def test_embed_layer_norm_fusion(self):
onnx_files = []
for i in [3, 8, 9]:
onnx_files.append(f"embed_layer_norm_format{i}.onnx")
onnx_files.append(f"embed_layer_norm_format{i}_opset13.onnx")
onnx_files.append('embed_layer_norm_format3_no_cast.onnx')
onnx_files.append('embed_layer_norm_format3_no_cast_opset13.onnx')
for file in onnx_files:
input_model_path = get_fusion_test_model(file)
model = optimize_model(input_model_path, 'bert')
expected_node_count = {'EmbedLayerNormalization': 1, 'Attention': 1, 'ReduceSum': 0}
self.verify_node_count(model, expected_node_count, file)
def _get_test_model_path(name):
sub_dir, file = TEST_MODELS[name]
if sub_dir == "FUSION":
return get_fusion_test_model(file)
else:
return get_test_data_path(sub_dir, file)