C5W1A3 Cell #13 ValueError: Shapes (None, 90) and (None, 64) are incompatible

Course Q&A Deep Learning Specialization Sequence Models
1

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I’ve passed all the tests in UNQ C1 cell but later the it shows the error “”" ValueError: in user code:

/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:806 train_function  *
    return step_function(self, iterator)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:796 step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
/opt/conda/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
    return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
    return self._call_for_each_replica(fn, args, kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
    return fn(*args, **kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:789 run_step  **
    outputs = model.train_step(data)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:749 train_step
    y, y_pred, sample_weight, regularization_losses=self.losses)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/engine/compile_utils.py:204 __call__
    loss_value = loss_obj(y_t, y_p, sample_weight=sw)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/losses.py:149 __call__
    losses = ag_call(y_true, y_pred)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/losses.py:253 call  **
    return ag_fn(y_true, y_pred, **self._fn_kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201 wrapper
    return target(*args, **kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/losses.py:1535 categorical_crossentropy
    return K.categorical_crossentropy(y_true, y_pred, from_logits=from_logits)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py:201 wrapper
    return target(*args, **kwargs)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/backend.py:4687 categorical_crossentropy
    target.shape.assert_is_compatible_with(output.shape)
/opt/conda/lib/python3.7/site-packages/tensorflow/python/framework/tensor_shape.py:1134 assert_is_compatible_with
    raise ValueError("Shapes %s and %s are incompatible" % (self, other))

ValueError: Shapes (None, 90) and (None, 64) are incompatible

“”"
I used categorical crossentropy as provided in the exercise. What can I do?

2

My bad. I had to append the ‘out’ tensor to the outputs list in UNQ C1 instead of appending [out, c, a] which resulted in the following error. Learned from mistake. Took a lot of time to realize.

3

It’s great to hear that you were able to find the answer under your own power. Nice work. Onward! :nerd_face: