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adjust unit tests for test_save_load_float16 #12500

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Merged
merged 16 commits into from
Nov 13, 2025
Merged

adjust unit tests for test_save_load_float16 #12500

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b938d30
adjust unit tests for wan pipeline
kaixuanliu Oct 17, 2025
2244e23
update code
kaixuanliu Oct 30, 2025
906adf7
Merge branch 'main' into wan-pipeline
kaixuanliu Oct 30, 2025
5305169
avoid adjusting common `get_dummy_components` API
kaixuanliu Oct 30, 2025
a1d659c
Merge branch 'wan-pipeline' of https://github.com/kaixuanliu/diffuser…
kaixuanliu Oct 30, 2025
ecd4c8b
use `form_pretrained` to `transformer` and `transformer_2`
kaixuanliu Oct 30, 2025
62f3428
update code
kaixuanliu Nov 5, 2025
6b697ed
update
kaixuanliu Nov 5, 2025
91bdabf
Merge branch 'main' into wan-pipeline
sayakpaul Nov 5, 2025
3f2ab46
Merge branch 'main' into wan-pipeline
sayakpaul Nov 9, 2025
4bdfa35
Merge branch 'main' into wan-pipeline
DN6 Nov 10, 2025
b6e5a28
Merge branch 'main' into wan-pipeline
kaixuanliu Nov 11, 2025
6ec93a7
Merge branch 'main' into wan-pipeline
kaixuanliu Nov 12, 2025
1baf156
Merge branch 'main' into wan-pipeline
sayakpaul Nov 12, 2025
0ee299a
Merge branch 'main' into wan-pipeline
sayakpaul Nov 12, 2025
1a8dd43
Merge branch 'main' into wan-pipeline
sayakpaul Nov 13, 2025
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5 changes: 1 addition & 4 deletions tests/pipelines/test_pipelines_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1420,10 +1420,7 @@ def test_float16_inference(self, expected_max_diff=5e-2):
@unittest.skipIf(torch_device not in ["cuda", "xpu"], reason="float16 requires CUDA or XPU")
@require_accelerator
def test_save_load_float16(self, expected_max_diff=1e-2):
components = self.get_dummy_components()
for name, module in components.items():
if hasattr(module, "half"):
components[name] = module.to(torch_device).half()
components = self.get_dummy_components(dtype=torch.float16)

pipe = self.pipeline_class(**components)
for component in pipe.components.values():
Expand Down
18 changes: 9 additions & 9 deletions tests/pipelines/wan/test_wan_22.py
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Expand Up @@ -51,19 +51,19 @@ class Wan22PipelineFastTests(PipelineTesterMixin, unittest.TestCase):
test_xformers_attention = False
supports_dduf = False

def get_dummy_components(self):
def get_dummy_components(self, dtype=torch.float32):
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@sayakpaul sayakpaul Oct 30, 2025

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Why do we need this?

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@kaixuanliu kaixuanliu Oct 30, 2025 •
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pls refer to L246-L256 (Sorry I only found Chinese version for this explanation). Using torch.Tensor.to method will convert all weights, while using torch_dtype parameter with from_pretrained will preserve layers in _keep_in_fp32_modules. For wan models, all components of pipe will be fp16 dtype while it is not the case for pipe_loaded. Here I override test_save_load_float16 function seperately for wan models.

torch.manual_seed(0)
vae = AutoencoderKLWan(
base_dim=3,
z_dim=16,
dim_mult=[1, 1, 1, 1],
num_res_blocks=1,
temperal_downsample=[False, True, True],
)
).to(dtype=dtype)

torch.manual_seed(0)
scheduler = UniPCMultistepScheduler(prediction_type="flow_prediction", use_flow_sigmas=True, flow_shift=3.0)
text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5", dtype=dtype)
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")

torch.manual_seed(0)
Expand All @@ -80,7 +80,7 @@ def get_dummy_components(self):
cross_attn_norm=True,
qk_norm="rms_norm_across_heads",
rope_max_seq_len=32,
)
).to(dtype=dtype)

torch.manual_seed(0)
transformer_2 = WanTransformer3DModel(
Expand All @@ -96,7 +96,7 @@ def get_dummy_components(self):
cross_attn_norm=True,
qk_norm="rms_norm_across_heads",
rope_max_seq_len=32,
)
).to(dtype=dtype)

components = {
"transformer": transformer,
Expand Down Expand Up @@ -215,7 +215,7 @@ class Wan225BPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
test_xformers_attention = False
supports_dduf = False

def get_dummy_components(self):
def get_dummy_components(self, dtype=torch.float32):
torch.manual_seed(0)
vae = AutoencoderKLWan(
base_dim=3,
Expand All @@ -231,11 +231,11 @@ def get_dummy_components(self):
scale_factor_spatial=16,
scale_factor_temporal=4,
temperal_downsample=[False, True, True],
)
).to(dtype=dtype)

torch.manual_seed(0)
scheduler = UniPCMultistepScheduler(prediction_type="flow_prediction", use_flow_sigmas=True, flow_shift=3.0)
text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5")
text_encoder = T5EncoderModel.from_pretrained("hf-internal-testing/tiny-random-t5", dtype=dtype)
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")

torch.manual_seed(0)
Expand All @@ -252,7 +252,7 @@ def get_dummy_components(self):
cross_attn_norm=True,
qk_norm="rms_norm_across_heads",
rope_max_seq_len=32,
)
).to(dtype=dtype)

components = {
"transformer": transformer,
Expand Down