Merge branch 'fastmachinelearning:main' into oneapi_backend/experiment

Author: haoyanwa

hls4ml/model/graph.py

@@ -565,6 +565,9 @@ def remove_node(self, node, rewire=True):
                     if outputs[0] == nxt_inp:
                         next_node.inputs[i] = inputs[0]
 
+        if node.outputs[0] in self.outputs:
+            prev_node = node.get_input_node(node.inputs[0])
+            self.outputs[self.outputs.index(node.outputs[0])] = prev_node.outputs[0]
         del self.output_vars[node.outputs[0]]
         del self.graph[node.name]
 

hls4ml/model/optimizer/passes/move_scales.py

@@ -12,6 +12,9 @@
 from hls4ml.model.layers import ApplyAlpha, Constant, Conv, MatMul, Merge
 from hls4ml.model.optimizer import OptimizerPass
 
+# These attributes should not be copied. (Should add the output name to this)
+_attrs_not_to_copy = ['trace', 'precision', 'scale', 'bias', 'scale_data', 'bias_data']
+
 
 class ScaleDownMatMul(OptimizerPass):
     '''Shift an ApplyAlpha below a MatMul'''
@@ -62,7 +65,7 @@ def transform(self, model, node):
 
         output = node.get_output_variable()
         # to remove warning, since these get set again
-        new_attrs = {k: v for k, v in apply_alpha.attributes.items() if k not in ('trace', 'precision')}
+        new_attrs = {k: v for k, v in apply_alpha.attributes.items() if k not in _attrs_not_to_copy + apply_alpha.outputs}
 
         can_propagate = False
         if not bias.shape and bias == 0:
@@ -258,7 +261,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in0.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in0.attributes.items() if k not in _attrs_not_to_copy + in0.outputs}
             new_name = in0.name
             model.remove_node(in0)
 
@@ -305,7 +308,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in0.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in0.attributes.items() if k not in _attrs_not_to_copy + in0.outputs}
             new_name = in1.name
             model.remove_node(in1)
 
@@ -329,7 +332,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in2.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in2.attributes.items() if k not in _attrs_not_to_copy + in2.outputs}
             new_name = in2.name
             model.remove_node(in2)
 
@@ -391,7 +394,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in0.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in0.attributes.items() if k not in _attrs_not_to_copy + in0.outputs}
             new_name = in1.name
             model.remove_node(in0)
             model.remove_node(in1)
@@ -415,7 +418,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in0.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in0.attributes.items() if k not in _attrs_not_to_copy + in0.outputs}
             new_name = in0.name
             model.remove_node(in0)
             model.remove_node(in2)
@@ -442,7 +445,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in1.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in1.attributes.items() if k not in _attrs_not_to_copy + in1.outputs}
             new_name = in1.name
             model.remove_node(in1)
             model.remove_node(in2)
@@ -478,7 +481,7 @@ def transform(self, model, node):
                 return False
 
             # to remove warning, since these get set again
-            new_attrs = {k: v for k, v in in0.attributes.items() if k not in ('trace', 'precision')}
+            new_attrs = {k: v for k, v in in0.attributes.items() if k not in _attrs_not_to_copy + in0.outputs}
             new_name = in0.name
             model.remove_node(in0)
             model.remove_node(in1)