I run the code in my editor (VS Code) without any problems, but for next step and due to RAM and GPU limitation, I took it in colab, but got an error that seems to be due to mismatch of versions due to transfer from my editor to colab. how can i fix this problem?
The current version of python running on Google Colab is 3.8.16, I used tensorflow 2.3.0 and keras 2.4.3.
The error is related to this part of code when use the model.fit()
for train the model:
(I use CTC_loss in model):
model.fit(
train_dg,
validation_data=val_dg,
epochs=args.epochs,
callbacks=[PlotLossesKeras(),
early_stopping,
cp,
csv_logger,
lrs]
)
But I got this error:
----------------------------------------------------------------------------------------------------
**Epoch 00001: LearningRateScheduler reducing learning rate to 0.001. Epoch 1/300
-----------**---------------------------------------------------------------- InvalidArgumentError Traceback (most recent call last) <ipython-input-87-2b4ea6811b43> in <module>
----> 1 model.fit(train_dg,validation_data=val_dg,epochs=args.epochs,callbacks=[PlotLossesKeras(),early_stopping,cp,csv_logger,lrs])
9 frames /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
57 try:
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:
InvalidArgumentError: Saw a non-null label (index >= num_classes - 1) following a null label, batch: 2 num_classes: 16 labels: 16,0,0,0,0,0,0 labels seen so far: [[node functional_3/CTCloss/CTCLoss (defined at <ipython-input-17-1689d20fc46d>:887) ]] [Op:__inference_train_function_6401]
Function call stack: train_function
---------------------------------------------------------------------------------------
I try change the version of python in colab but it dosent work. also change num_classes in the last layer of my model, it dosent work too.