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Igoslow avatar Igoslow commented on July 17, 2024

this is a bug as follows:
Traceback (most recent call last):
File "E:/KG/kashgari/test_kashgari_onnx.py", line 26, in
onnx_model = onnxmltools.convert_keras(loaded_model.tf_model)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\onnxmltools\convert\main.py", line 33, in convert_keras
return convert(model, name, doc_string, target_opset, channel_first_inputs)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\keras2onnx\main.py", line 82, in convert_keras
parse_graph(topology, tf_graph, target_opset, output_names)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\keras2onnx\parser.py", line 828, in parse_graph
return _parse_graph_core(graph, keras_layer_ts_map, topo, top_level, output_names)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\keras2onnx\parser.py", line 746, in _parse_graph_core
_on_parsing_tf_subgraph(graph, nodes, varset)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\keras2onnx\parser.py", line 402, in _on_parsing_tf_subgraph
subgraph, replacement = create_subgraph(graph, node_list, sess, operator.full_name)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\keras2onnx\subgraph.py", line 170, in create_subgraph
tf.import_graph_def(output_graph_def, name=im_scope)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\tensorflow_core\python\framework\importer.py", line 405, in import_graph_def
producer_op_list=producer_op_list)
File "C:\Users\Learn\Envs\jiansuo1\lib\site-packages\tensorflow_core\python\framework\importer.py", line 505, in _import_graph_def_internal
raise ValueError(str(e))
ValueError: Input 0 of node TFNodes50/Embedding-Token/embedding_lookup was passed float from TFNodes50/Embedding-Token/embeddings:0 incompatible with expected resource.

Process finished with exit code 1

from onnx-docker.

jiafatom avatar jiafatom commented on July 17, 2024

Please try keras2onnx master directly to see if it works.

from onnx-docker.

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