InvalidArgumentError while using TensorBoard on a TensorFlow Hub Model

Question

So I was using this link to learn about the BERT model and about importing models from Tensorflow Hub.

Original Code( Colab ):

print(f'Training model with {tfhub_handle_encoder}')
history = classifier_model.fit(x=train_ds,
                               validation_data=val_ds,
                               epochs=epochs)

Now I tried to add TensorBoard to the Model.fit() function, but got this error after 12 frames.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     58     ctx.ensure_initialized()
     59     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
---> 60                                         inputs, attrs, num_outputs)
     61   except core._NotOkStatusException as e:
     62     if name is not None:

InvalidArgumentError: Value for attr 'T' of bool is not in the list of allowed values: float, double, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64
    ; NodeDef: {{node WriteHistogramSummary}}; Op<name=WriteHistogramSummary; signature=writer:resource, step:int64, tag:string, values:T -> ; attr=T:type,default=DT_FLOAT,allowed=[DT_FLOAT, DT_DOUBLE, DT_INT32, DT_UINT8, DT_INT16, DT_INT8, DT_INT64, DT_BFLOAT16, DT_UINT16, DT_HALF, DT_UINT32, DT_UINT64]; is_stateful=true> [Op:WriteHistogramSummary]

My Code( Colab ):

%load_ext tensorboard

!rm -rf ./logs/

log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)

print(f'Training model with {tfhub_handle_encoder}')
history = classifier_model.fit(x=train_ds,
                               validation_data=val_ds,
                               epochs=epochs,
                               callbacks=[tensorboard_callback])

%tensorboard --logdir logs/fit

A similar question was posted here but it got no replies.

Please help!

Edit 1: Error's Screenshot

Please suggest any edits.

Answer 1

there is an open issue on the TensorFlow repo on GitHub. issue #43200

A fix is being proposed but I don't know if it is implemented in the core framework yet (hence the issue being open).