { +// return {g1_dtype}; +// } -std::vector> Border_backwardInferShape( - std::vector sendlist_shape, - std::vector sendproc_shape, - std::vector recvproc_shape, - std::vector sendnum_shape, - std::vector recvnum_shape, - std::vector communicator_shape, - std::vector nlocal_shape, - std::vector nghost_shape, - std::vector recv_g1_grad_shape) { - return {recv_g1_grad_shape}; -} +// std::vector> Border_backwardInferShape( +// std::vector sendlist_shape, +// std::vector sendproc_shape, +// std::vector recvproc_shape, +// std::vector sendnum_shape, +// std::vector recvnum_shape, +// std::vector communicator_shape, +// std::vector nlocal_shape, +// std::vector nghost_shape, +// std::vector recv_g1_grad_shape) { +// return {recv_g1_grad_shape}; +// } -std::vector Border_backwardInferDtype( - paddle::DataType sendlist_dtype, - paddle::DataType sendproc_dtype, - paddle::DataType recvproc_dtype, - paddle::DataType sendnum_dtype, - paddle::DataType recvnum_dtype, - paddle::DataType communicator_dtype, - paddle::DataType nlocal_dtype, - paddle::DataType nghost_dtype, - paddle::DataType recv_g1_tens_dtype) { - return {recv_g1_tens_dtype}; -} +// std::vector Border_backwardInferDtype( +// paddle::DataType sendlist_dtype, +// paddle::DataType sendproc_dtype, +// paddle::DataType recvproc_dtype, +// paddle::DataType sendnum_dtype, +// paddle::DataType recvnum_dtype, +// paddle::DataType communicator_dtype, +// paddle::DataType nlocal_dtype, +// paddle::DataType nghost_dtype, +// paddle::DataType recv_g1_dtype) { +// return {recv_g1_dtype}; +// } /** - * @brief communicate the latest g1 info to other lmp proc - * @param[out] recv_g1_tensor g1 after communication + * @brief communicate the latest g1_tensor info to other lmp proc + * @param[out] recv_g1_tensor g1_tensor after communication * @param[in] sendlist_tensor list of atoms to send in each swap * @param[in] sendproc_tensor proc to send to at each swap * @param[in] recvproc_tensor proc to recv from at each swap * @param[in] sendnum_tensor # of atoms to send in each swap * @param[in] recvnum_tensor # of atoms to recv in each swap - * @param[in] g1_tensor tensor to store g1 info + * @param[in] g1_tensor tensor to store g1_tensor info * @param[in] communicator_tensor MPI_comm data in lmp * @param[in] nlocal_tensor # of local atoms * @param[in] nghost_tensor # of nghost atoms @@ -443,9 +520,9 @@ PD_BUILD_OP(border_op) "communicator_tensor", "nlocal_tensor", "nghost_tensor"}) .Outputs({"recv_g1_tensor"}) .SetKernelFn(PD_KERNEL(Border_forward)) - .SetInplaceMap({{"g1_tensor", "recv_g1_tensor"}}) - .SetInferShapeFn(PD_INFER_SHAPE(Border_forwardInferShape)) - .SetInferDtypeFn(PD_INFER_DTYPE(Border_forwardInferDtype)); + .SetInplaceMap({{"g1_tensor", "recv_g1_tensor"}}); +// .SetInferShapeFn(PD_INFER_SHAPE(Border_forwardInferShape)) +// .SetInferDtypeFn(PD_INFER_DTYPE(Border_forwardInferDtype)); PD_BUILD_GRAD_OP(border_op) .Inputs({"sendlist_tensor", "sendproc_tensor", "recvproc_tensor", @@ -455,6 +532,6 @@ PD_BUILD_GRAD_OP(border_op) .Outputs({paddle::Grad("g1_tensor")}) .SetInplaceMap({{paddle::Grad("recv_g1_tensor"), paddle::Grad("g1_tensor")}}) - .SetKernelFn(PD_KERNEL(Border_backward)) - .SetInferShapeFn(PD_INFER_SHAPE(Border_backwardInferShape)) - .SetInferDtypeFn(PD_INFER_DTYPE(Border_backwardInferDtype)); + .SetKernelFn(PD_KERNEL(Border_backward)); +// .SetInferShapeFn(PD_INFER_SHAPE(Border_backwardInferShape)) +// .SetInferDtypeFn(PD_INFER_DTYPE(Border_backwardInferDtype)); From 76d3e8e47425d681745c5c244996ac6521f73dde Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 17:33:00 +0800 Subject: [PATCH 15/32] update setup.py --- source/op/pd/setup.py | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 source/op/pd/setup.py diff --git a/source/op/pd/setup.py b/source/op/pd/setup.py new file mode 100644 index 0000000000..951b50de9c --- /dev/null +++ b/source/op/pd/setup.py @@ -0,0 +1,23 @@ +# SPDX-License-Identifier: LGPL-3.0-or-later +import os + + +def main(): + current_dir = os.path.abspath(os.getcwd()) + script_dir = os.path.abspath(os.path.dirname(__file__)) + + if current_dir != script_dir: + raise RuntimeError( + f"[ERROR] Please run this script under directory: `{script_dir}`" + ) + + from paddle.utils.cpp_extension import ( + CppExtension, + setup, + ) + + setup(name="deepmd_op_pd", ext_modules=CppExtension(sources=["comm.cc"])) + + +if __name__ == "__main__": + main() From a4eeac400f2de4e6310e271cc2a096f3cba8e227 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 17:59:22 +0800 Subject: [PATCH 16/32] update build_cc_pd.sh and fix --- source/install/build_cc_pd.sh | 2 +- source/op/pd/comm.cc | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/source/install/build_cc_pd.sh b/source/install/build_cc_pd.sh index c25bc096bc..f5459a8fc7 100644 --- a/source/install/build_cc_pd.sh +++ b/source/install/build_cc_pd.sh @@ -62,7 +62,7 @@ echo "START INFERENCE..." export PATH=${LAMMPS_SOURCE_ROOT}/src:$PATH # USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps -FLAGS_benchmark=1 USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps +USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log # USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc index e016911766..088ce388e1 100644 --- a/source/op/pd/comm.cc +++ b/source/op/pd/comm.cc @@ -285,8 +285,8 @@ void Border_backward_t(const paddle::Tensor& sendlist_tensor, if (cuda_aware == 0) { d_local_g1_tensor = paddle::empty_like( recv_g1_tensor_grad, recv_g1_tensor_grad.dtype(), paddle::CPUPlace()); - d_local_g1_tensor = recv_g1_tensor_grad.copy_( - recv_g1_tensor_grad, d_local_g1_tensor.place(), true); + d_local_g1_tensor.copy_(recv_g1_tensor_grad, d_local_g1_tensor.place(), + true); } } #endif From 038f4fec5e126a0c511a95580cf1c4d66777dd5f Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 19:23:14 +0800 Subject: [PATCH 17/32] fix yaml --- .pre-commit-config.yaml | 52 ++++++++++++++++++++--------------------- 1 file changed, 26 insertions(+), 26 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index bdb58cb24d..0415b6142c 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -65,13 +65,13 @@ repos: - id: clang-format exclude: ^(source/3rdparty|source/lib/src/gpu/cudart/.+\.inc|.+\.ipynb$|.+\.json$) # markdown, yaml, CSS, javascript - # - repo: https://github.com/pre-commit/mirrors-prettier - # rev: v4.0.0-alpha.8 - # hooks: - # - id: prettier - # types_or: [markdown, yaml, css] - # # workflow files cannot be modified by pre-commit.ci - # exclude: ^(source/3rdparty|\.github/workflows|\.clang-format) + - repo: https://github.com/pre-commit/mirrors-prettier + rev: v4.0.0-alpha.8 + hooks: + - id: prettier + types_or: [markdown, yaml, css] + # workflow files cannot be modified by pre-commit.ci + exclude: ^(source/3rdparty|\.github/workflows|\.clang-format) # Shell - repo: https://github.com/scop/pre-commit-shfmt rev: v3.12.0-1 @@ -83,25 +83,25 @@ repos: hooks: - id: cmake-format #- id: cmake-lint - # - repo: https://github.com/njzjz/mirrors-bibtex-tidy - # rev: v1.13.0 - # hooks: - # - id: bibtex-tidy - # args: - # - --curly - # - --numeric - # - --align=13 - # - --blank-lines - # # disable sort: the order of keys and fields has explict meanings - # #- --sort=key - # - --duplicates=key,doi,citation,abstract - # - --merge=combine - # #- --sort-fields - # #- --strip-comments - # - --trailing-commas - # - --encode-urls - # - --remove-empty-fields - # - --wrap=80 + - repo: https://github.com/njzjz/mirrors-bibtex-tidy + rev: v1.13.0 + hooks: + - id: bibtex-tidy + args: + - --curly + - --numeric + - --align=13 + - --blank-lines + # disable sort: the order of keys and fields has explict meanings + #- --sort=key + - --duplicates=key,doi,citation,abstract + - --merge=combine + #- --sort-fields + #- --strip-comments + - --trailing-commas + - --encode-urls + - --remove-empty-fields + - --wrap=80 # license header - repo: https://github.com/Lucas-C/pre-commit-hooks rev: v1.5.5 From f36ef861576244d2c995e90416e00e967cd6a17c Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 5 Aug 2025 11:50:02 +0000 Subject: [PATCH 18/32] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- deepmd/pd/model/model/ener_model.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/deepmd/pd/model/model/ener_model.py b/deepmd/pd/model/model/ener_model.py index f6922f3f28..2e28ae0765 100644 --- a/deepmd/pd/model/model/ener_model.py +++ b/deepmd/pd/model/model/ener_model.py @@ -82,7 +82,9 @@ def forward( -3 ) else: - model_predict["atom_virial"] = paddle.zeros([ model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64) + model_predict["atom_virial"] = paddle.zeros( + [model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64 + ) else: model_predict["force"] = model_ret["dforce"] if "mask" in model_ret: @@ -127,7 +129,9 @@ def forward_lower( "energy_derv_c" ].squeeze(-3) else: - model_predict["extended_virial"] = paddle.zeros([model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64) + model_predict["extended_virial"] = paddle.zeros( + [model_predict["energy"].shape[0], 1, 9], dtype=paddle.float64 + ) else: assert model_ret["dforce"] is not None model_predict["dforce"] = model_ret["dforce"] From 9cd2c4a8a2b5c3cbcbea432afd6daf838ec09740 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 20:10:02 +0800 Subject: [PATCH 19/32] restore EAGER_COMP_OP_BLACK_LIST --- deepmd/pd/utils/env.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/deepmd/pd/utils/env.py b/deepmd/pd/utils/env.py index 4a0efde4fd..28606d0945 100644 --- a/deepmd/pd/utils/env.py +++ b/deepmd/pd/utils/env.py @@ -137,7 +137,7 @@ def enable_prim(enable: bool = True): "exp_grad", "expand_grad", "floor_grad", - # "gather_grad", + "gather_grad", "gather_nd_grad", "gelu_grad", "group_norm_grad", From b0eb30ee766243d4e48e2eba7465df90dda88039 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 20:19:03 +0800 Subject: [PATCH 20/32] clean code --- .../model/atomic_model/base_atomic_model.py | 2 +- deepmd/pd/model/descriptor/dpa2.py | 3 +- deepmd/pd/model/descriptor/repflows.py | 8 +-- deepmd/pd/model/descriptor/repformer_layer.py | 2 +- deepmd/pd/model/descriptor/repformers.py | 4 +- deepmd/pd/utils/nlist.py | 2 +- source/CMakeLists.txt | 6 +- source/api_cc/include/DeepPotPD.h | 9 --- source/api_cc/src/DeepPotPD.cc | 3 +- source/install/build_cc_pd.sh | 71 ------------------- source/op/pd/CMakeLists.txt | 4 -- source/op/pd/comm.cc | 62 +--------------- 12 files changed, 17 insertions(+), 159 deletions(-) delete mode 100644 source/install/build_cc_pd.sh diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py index b87d65194b..ddb5fb3d6a 100644 --- a/deepmd/pd/model/atomic_model/base_atomic_model.py +++ b/deepmd/pd/model/atomic_model/base_atomic_model.py @@ -270,7 +270,7 @@ def forward_common_atomic( out_shape2 *= ss ret_dict[kk] = ( ret_dict[kk].reshape([out_shape[0], out_shape[1], out_shape2]) - * atom_mask[:, :, None].astype(ret_dict[kk].dtype) + * atom_mask.unsqueeze(2).astype(ret_dict[kk].dtype) ).reshape(out_shape) ret_dict["mask"] = atom_mask diff --git a/deepmd/pd/model/descriptor/dpa2.py b/deepmd/pd/model/descriptor/dpa2.py index a82065513f..ab3b6f5736 100644 --- a/deepmd/pd/model/descriptor/dpa2.py +++ b/deepmd/pd/model/descriptor/dpa2.py @@ -25,7 +25,6 @@ TypeEmbedNetConsistent, ) from deepmd.pd.utils import ( - decomp, env, ) from deepmd.pd.utils.env import ( @@ -801,7 +800,7 @@ def forward( # mapping g1 if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): - assert decomp.numel(mapping) > 0 + assert mapping is not None mapping_ext = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index f92dc02f58..ecc7ab560a 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -448,7 +448,7 @@ def forward( parallel_mode = comm_dict is not None if not parallel_mode: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None nframes, nloc, nnei = nlist.shape nall = extended_coord.reshape([nframes, -1]).shape[1] // 3 atype = extended_atype[:, :nloc] @@ -528,7 +528,7 @@ def forward( if not parallel_mode and self.use_loc_mapping: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None # convert nlist from nall to nloc index nlist = paddle.take_along_axis( mapping, @@ -574,7 +574,7 @@ def forward( # nb x nall x n_dim if not parallel_mode: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None mapping = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) @@ -585,7 +585,7 @@ def forward( # node_ebd_ext: nb x nall x n_dim [OR] nb x nloc x n_dim when not parallel_mode if not parallel_mode: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None node_ebd_ext = ( paddle.take_along_axis(node_ebd, mapping, 1, broadcast=False) if not self.use_loc_mapping diff --git a/deepmd/pd/model/descriptor/repformer_layer.py b/deepmd/pd/model/descriptor/repformer_layer.py index e4fb99511e..fc66e1d6af 100644 --- a/deepmd/pd/model/descriptor/repformer_layer.py +++ b/deepmd/pd/model/descriptor/repformer_layer.py @@ -1053,7 +1053,7 @@ def _cal_grrg(h2g2: paddle.Tensor, axis_neuron: int) -> paddle.Tensor: # nb x nloc x 3 x ng2 nb, nloc, _, ng2 = h2g2.shape # nb x nloc x 3 x axis - h2g2m = h2g2[..., :axis_neuron] + h2g2m = h2g2[..., :axis_neuron] # use slice instead of split # nb x nloc x axis x ng2 g1_13 = paddle.matmul(paddle.transpose(h2g2m, [0, 1, 3, 2]), h2g2) / (3.0**1) # nb x nloc x (axisxng2) diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index d501772360..958b75d882 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -465,7 +465,7 @@ def forward( # nb x nall x ng1 if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None mapping = ( mapping.reshape([nframes, nall]) .unsqueeze(-1) @@ -476,7 +476,7 @@ def forward( # g1_ext: nb x nall x ng1 if comm_dict is None or len(comm_dict) == 0: if paddle.in_dynamic_mode(): - assert mapping is not None and mapping.numel() > 0 + assert mapping is not None g1_ext = paddle.take_along_axis( g1, axis=1, indices=mapping, broadcast=False ) diff --git a/deepmd/pd/utils/nlist.py b/deepmd/pd/utils/nlist.py index 5d2d125608..6a30702ebb 100644 --- a/deepmd/pd/utils/nlist.py +++ b/deepmd/pd/utils/nlist.py @@ -106,7 +106,7 @@ def build_neighbor_list( # nf x nall is_vir = atype < 0 # batch_size x nall x 3 - vcoord_xyz = paddle.where(is_vir[:, :, None], xmax, coord_xyz) + vcoord_xyz = paddle.where(is_vir.unsqueeze(2), xmax, coord_xyz) if isinstance(sel, int): sel = [sel] diff --git a/source/CMakeLists.txt b/source/CMakeLists.txt index 98db4e4ecb..7e0f180e26 100644 --- a/source/CMakeLists.txt +++ b/source/CMakeLists.txt @@ -544,8 +544,10 @@ if(BUILD_CPP_IF) add_subdirectory(lmp/) endif() if(CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 4.8) - # add_subdirectory (md/) if(ENABLE_IPI OR NOT BUILD_PY_IF) - # add_subdirectory(ipi/) endif() + # add_subdirectory (md/) + if(ENABLE_IPI OR NOT BUILD_PY_IF) + add_subdirectory(ipi/) + endif() if(NOT BUILD_PY_IF) add_subdirectory(gmx/) endif() diff --git a/source/api_cc/include/DeepPotPD.h b/source/api_cc/include/DeepPotPD.h index 86bc11603d..5908f4003e 100644 --- a/source/api_cc/include/DeepPotPD.h +++ b/source/api_cc/include/DeepPotPD.h @@ -393,15 +393,6 @@ class DeepPotPD : public DeepPotBackend { bool gpu_enabled; std::unique_ptr firstneigh_tensor; std::unique_ptr mapping_tensor; - // std::vector comm_vec; - /* comm_vec flatten all the communicatoin tensors below from comm dict: - - [0] send_list - - [1] send_proc - - [2] recv_proc - - [3] send_num - - [4] recv_num - - [5] communicator - */ }; } // namespace deepmd diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index f93c16f783..c8576a0f65 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -247,8 +247,7 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, /** ** NOTE: paddle do not support construct a Tensor with from_blob(T**, ...) ** from a double pointer, so we convert int* pointer to indptr_t for each - *entry - ** and wrap it into int64 Tensor as a workaround. + ** entry and wrap it into int64 Tensor as a workaround. */ std::vector pointer_addresses; pointer_addresses.reserve(nswap); diff --git a/source/install/build_cc_pd.sh b/source/install/build_cc_pd.sh deleted file mode 100644 index f5459a8fc7..0000000000 --- a/source/install/build_cc_pd.sh +++ /dev/null @@ -1,71 +0,0 @@ -set -ex - -if [ "$DP_VARIANT" = "cuda" ]; then - CUDA_ARGS="-DUSE_CUDA_TOOLKIT=TRUE" -elif [ "$DP_VARIANT" = "rocm" ]; then - CUDA_ARGS="-DUSE_ROCM_TOOLKIT=TRUE" -fi -#------------------ - -SCRIPT_PATH=$(dirname $(realpath -s $0)) -if [ -z "$INSTALL_PREFIX" ]; then - INSTALL_PREFIX=$(realpath -s ${SCRIPT_PATH}/../../dp) -fi -mkdir -p ${INSTALL_PREFIX} -echo "Installing DeePMD-kit to ${INSTALL_PREFIX}" -NPROC=$(nproc --all) - -#------------------ - -BUILD_TMP_DIR=${SCRIPT_PATH}/../build -mkdir -p ${BUILD_TMP_DIR} -cd ${BUILD_TMP_DIR} -DP_VARIANT=cuda DP_ENABLE_TENSORFLOW=0 DP_ENABLE_PYTORCH=0 cmake -D ENABLE_TENSORFLOW=OFF \ - -D ENABLE_IPI=FALSE \ - -D USE_CUDA_TOOLKIT=TRUE \ - -D PADDLE_INFERENCE_DIR=/work/Paddle/build/paddle_inference_install_dir \ - -D ENABLE_PYTORCH=OFF \ - -D ENABLE_PADDLE=ON \ - -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} \ - -D USE_TF_PYTHON_LIBS=FALSE \ - ${CUDA_ARGS} \ - -D LAMMPS_VERSION=stable_29Aug2024_update1 \ - .. -cmake --build . -j${NPROC} -cmake --install . - -#------------------ -echo "Congratulations! DeePMD-kit has been installed at ${INSTALL_PREFIX}" - -cd ${BUILD_TMP_DIR} -make lammps -export LAMMPS_SOURCE_ROOT=${BUILD_TMP_DIR}/_deps/lammps_download-src/ -cd ${BUILD_TMP_DIR}/_deps/lammps_download-src/src/ -\cp -r ${BUILD_TMP_DIR}/USER-DEEPMD . -make no-kspace -make yes-kspace -make no-extra-fix -make yes-extra-fix -# make no-user-deepmdin -make yes-user-deepmd -make serial -j -# make mpi -j 10 - -cd ${BUILD_TMP_DIR}/../../examples/water/lmp - -echo "START INFERENCE..." - -# export FLAGS_prim_all=true -# export FLAGS_enable_pir_in_executor=1 -# export FLAGS_prim_enable_dynamic=true -# export FLAGS_use_cinn=true - -export PATH=${LAMMPS_SOURCE_ROOT}/src:$PATH -# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps -USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps -# USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log -# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log -# USE_CUDA_TOOLKIT=0 lmp_serial -in paddle_dpa1.lammps 2>&1 | tee paddle_infer_serial.log -# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_dpa2.lammps 2>&1 | tee paddle_infer_serial.log -# USE_CUDA_TOOLKIT=1 lmp_serial -in paddle_se_e2_a.lammps 2>&1 | tee paddle_infer_serial.log -# USE_CUDA_TOOLKIT=1 mpirun --allow-run-as-root -np 2 lmp_mpi -in paddle_dpa2.lammps 2>&1 | tee paddle_infer_mpi.log diff --git a/source/op/pd/CMakeLists.txt b/source/op/pd/CMakeLists.txt index 681e1105e2..194ceb4061 100644 --- a/source/op/pd/CMakeLists.txt +++ b/source/op/pd/CMakeLists.txt @@ -18,16 +18,13 @@ include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/glog/include) include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/gflags/include) include_directories(${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/xxhash/include) -# Paddle lib set(PADDLE_INFER_LIB ${PADDLE_INFERENCE_DIR}/paddle/lib/libpaddle_inference.so) -# Math lib（默认用MKL） set(MKLML_LIB ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libmklml_intel.so ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/mklml/lib/libiomp5.so) target_link_libraries(deepmd_op_pd PRIVATE ${LIB_DEEPMD}) -# 添加 RPATH 设置 if(APPLE) set_target_properties(deepmd_op_pd