gaikwadrahul8
commented
1 year ago Hi, @jlouyang
Thank you for bringing this issue to our attention and I tried to replicate the same issue from my end with different versions of tensorflowjs like 4.7.*, 4.8.* and 4.9.* and I'm also getting same error message AssertionError: Identity is not in graph, please refer this gist-file
At the moment it seems like there are some Ops or TextVectorization Layer itself does not support in Tensorflow.js while converting the model into TFJs with the help of tensorflow_converter if that is the case then this issue will be considered as feature request
You can refer our official documentation of supported Tensorflow Ops for tfjs_converter, If have I missed something here please let me know ? Thank you!
jlouyang
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information
Describe the current behavior I'm trying to convert a tensorflow model to js, but I believe the TextVectorization layer isn't supported so I keep getting an error.
Describe the expected behavior
Standalone code to reproduce the issue Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/CodePen/any notebook.
import tensorflow as tf
text_dataset = tf.data.Dataset.from_tensor_slices(["foo", "bar", "baz"])
text_dataset = ['abcdefghijklmnopqrstuvwxyz'] max_features = 5000 # Maximum vocab size. max_len = 15 # Sequence length to pad the outputs to.
Create the layer.
vectorize_layer = tf.keras.layers.TextVectorization( max_tokens=max_features, output_mode='int', output_sequence_length=max_len,split='character',encoding='utf-8')
Now that the vocab layer has been created, call
adapton thetext-only dataset to create the vocabulary. You don't have to batch,
but for large datasets this means we're not keeping spare copies of
the dataset.
vectorize_layer.adapt(text_dataset)
Create the model that uses the vectorize text layer
model = tf.keras.models.Sequential()
Start by creating an explicit input layer. It needs to have a shape of
(1,) (because we need to guarantee that there is exactly one string
input per batch), and the dtype needs to be 'string'.
model.add(tf.keras.Input(shape=(1,), dtype=tf.string))
The first layer in our model is the vectorization layer. After this
layer, we have a tensor of shape (batch_size, max_len) containing
vocab indices.
model.add(vectorize_layer)
Now, the model can map strings to integers, and you can add an
embedding layer to map these integers to learned embeddings.
input_data = [["foo qux bar"], ["qux baz"]] print(model.predict(input_data))
model.save('test_saved_model')
Once the model is saved, if I try to use tensorflowjs_converter to convert to js I get an assertion error stating Identity is not in graph
Other info / logs Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.
Traceback (most recent call last): File "/Library/Frameworks/Python.framework/Versions/3.11/bin/tensorflowjs_converter", line 8, in
sys.exit(pip_main())
^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/converter.py", line 958, in pip_main
main([' '.join(sys.argv[1:])])
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/converter.py", line 962, in main
convert(argv[0].split(' '))
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/converter.py", line 948, in convert
_dispatch_converter(input_format, output_format, args, quantization_dtype_map,
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/converter.py", line 654, in _dispatch_converter
tf_saved_model_conversion_v2.convert_tf_saved_model(
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/tf_saved_model_conversion_v2.py", line 979, in convert_tf_saved_model
_convert_tf_saved_model(output_dir, saved_model_dir=saved_model_dir,
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/tf_saved_model_conversion_v2.py", line 821, in _convert_tf_saved_model
frozen_initializer_graph) = _freeze_saved_model_v1(saved_model_dir,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflowjs/converters/tf_saved_model_conversion_v2.py", line 436, in _freeze_saved_model_v1
frozen_graph_def = tf.compat.v1.graph_util.convert_variables_to_constants(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/util/deprecation.py", line 371, in new_func
return func(*args, *kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/framework/convert_to_constants.py", line 1330, in convert_variables_to_constants
ret = convert_variables_to_constants_from_session_graph(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/framework/convert_to_constants.py", line 1286, in convert_variables_to_constants_from_session_graph
converter_data=_SessionConverterData(
^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/framework/convert_to_constants.py", line 946, in init
graph_def = graph_util.extract_sub_graph(graph_def, output_node_names)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/util/deprecation.py", line 371, in new_func
return func(args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/framework/graph_util_impl.py", line 245, in extract_sub_graph
_assert_nodes_are_present(name_to_node, dest_nodes)
File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/tensorflow/python/framework/graph_util_impl.py", line 198, in _assert_nodes_are_present
assert d in name_to_node, "%s is not in graph" % d
^^^^^^^^^^^^^^^^^
AssertionError: Identity is not in graph