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test_mkldnn_matmul_activation_fuse_pass.py modify use_mkldnn [fluid_ops] #74575

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Merged
merged 1 commit into from
Aug 14, 2025
Merged

test_mkldnn_matmul_activation_fuse_pass.py modify use_mkldnn [fluid_ops] #74575

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12 changes: 6 additions & 6 deletions test/ir/inference/test_mkldnn_matmul_elementwise_add_fuse_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ def generate_input():
inputs={'X': ['matmul_x'], 'Y': ['matmul_y']},
outputs={'Out': ['matmul_output']},
attrs={
'use_mkldnn': True,
'use_onednn': True,
},
)

Expand All @@ -52,7 +52,7 @@ def generate_input():
type='elementwise_add',
inputs=inputs,
outputs={'Out': ['elementwise_add_output']},
attrs={'axis': axis, 'use_mkldnn': True},
attrs={'axis': axis, 'use_onednn': True},
)

model_net = [matmul_op, elt_add_op]
Expand Down Expand Up @@ -102,7 +102,7 @@ def generate_input():
inputs={'X': ['matmul_x'], 'Y': ['matmul_y']},
outputs={'Out': ['matmul_output']},
attrs={
'use_mkldnn': True,
'use_onednn': True,
},
)

Expand All @@ -115,7 +115,7 @@ def generate_input():
type='elementwise_add',
inputs=inputs,
outputs={'Out': ['elementwise_add_output']},
attrs={'axis': axis, 'use_mkldnn': True},
attrs={'axis': axis, 'use_onednn': True},
)

model_net = [matmul_op, elt_add_op]
Expand Down Expand Up @@ -168,7 +168,7 @@ def generate_input_redisual():
inputs={'X': ['matmul_x'], 'Y': ['matmul_y']},
outputs={'Out': ['matmul_output']},
attrs={
'use_mkldnn': True,
'use_onednn': True,
},
)

Expand All @@ -181,7 +181,7 @@ def generate_input_redisual():
type='elementwise_add',
inputs=inputs,
outputs={'Out': ['elementwise_add_output']},
attrs={'use_mkldnn': True},
attrs={'use_onednn': True},
)

model_net = [matmul_op, elt_add_op]
Expand Down
4 changes: 2 additions & 2 deletions test/ir/inference/test_onednn_batch_norm_act_fuse_pass.py
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Expand Up @@ -78,15 +78,15 @@ def generate_weight():
'momentum': momentum,
'trainable_statistics': trainable_statistics,
'use_global_stats': use_global_stats,
'use_mkldnn': use_onednn1,
'use_onednn': use_onednn1,
},
)

relu_op = OpConfig(
type='relu',
inputs={'X': ['norm_output']},
outputs={'Out': ['relu_output']},
attrs={'use_cudnn': use_cudnn, 'use_mkldnn': use_onednn2},
attrs={'use_cudnn': use_cudnn, 'use_onednn': use_onednn2},
)

model_net = [batch_norm_op, relu_op]
Expand Down