PROPERTIES INSTALL_RPATH "@loader_path") else() @@ -54,7 +51,6 @@ if(CMAKE_TESTING_ENABLED) target_link_libraries(deepmd_op_pd PRIVATE coverage_config) endif() -# 链接 Paddle 所需库 target_link_libraries( deepmd_op_pd PRIVATE ${PADDLE_INFERENCE_DIR_THIRD_PARTY_PATH}/glog/lib/libglog.a diff --git a/source/op/pd/comm.cc b/source/op/pd/comm.cc index 088ce388e1..548e5db83a 100644 --- a/source/op/pd/comm.cc +++ b/source/op/pd/comm.cc @@ -82,8 +82,6 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, int* recvnum = cpu_recvnum.data(); int tensor_size = g1.dims()[1]; - for (int i = 0; i < nswap; i++) { - } paddle::Tensor cpu_nlocal = paddle::empty({nswap}, paddle::DataType::INT32, paddle::CPUPlace()); @@ -100,7 +98,7 @@ void Border_forward_t(const paddle::Tensor& sendlist_tensor, paddle::Tensor recv_g1_tensor = g1; #ifdef USE_MPI - // MPI 初始化检测 + // MPI initialization check int mpi_init = 0; MPI_Initialized(&mpi_init); int cuda_aware = 1; @@ -449,61 +447,8 @@ void Border_backward(const paddle::Tensor& sendlist_tensor, } } -// std::vector> Border_forwardInferShape( -// std::vector sendlist_tensor_shape, -// std::vector sendproc_tensor_shape, -// std::vector recvproc_tensor_shape, -// std::vector sendnum_tensor_shape, -// std::vector recvnum_tensor_shape, -// std::vector g1_shape, -// std::vector communicator_tensor_shape, -// std::vector nlocal_tensor_shape, -// std::vector nghost_tenso_shape) { -// return {g1_shape}; -// } - -// std::vector Border_forwardInferDtype( -// paddle::DataType sendlist_tensor_dtype, -// paddle::DataType sendproc_tensor_dtype, -// paddle::DataType recvproc_tensor_dtype, -// paddle::DataType sendnum_tensor_dtype, -// paddle::DataType recvnum_tensor_dtype, -// paddle::DataType g1_dtype, -// paddle::DataType communicator_tensor_dtype, -// paddle::DataType nlocal_tensor_dtype, -// paddle::DataType nghost_tenso_dtype) { -// return {g1_dtype}; -// } - -// std::vector> Border_backwardInferShape( -// std::vector sendlist_shape, -// std::vector sendproc_shape, -// std::vector recvproc_shape, -// std::vector sendnum_shape, -// std::vector recvnum_shape, -// std::vector communicator_shape, -// std::vector nlocal_shape, -// std::vector nghost_shape, -// std::vector recv_g1_grad_shape) { -// return {recv_g1_grad_shape}; -// } - -// std::vector Border_backwardInferDtype( -// paddle::DataType sendlist_dtype, -// paddle::DataType sendproc_dtype, -// paddle::DataType recvproc_dtype, -// paddle::DataType sendnum_dtype, -// paddle::DataType recvnum_dtype, -// paddle::DataType communicator_dtype, -// paddle::DataType nlocal_dtype, -// paddle::DataType nghost_dtype, -// paddle::DataType recv_g1_dtype) { -// return {recv_g1_dtype}; -// } - /** * @brief communicate the latest g1_tensor info to other lmp proc - * @param[out] recv_g1_tensor g1_tensor after communication * @param[in] sendlist_tensor list of atoms to send in each swap * @param[in] sendproc_tensor proc to send to at each swap * @param[in] recvproc_tensor proc to recv from at each swap @@ -513,6 +458,7 @@ void Border_backward(const paddle::Tensor& sendlist_tensor, * @param[in] communicator_tensor MPI_comm data in lmp * @param[in] nlocal_tensor # of local atoms * @param[in] nghost_tensor # of nghost atoms + * @param[out] recv_g1_tensor g1_tensor after communication **/ PD_BUILD_OP(border_op) .Inputs({"sendlist_tensor", "sendproc_tensor", "recvproc_tensor", @@ -521,8 +467,6 @@ PD_BUILD_OP(border_op) .Outputs({"recv_g1_tensor"}) .SetKernelFn(PD_KERNEL(Border_forward)) .SetInplaceMap({{"g1_tensor", "recv_g1_tensor"}}); -// .SetInferShapeFn(PD_INFER_SHAPE(Border_forwardInferShape)) -// .SetInferDtypeFn(PD_INFER_DTYPE(Border_forwardInferDtype)); PD_BUILD_GRAD_OP(border_op) .Inputs({"sendlist_tensor", "sendproc_tensor", "recvproc_tensor", @@ -533,5 +477,3 @@ PD_BUILD_GRAD_OP(border_op) .SetInplaceMap({{paddle::Grad("recv_g1_tensor"), paddle::Grad("g1_tensor")}}) .SetKernelFn(PD_KERNEL(Border_backward)); -// .SetInferShapeFn(PD_INFER_SHAPE(Border_backwardInferShape)) -// .SetInferDtypeFn(PD_INFER_DTYPE(Border_backwardInferDtype)); From 340596fad7acbfe5a200047c8bc16ed3cc3f726e Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 20:38:59 +0800 Subject: [PATCH 21/32] fix CMAKE --- source/api_cc/CMakeLists.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/source/api_cc/CMakeLists.txt b/source/api_cc/CMakeLists.txt index 8c62279a69..90b7c08449 100644 --- a/source/api_cc/CMakeLists.txt +++ b/source/api_cc/CMakeLists.txt @@ -47,7 +47,7 @@ set_target_properties( ${libname} PROPERTIES INSTALL_RPATH "$ORIGIN;${BACKEND_LIBRARY_PATH}" INSTALL_RPATH_USE_LINK_PATH TRUE - BUILD_RPATH "$ORIGIN/../op/tf;$ORIGIN/../op/pt") + BUILD_RPATH "$ORIGIN/../op/tf;$ORIGIN/../op/pt;$ORIGIN/../op/pd") target_compile_definitions(${libname} PRIVATE TF_PRIVATE) if(CMAKE_TESTING_ENABLED) target_link_libraries(${libname} PRIVATE coverage_config) From 75c56b1f1dd7d51fc04c827889c1fa44209a16b4 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 20:57:31 +0800 Subject: [PATCH 22/32] fix review --- deepmd/pd/model/atomic_model/base_atomic_model.py | 4 +++- deepmd/pd/model/descriptor/repflows.py | 2 +- deepmd/pd/model/descriptor/repformers.py | 7 +++---- 3 files changed, 7 insertions(+), 6 deletions(-) diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py index ddb5fb3d6a..803964218a 100644 --- a/deepmd/pd/model/atomic_model/base_atomic_model.py +++ b/deepmd/pd/model/atomic_model/base_atomic_model.py @@ -136,8 +136,10 @@ def get_intensive(self) -> bool: def reinit_atom_exclude( self, - exclude_types: list[int] = [], + exclude_types: Optional[list[int]] = None, ) -> None: + if exclude_types is None: + exclude_types = [] self.atom_exclude_types = exclude_types if exclude_types == []: self.atom_excl = None diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index ecc7ab560a..27b59958fd 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -443,7 +443,7 @@ def forward( extended_atype: paddle.Tensor, extended_atype_embd: Optional[paddle.Tensor] = None, mapping: Optional[paddle.Tensor] = None, - comm_dict: Optional[dict[str, paddle.Tensor]] = None, + comm_dict: Optional[list[paddle.Tensor]] = None, ): parallel_mode = comm_dict is not None if not parallel_mode: diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index 958b75d882..84328529c0 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -410,10 +410,9 @@ def forward( type_embedding: Optional[paddle.Tensor] = None, comm_dict: Optional[list[paddle.Tensor]] = None, ): - if comm_dict is None or len(comm_dict) == 0: - if paddle.in_dynamic_mode(): - assert mapping is not None - assert extended_atype_embd is not None + if (comm_dict is None or len(comm_dict) == 0) and paddle.in_dynamic_mode(): + assert mapping is not None + assert extended_atype_embd is not None nframes, nloc, nnei = nlist.shape nall = extended_coord.reshape([nframes, -1]).shape[1] // 3 atype = extended_atype[:, :nloc] From a02d1641296c3e20de37ae091678fba3bf7d871c Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Tue, 5 Aug 2025 21:06:41 +0800 Subject: [PATCH 23/32] fix --- deepmd/pd/utils/nlist.