Module 6- Deep sequence modeling-RNN-LSTM.ipynb - DNN

[echokhan]

When using timeseries_dataset_from_array to create datasets, train_dataset, test_dataset and val_dataset had all uniform tensors except the last one which were partials, i.e. their samples and targets were as follows:

for samples, targets in train_dataset:
  if samples.shape != (batch_size, sequence_length, 14):
    print(samples.shape)
    print(targets.shape)

for samples, targets in test_dataset:
  if samples.shape != (batch_size, sequence_length, 14):
    print(samples.shape)
    print(targets.shape)

for samples, targets in val_dataset:
  if samples.shape != (batch_size, sequence_length, 14):
    print(samples.shape)
    print(targets.shape)

(103, 120, 14)
(103,)
(118, 120, 14)
(118,)
(206, 120, 14)
(206,)

This gave the error:

Epoch 1/10
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-146-e09ecdf9d4ec> in <cell line: 15>()
     13 ]
     14 model.compile(optimizer="rmsprop", loss="mse", metrics=["mae"])
---> 15 history = model.fit(train_dataset,
     16                     epochs=10,
     17                     validation_data=val_dataset,
Only one input size may be -1, not both 0 and 1
	 [[{{node functional_9_1/flatten_10_1/Reshape}}]] [Op:__inference_one_step_on_iterator_41264]

Although I remove the partial batches, I still get the error.
I do not get the same error when fitting the dataset with the CNN.