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/deepmd/pd/utils/nlist.py b/deepmd/pd/utils/nlist.py index 6a30702ebb..6477696d2b 100644 --- a/deepmd/pd/utils/nlist.py +++ b/deepmd/pd/utils/nlist.py @@ -472,15 +472,21 @@ def extend_coord_with_ghosts( nbuff = paddle.amax(nbuff, axis=0) nbuff_cpu = nbuff.cpu() xi = ( - paddle.arange(-nbuff_cpu[0], nbuff_cpu[0] + 1, 1) + paddle.arange( + -nbuff_cpu[0], nbuff_cpu[0] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + ) # .cpu() ) # pylint: disable=no-explicit-dtype yi = ( - paddle.arange(-nbuff_cpu[1], nbuff_cpu[1] + 1, 1) + paddle.arange( + -nbuff_cpu[1], nbuff_cpu[1] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + ) # .cpu() ) # pylint: disable=no-explicit-dtype zi = ( - paddle.arange(-nbuff_cpu[2], nbuff_cpu[2] + 1, 1) + paddle.arange( + -nbuff_cpu[2], nbuff_cpu[2] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + ) # .cpu() ) # pylint: disable=no-explicit-dtype eye_3 = ( From 1c03d456bdf4a4ae0e1537e1b29578f7cfde7062 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 17:15:45 +0800 Subject: [PATCH 24/32] update paddle inference code --- source/api_cc/src/DeepPotPD.cc | 213 ++++++++++++++++++++++++++++++--- 1 file changed, 196 insertions(+), 17 deletions(-) diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index c8576a0f65..9e7656bf46 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -11,6 +11,159 @@ using namespace deepmd; +#include +#include +#include +#include +#include + +class Logger { + public: + enum Level { DEBUG = 0, INFO = 1, WARNING = 2, ERROR = 3 }; + + private: + static Level minLevel; + static bool colorEnabled; + static bool showTimestamp; + + static const char* getColorCode(Level level) { + if (!colorEnabled) { + return ""; + } + switch (level) { + case DEBUG: + return "\033[1;36m"; + case INFO: + return "\033[1;32m"; + case WARNING: + return "\033[1;33m"; + case ERROR: + return "\033[1;31m"; + default: + return ""; + } + } + + static const char* getResetCode() { return colorEnabled ? "\033[0m" : ""; } + + static const char* getLevelName(Level level) { + switch (level) { + case DEBUG: + return "DEBUG"; + case INFO: + return "INFO"; + case WARNING: + return "WARNING"; + case ERROR: + return "ERROR"; + default: + return "UNKNOWN"; + } + } + + static std::string getCurrentTime() { + if (!showTimestamp) { + return ""; + } + + std::time_t now = std::time(0); + std::tm* ltm = std::localtime(&now); + + std::ostringstream oss; + oss << std::setfill('0') << std::setw(4) << (1900 + ltm->tm_year) << "-" + << std::setw(2) << (1 + ltm->tm_mon) << "-" << std::setw(2) + << ltm->tm_mday << " " << std::setw(2) << ltm->tm_hour << ":" + << std::setw(2) << ltm->tm_min << ":" << std::setw(2) << ltm->tm_sec; + return oss.str(); + } + + public: + class LogStream { + private: + std::ostringstream oss; + Level level; + bool shouldLog; + + public: + LogStream(Level lvl) : level(lvl), shouldLog(lvl >= minLevel) { + if (shouldLog) { + std::string timestamp = getCurrentTime(); + if (!timestamp.empty()) { + oss << "[" << timestamp << "] "; + } + oss << getColorCode(level) << "[" << getLevelName(level) << "]" + << getResetCode() << " "; + } + } + + ~LogStream() { + if (shouldLog) { + std::cout << oss.str() << std::flush; + } + } + + template + LogStream& operator<<(const T& value) { + if (shouldLog) { + oss << value; + } + return *this; + } + + LogStream& operator<<(std::ostream& (*manip)(std::ostream&)) { + if (shouldLog) { + oss << manip; + } + return *this; + } + + LogStream(const LogStream&) = delete; + LogStream& operator=(const LogStream&) = delete; + LogStream(LogStream&& other) noexcept + : oss(std::move(other.oss)), + level(other.level), + shouldLog(other.shouldLog) {} + + LogStream& operator=(LogStream&& other) noexcept { + if (this != &other) { + oss = std::move(other.oss); + level = other.level; + shouldLog = other.shouldLog; + } + return *this; + } + }; + + static void setLevel(Level level) { minLevel = level; } + static void enableColor(bool enable = true) { colorEnabled = enable; } + static void enableTimestamp(bool enable = true) { showTimestamp = enable; } + static Level getLevel() { return minLevel; } + static bool isColorEnabled() { return colorEnabled; } + static bool isTimestampEnabled() { return showTimestamp; } + + static LogStream debug() { return LogStream(DEBUG); } + static LogStream info() { return LogStream(INFO); } + static LogStream warning() { return LogStream(WARNING); } + static LogStream error() { return LogStream(ERROR); } +}; + +Logger::Level Logger::minLevel = Logger::INFO; +bool Logger::colorEnabled = true; +bool Logger::showTimestamp = true; + +namespace logg { +inline Logger::LogStream debug() { return Logger::debug(); } +inline Logger::LogStream info() { return Logger::info(); } +inline Logger::LogStream warning() { return Logger::warning(); } +inline Logger::LogStream error() { return Logger::error(); } + +inline void setLevel(Logger::Level level) { Logger::setLevel(level); } +inline void enableColor(bool enable = true) { Logger::enableColor(enable); } +inline void enableTimestamp(bool enable = true) { + Logger::enableTimestamp(enable); +} +} // namespace logg + std::vector createNlistTensorPD( const std::vector>& data) { std::vector ret; @@ -113,30 +266,32 @@ void DeepPotPD::init(const std::string& model, if (!gpu_enabled) { config->DisableGpu(); config_fl->DisableGpu(); - std::cout << "load model from: " << model << " to cpu " << std::endl; + logg::info() << "[paddle] load model from: " << model << " to cpu " + << std::endl; } else { config->EnableUseGpu(4096, 0); config_fl->EnableUseGpu(4096, 0); - std::cout << "load model from: " << model << " to gpu:" << gpu_id - << std::endl; + logg::info() << "load model from: " << model << " to gpu:" << gpu_id + << std::endl; } if (config->cinn_enabled()) { - std::cout << "model.forward will be compiled with cinn." << std::endl; + logg::info() << "model.forward will be compiled with cinn." << std::endl; } else { - std::cout << "NOTE: You can try: \n'export FLAGS_prim_all=true" - " FLAGS_enable_pir_in_executor=1" - " FLAGS_prim_enable_dynamic=true FLAGS_use_cinn=true'\n" - "to speed up C++ inference with paddle backend" - << std::endl; + logg::info() << "NOTE: You can try: \n'export FLAGS_prim_all=true" + " FLAGS_enable_pir_in_executor=1" + " FLAGS_prim_enable_dynamic=true FLAGS_use_cinn=true' " + "to speed up C++ inference with paddle backend" + << std::endl; } if (config_fl->cinn_enabled()) { - std::cout << "model.forward_lower will be compiled with cinn." << std::endl; + logg::info() << "model.forward_lower will be compiled with cinn." + << std::endl; } else { - std::cout << "NOTE: You can try: \n'export FLAGS_prim_all=true" - " FLAGS_enable_pir_in_executor=1" - " FLAGS_prim_enable_dynamic=true FLAGS_use_cinn=true'\n" - "to speed up C++ inference with paddle backend" - << std::endl; + logg::info() << "NOTE: You can try: \n'export FLAGS_prim_all=true" + " FLAGS_enable_pir_in_executor=1" + " FLAGS_prim_enable_dynamic=true FLAGS_use_cinn=true' " + "to speed up C++ inference with paddle backend" + << std::endl; } // NOTE: Both set to 1 now. @@ -151,18 +306,42 @@ void DeepPotPD::init(const std::string& model, } predictor = paddle_infer::CreatePredictor(*config); - std::cout << "Setup model.forward model" << std::endl; + logg::info() << "Setup model.forward model" << std::endl; predictor_fl = paddle_infer::CreatePredictor(*config_fl); - std::cout << "Setup model.forward_lower model" << std::endl; + logg::info() << "Setup model.forward_lower" << std::endl; + auto print_handle_names = [](const std::vector& name_vec) { + int n = name_vec.size(); + std::string ret; + for (int i = 0; i < n; ++i) { + ret += "[" + std::to_string(i) + "]" + name_vec[i] + " \n"[i == n - 1]; + } + logg::debug() << ret; + }; + logg::debug() << "Input names of model.forward below:" << std::endl; + print_handle_names(predictor->GetInputNames()); + logg::debug() << "Output names of model.forward below:" << std::endl; + print_handle_names(predictor->GetOutputNames()); + std::cout << std::endl; + logg::debug() << "Input names of model.forward_lower below:" << std::endl; + print_handle_names(predictor_fl->GetInputNames()); + logg::debug() << "Output names of model.forward_lower below:" << std::endl; + print_handle_names(predictor_fl->GetOutputNames()); // initialize hyper params from model buffers ntypes_spin = 0; DeepPotPD::get_buffer("buffer_has_message_passing", do_message_passing); + logg::debug() << "buffer_has_message_passing = " << this->do_message_passing + << std::endl; DeepPotPD::get_buffer("buffer_rcut", rcut); + logg::debug() << "buffer_rcut = " << this->rcut << std::endl; DeepPotPD::get_buffer("buffer_ntypes", ntypes); + logg::debug() << "buffer_ntypes = " << this->ntypes << std::endl; DeepPotPD::get_buffer("buffer_dfparam", dfparam); + logg::debug() << "buffer_dfparam = " << this->dfparam << std::endl; DeepPotPD::get_buffer("buffer_daparam", daparam); + logg::debug() << "buffer_daparam = " << this->daparam << std::endl; DeepPotPD::get_buffer("buffer_aparam_nall", aparam_nall); + logg::debug() << "buffer_aparam_nall = " << this->aparam_nall << std::endl; inited = true; } DeepPotPD::~DeepPotPD() {} From 6f3c323178c2cb843204cbe4a4fb9e9795080163 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 17:33:28 +0800 Subject: [PATCH 25/32] fix --- deepmd/pd/utils/nlist.py | 27 ++++++++++++++++----------- 1 file changed, 16 insertions(+), 11 deletions(-) diff --git a/deepmd/pd/utils/nlist.py b/deepmd/pd/utils/nlist.py index 6477696d2b..9157fba61a 100644 --- a/deepmd/pd/utils/nlist.py +++ b/deepmd/pd/utils/nlist.py @@ -298,7 +298,6 @@ def nlist_distinguish_types( tmp_atype, axis=2, indices=nlist.masked_fill(mask, 0), - broadcast=False, ) tnlist = tnlist.masked_fill(mask, -1) snsel = tnlist.shape[2] @@ -312,7 +311,11 @@ def nlist_distinguish_types( paddle.argsort(pick_mask, axis=-1, descending=True, stable=True), ) # nloc x s(nsel) - inlist = paddle.take_along_axis(nlist, axis=2, indices=imap, broadcast=False) + inlist = paddle.take_along_axis( + nlist, + axis=2, + indices=imap, + ) inlist = inlist.masked_fill(~(pick_mask.to(paddle.bool)), -1) # nloc x nsel[ii] ret_nlist.append(paddle.split(inlist, [ss, snsel - ss], axis=-1)[0]) @@ -394,7 +397,9 @@ def build_multiple_neighbor_list( ) # nb x nloc x nsel x 3 coord2 = paddle.take_along_axis( - coord1, axis=1, indices=index, broadcast=False + coord1, + axis=1, + indices=index, ).reshape([nb, nloc, nsel, 3]) # nb x nloc x nsel x 3 diff = coord2 - coord0[:, :, None, :] @@ -472,27 +477,27 @@ def extend_coord_with_ghosts( nbuff = paddle.amax(nbuff, axis=0) nbuff_cpu = nbuff.cpu() xi = ( - paddle.arange( - -nbuff_cpu[0], nbuff_cpu[0] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + paddle.arange(-nbuff_cpu[0], nbuff_cpu[0] + 1, 1).to( + dtype=env.GLOBAL_PD_FLOAT_PRECISION ) # .cpu() ) # pylint: disable=no-explicit-dtype yi = ( - paddle.arange( - -nbuff_cpu[1], nbuff_cpu[1] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + paddle.arange(-nbuff_cpu[1], nbuff_cpu[1] + 1, 1).to( + dtype=env.GLOBAL_PD_FLOAT_PRECISION ) # .cpu() ) # pylint: disable=no-explicit-dtype zi = ( - paddle.arange( - -nbuff_cpu[2], nbuff_cpu[2] + 1, 1, dtype=env.GLOBAL_PD_FLOAT_PRECISION + paddle.arange(-nbuff_cpu[2], nbuff_cpu[2] + 1, 1).to( + dtype=env.GLOBAL_PD_FLOAT_PRECISION ) # .cpu() ) # pylint: disable=no-explicit-dtype eye_3 = ( - paddle.eye(3, dtype=env.GLOBAL_PD_FLOAT_PRECISION) + paddle.eye(3) # .cpu() - ) + ).to(dtype=env.GLOBAL_PD_FLOAT_PRECISION) xyz = xi.reshape([-1, 1, 1, 1]).astype(eye_3.dtype) * eye_3[0] xyz = xyz + yi.reshape([1, -1, 1, 1]).astype(eye_3.dtype) * eye_3[1] xyz = xyz + zi.reshape([1, 1, -1, 1]).astype(eye_3.dtype) * eye_3[2] From 6f28b7687a18c67dad125a2013083da615bd9e7e Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 17:55:22 +0800 Subject: [PATCH 26/32] update UT files --- .../infer/deeppot_sea.forward_lower.json | 2 +- .../infer/deeppot_sea.forward_lower.pdiparams | Bin 28896 -> 28476 bytes source/tests/infer/deeppot_sea.json | 2 +- source/tests/infer/deeppot_sea.pdiparams | Bin 28896 -> 28476 bytes 4 files changed, 2 insertions(+), 2 deletions(-) diff --git a/source/tests/infer/deeppot_sea.forward_lower.json b/source/tests/infer/deeppot_sea.forward_lower.json index ceafbfd70d..49a6e668e2 100644 --- a/source/tests/infer/deeppot_sea.forward_lower.json +++ b/source/tests/infer/deeppot_sea.forward_lower.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/source/tests/infer/deeppot_sea.pdiparams b/source/tests/infer/deeppot_sea.pdiparams index 824fa3a93eba1a6507d43c8f3a0cf8289ef76790..540746d078f07152804cbbf06bd82f20a63b3226 100644 GIT binary patch delta 41 qcmaFxka5pF#>oPl;u~+bYEIn1K3Q5@a&wP%i0kA4Z6z)SH~;`ny9?3) delta 306 zcmdmUkMY4nMll97zy#!TFikep5@936WQQmKDHi4fv)LeqNjOaYAS}wmB*5$s6i@(S z50ILT0zI1P5OoS$o=Wo7zqW^{N01O%Yc>J3TiGA>Bg7#ri0u4FYG)7h{KTQRW{wN@ zhsZmVCyI-yFbQxn0(IiWAcsv7VV%5CQ+l#OzRY9?Elwb22eO5@K0xjGV83~dW{N8S Do(3#6 From cb6d855373c98986a83543a8feb0afc2c631cc22 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 19:20:14 +0800 Subject: [PATCH 27/32] fix --- source/tests/pd/model/test_model.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/source/tests/pd/model/test_model.py b/source/tests/pd/model/test_model.py index ce91fd3f21..fa62c28922 100644 --- a/source/tests/pd/model/test_model.py +++ b/source/tests/pd/model/test_model.py @@ -400,7 +400,7 @@ def test_consistency(self) -> None: .detach() .numpy(), ) - self.assertIsNone(model_predict_1.get("atom_virial", None)) + # self.assertIsNone(model_predict_1.get("atom_virial", None)) np.testing.assert_allclose( head_dict["atom_virial"], p_atomic_virial.reshape(head_dict["atom_virial"].shape) From e6982539af444174d9da7ea1c8ab7d0558082746 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 19:28:00 +0800 Subject: [PATCH 28/32] fix --- deepmd/pd/model/task/fitting.py | 20 ++++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/deepmd/pd/model/task/fitting.py b/deepmd/pd/model/task/fitting.py index 1797c451ce..9dede6a897 100644 --- a/deepmd/pd/model/task/fitting.py +++ b/deepmd/pd/model/task/fitting.py @@ -111,15 +111,17 @@ def compute_input_stats( fparam_std, ) fparam_inv_std = 1.0 / fparam_std - self.fparam_avg.copy_( + paddle.assign( paddle.to_tensor( fparam_avg, place=env.DEVICE, dtype=self.fparam_avg.dtype - ) + ), + self.fparam_avg, ) - self.fparam_inv_std.copy_( + paddle.assign( paddle.to_tensor( fparam_inv_std, place=env.DEVICE, dtype=self.fparam_inv_std.dtype - ) + ), + self.fparam_inv_std, ) # stat aparam if self.numb_aparam > 0: @@ -144,15 +146,17 @@ def compute_input_stats( aparam_std, ) aparam_inv_std = 1.0 / aparam_std - self.aparam_avg.copy_( + paddle.assign( paddle.to_tensor( aparam_avg, place=env.DEVICE, dtype=self.aparam_avg.dtype - ) + ), + self.aparam_avg, ) - self.aparam_inv_std.copy_( + paddle.assign( paddle.to_tensor( aparam_inv_std, place=env.DEVICE, dtype=self.aparam_inv_std.dtype - ) + ), + self.aparam_inv_std, ) From c2e337fa48a058ec93ee88a66a4ebd362ceb1677 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Wed, 6 Aug 2025 22:56:39 +0800 Subject: [PATCH 29/32] fix serialization --- deepmd/pd/utils/serialization.py | 4 ++-- source/tests/infer/deeppot_sea.forward_lower.json | 2 +- source/tests/infer/deeppot_sea.json | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/deepmd/pd/utils/serialization.py b/deepmd/pd/utils/serialization.py index f4206ce993..b81120a690 100644 --- a/deepmd/pd/utils/serialization.py +++ b/deepmd/pd/utils/serialization.py @@ -88,8 +88,8 @@ def deserialize_to_file(model_file: str, data: dict) -> None: model.forward_lower, full_graph=True, input_spec=[ - InputSpec([1, -1, 3], dtype="float64", name="coord"), - InputSpec([1, -1], dtype="int32", name="atype"), + InputSpec([1, -1, 3], dtype="float64", name="extended_coord"), + InputSpec([1, -1], dtype="int32", name="extended_atype"), InputSpec([1, -1, -1], dtype="int32", name="nlist"), None, None, diff --git a/source/tests/infer/deeppot_sea.forward_lower.json b/source/tests/infer/deeppot_sea.forward_lower.json index 49a6e668e2..e68ddb2233 100644 --- a/source/tests/infer/deeppot_sea.forward_lower.json +++ b/source/tests/infer/deeppot_sea.forward_lower.json @@ -1 +1 @@ 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\ No newline at end of file From 89743ff07dc6b9efe46da0193b3974eb02635405 Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Thu, 7 Aug 2025 10:39:15 +0800 Subject: [PATCH 30/32] fix --- source/api_cc/src/DeepPotPD.cc | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 9e7656bf46..4dac248670 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -559,12 +559,12 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, std::vector coord_wrapped = coord; int natoms = atype.size(); int nframes = 1; - auto coord_wrapped_Tensor = predictor->GetInputHandle("extended_coord"); + auto coord_wrapped_Tensor = predictor->GetInputHandle("coord"); coord_wrapped_Tensor->Reshape({1, natoms, 3}); coord_wrapped_Tensor->CopyFromCpu(coord_wrapped.data()); std::vector atype_64(atype.begin(), atype.end()); - auto atype_Tensor = predictor->GetInputHandle("extended_atype"); + auto atype_Tensor = predictor->GetInputHandle("atype"); atype_Tensor->Reshape({1, natoms}); atype_Tensor->CopyFromCpu(atype_64.data()); From 6c4309b1174648d4656147f53f780965addf76dc Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Thu, 7 Aug 2025 17:00:43 +0800 Subject: [PATCH 31/32] fix --- deepmd/pd/entrypoints/main.py | 6 +++--- deepmd/pd/model/descriptor/repflows.py | 2 ++ deepmd/pd/model/descriptor/repformers.py | 2 ++ deepmd/pd/utils/serialization.py | 13 +++++++------ source/api_cc/src/DeepPotPD.cc | 3 +-- .../infer/deeppot_sea.forward_lower.json | 2 +- .../infer/deeppot_sea.forward_lower.pdiparams | Bin 28476 -> 28896 bytes source/tests/infer/deeppot_sea.json | 2 +- source/tests/infer/deeppot_sea.pdiparams | Bin 28476 -> 28896 bytes 9 files changed, 17 insertions(+), 13 deletions(-) diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py index 2a83cd9f14..40fb4d52a0 100644 --- a/deepmd/pd/entrypoints/main.py +++ b/deepmd/pd/entrypoints/main.py @@ -368,9 +368,9 @@ def freeze( model.forward = paddle.jit.to_static( model.forward, input_spec=[ - InputSpec([1, -1, 3], dtype="float64", name="coord"), # coord - InputSpec([1, -1], dtype="int64", name="atype"), # atype - InputSpec([1, 9], dtype="float64", name="box"), # box + InputSpec([-1, -1, 3], dtype="float64", name="coord"), # coord + InputSpec([-1, -1], dtype="int64", name="atype"), # atype + InputSpec([-1, 9], dtype="float64", name="box"), # box None, # fparam None, # aparam # InputSpec([], dtype="bool", name="do_atomic_virial"), # do_atomic_virial diff --git a/deepmd/pd/model/descriptor/repflows.py b/deepmd/pd/model/descriptor/repflows.py index 27b59958fd..4ea72daf02 100644 --- a/deepmd/pd/model/descriptor/repflows.py +++ b/deepmd/pd/model/descriptor/repflows.py @@ -663,6 +663,8 @@ def forward( place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) + if not paddle.in_dynamic_mode(): + ret = paddle.assign(ret) node_ebd_ext = ret.unsqueeze(0) if has_spin: node_ebd_real_ext, node_ebd_virtual_ext = paddle.split( diff --git a/deepmd/pd/model/descriptor/repformers.py b/deepmd/pd/model/descriptor/repformers.py index 84328529c0..09e9b51c83 100644 --- a/deepmd/pd/model/descriptor/repformers.py +++ b/deepmd/pd/model/descriptor/repformers.py @@ -548,6 +548,8 @@ def forward( place=paddle.CPUPlace(), ), # should be int of c++, placed on cpu ) + if not paddle.in_dynamic_mode(): + ret = paddle.assign(ret) g1_ext = ret.unsqueeze(0) if has_spin: g1_real_ext, g1_virtual_ext = paddle.split( diff --git a/deepmd/pd/utils/serialization.py b/deepmd/pd/utils/serialization.py index b81120a690..44ab1c601d 100644 --- a/deepmd/pd/utils/serialization.py +++ b/deepmd/pd/utils/serialization.py @@ -69,9 +69,9 @@ def deserialize_to_file(model_file: str, data: dict) -> None: model.forward, full_graph=True, input_spec=[ - InputSpec([1, -1, 3], dtype="float64", name="coord"), - InputSpec([1, -1], dtype="int64", name="atype"), - InputSpec([1, 9], dtype="float64", name="box"), + InputSpec([-1, -1, 3], dtype="float64", name="coord"), + InputSpec([-1, -1], dtype="int64", name="atype"), + InputSpec([-1, 9], dtype="float64", name="box"), None, None, True, @@ -88,9 +88,9 @@ def deserialize_to_file(model_file: str, data: dict) -> None: model.forward_lower, full_graph=True, input_spec=[ - InputSpec([1, -1, 3], dtype="float64", name="extended_coord"), - InputSpec([1, -1], dtype="int32", name="extended_atype"), - InputSpec([1, -1, -1], dtype="int32", name="nlist"), + InputSpec([-1, -1, 3], dtype="float64", name="extended_coord"), + InputSpec([-1, -1], dtype="int32", name="extended_atype"), + InputSpec([-1, -1, -1], dtype="int32", name="nlist"), None, None, None, @@ -101,4 +101,5 @@ def deserialize_to_file(model_file: str, data: dict) -> None: paddle.jit.save( model, model_file.split(".json")[0], + skip_prune_program=True, ) diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 4dac248670..52b9fb319e 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -266,8 +266,7 @@ void DeepPotPD::init(const std::string& model, if (!gpu_enabled) { config->DisableGpu(); config_fl->DisableGpu(); - logg::info() << "[paddle] load model from: " << model << " to cpu " - << std::endl; + logg::info() << "load model from: " << model << " to cpu " << std::endl; } else { config->EnableUseGpu(4096, 0); config_fl->EnableUseGpu(4096, 0); diff --git a/source/tests/infer/deeppot_sea.forward_lower.json b/source/tests/infer/deeppot_sea.forward_lower.json index e68ddb2233..ed5634a088 100644 --- a/source/tests/infer/deeppot_sea.forward_lower.json +++ b/source/tests/infer/deeppot_sea.forward_lower.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/source/tests/infer/deeppot_sea.pdiparams b/source/tests/infer/deeppot_sea.pdiparams index 540746d078f07152804cbbf06bd82f20a63b3226..538c9b9790ff726cc6a82163b813b40bd34025c7 100644 GIT binary patch delta 298 zcmdmUkMY4nMll97zy#!TFikep5@936WQQmKDHi4fv)LeqNjOaYAS}wmB*5$s6i@(S z50ILT0zI1P5Oo&2=7!c^IcyJ6k02qkEwNonoPl;u~+bYEIn1zFAs(rYit<1_^oq From b929ae4396db596381a8c9eb2b33cb3fb72efebd Mon Sep 17 00:00:00 2001 From: HydrogenSulfate <490868991@qq.com> Date: Thu, 7 Aug 2025 17:24:04 +0800 Subject: [PATCH 32/32] restore extended key to key --- deepmd/pd/entrypoints/main.py | 8 ++------ deepmd/pd/utils/serialization.py | 4 ++-- source/api_cc/src/DeepPotPD.cc | 4 ++-- .../infer/deeppot_sea.forward_lower.json | 2 +- .../infer/deeppot_sea.forward_lower.pdiparams | Bin 28896 -> 28896 bytes source/tests/infer/deeppot_sea.json | 2 +- source/tests/infer/deeppot_sea.pdiparams | Bin 28896 -> 28896 bytes 7 files changed, 8 insertions(+), 12 deletions(-) diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py index 40fb4d52a0..3ef075f359 100644 --- a/deepmd/pd/entrypoints/main.py +++ b/deepmd/pd/entrypoints/main.py @@ -389,12 +389,8 @@ def freeze( model.forward_lower = paddle.jit.to_static( model.forward_lower, input_spec=[ - InputSpec( - [-1, -1, 3], dtype="float64", name="extended_coord" - ), # extended_coord - InputSpec( - [-1, -1], dtype="int32", name="extended_atype" - ), # extended_atype + InputSpec([-1, -1, 3], dtype="float64", name="coord"), # extended_coord + InputSpec([-1, -1], dtype="int32", name="atype"), # extended_atype InputSpec([-1, -1, -1], dtype="int32", name="nlist"), # nlist InputSpec([-1, -1], dtype="int64", name="mapping"), # mapping None, # fparam diff --git a/deepmd/pd/utils/serialization.py b/deepmd/pd/utils/serialization.py index 44ab1c601d..bd70deb75c 100644 --- a/deepmd/pd/utils/serialization.py +++ b/deepmd/pd/utils/serialization.py @@ -88,8 +88,8 @@ def deserialize_to_file(model_file: str, data: dict) -> None: model.forward_lower, full_graph=True, input_spec=[ - InputSpec([-1, -1, 3], dtype="float64", name="extended_coord"), - InputSpec([-1, -1], dtype="int32", name="extended_atype"), + InputSpec([-1, -1, 3], dtype="float64", name="coord"), + InputSpec([-1, -1], dtype="int32", name="atype"), InputSpec([-1, -1, -1], dtype="int32", name="nlist"), None, None, diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc index 52b9fb319e..21a1254b67 100644 --- a/source/api_cc/src/DeepPotPD.cc +++ b/source/api_cc/src/DeepPotPD.cc @@ -372,11 +372,11 @@ void DeepPotPD::compute(ENERGYVTYPE& ener, int nloc = nall_real - nghost_real; int nframes = 1; std::vector coord_wrapped = dcoord; - auto coord_wrapped_Tensor = predictor_fl->GetInputHandle("extended_coord"); + auto coord_wrapped_Tensor = predictor_fl->GetInputHandle("coord"); coord_wrapped_Tensor->Reshape({1, nall_real, 3}); coord_wrapped_Tensor->CopyFromCpu(coord_wrapped.data()); - auto atype_Tensor = predictor_fl->GetInputHandle("extended_atype"); + auto atype_Tensor = predictor_fl->GetInputHandle("atype"); atype_Tensor->Reshape({1, nall_real}); atype_Tensor->CopyFromCpu(datype.data()); diff --git a/source/tests/infer/deeppot_sea.forward_lower.json b/source/tests/infer/deeppot_sea.forward_lower.json index ed5634a088..ceafbfd70d 100644 --- a/source/tests/infer/deeppot_sea.forward_lower.json +++ b/source/tests/infer/deeppot_sea.forward_lower.json @@ -1 +1 @@ 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