gistfile1.txt

      1/Unknown - 0s 14ms/step
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-231b4cfe798d> in <module>()
     19 dataset = dataset.batch(4).prefetch(1)
     20 
---> 21 model.fit(dataset)

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
    732         max_queue_size=max_queue_size,
    733         workers=workers,
--> 734         use_multiprocessing=use_multiprocessing)
    735 
    736   def evaluate(self,

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, **kwargs)
    322                 mode=ModeKeys.TRAIN,
    323                 training_context=training_context,
--> 324                 total_epochs=epochs)
    325             cbks.make_logs(model, epoch_logs, training_result, ModeKeys.TRAIN)
    326 

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2.py in run_one_epoch(model, iterator, execution_function, dataset_size, batch_size, strategy, steps_per_epoch, num_samples, mode, training_context, total_epochs)
    121         step=step, mode=mode, size=current_batch_size) as batch_logs:
    122       try:
--> 123         batch_outs = execution_function(iterator)
    124       except (StopIteration, errors.OutOfRangeError):
    125         # TODO(kaftan): File bug about tf function and errors.OutOfRangeError?

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2_utils.py in execution_function(input_fn)
     84     # `numpy` translates Tensors to values in Eager mode.
     85     return nest.map_structure(_non_none_constant_value,
---> 86                               distributed_function(input_fn))
     87 
     88   return execution_function

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in __call__(self, *args, **kwds)
    425     # This is the first call of __call__, so we have to initialize.
    426     initializer_map = object_identity.ObjectIdentityDictionary()
--> 427     self._initialize(args, kwds, add_initializers_to=initializer_map)
    428     if self._created_variables:
    429       try:

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
    368     self._concrete_stateful_fn = (
    369         self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
--> 370             *args, **kwds))
    371 
    372     def invalid_creator_scope(*unused_args, **unused_kwds):

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
   1845     if self.input_signature:
   1846       args, kwargs = None, None
-> 1847     graph_function, _, _ = self._maybe_define_function(args, kwargs)
   1848     return graph_function
   1849 

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _maybe_define_function(self, args, kwargs)
   2145         graph_function = self._function_cache.primary.get(cache_key, None)
   2146         if graph_function is None:
-> 2147           graph_function = self._create_graph_function(args, kwargs)
   2148           self._function_cache.primary[cache_key] = graph_function
   2149         return graph_function, args, kwargs

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
   2036             arg_names=arg_names,
   2037             override_flat_arg_shapes=override_flat_arg_shapes,
-> 2038             capture_by_value=self._capture_by_value),
   2039         self._function_attributes,
   2040         # Tell the ConcreteFunction to clean up its graph once it goes out of

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
    913                                           converted_func)
    914 
--> 915       func_outputs = python_func(*func_args, **func_kwargs)
    916 
    917       # invariant: `func_outputs` contains only Tensors, CompositeTensors,

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in wrapped_fn(*args, **kwds)
    318         # __wrapped__ allows AutoGraph to swap in a converted function. We give
    319         # the function a weak reference to itself to avoid a reference cycle.
--> 320         return weak_wrapped_fn().__wrapped__(*args, **kwds)
    321     weak_wrapped_fn = weakref.ref(wrapped_fn)
    322 

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2_utils.py in distributed_function(input_iterator)
     64     """A single step of the distributed execution across replicas."""
     65     x, y, sample_weights = _prepare_feed_values(
---> 66         model, input_iterator, mode)
     67     # Call `Model.{train,test,predict}_on_batch` on every replica passing
     68     # PerReplicas as arguments.  On every replica inside this call, each

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2_utils.py in _prepare_feed_values(model, inputs, mode)
    110     for inputs will always be wrapped in lists.
    111   """
--> 112   inputs, targets, sample_weights = _get_input_from_iterator(inputs)
    113 
    114   # When the inputs are dict, then we want to flatten it in the same order as

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_v2_utils.py in _get_input_from_iterator(iterator)
    147   # Validate that all the elements in x and y are of the same type and shape.
    148   dist_utils.validate_distributed_dataset_inputs(
--> 149       distribution_strategy_context.get_strategy(), x, y, sample_weights)
    150   return x, y, sample_weights
    151 

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in validate_distributed_dataset_inputs(distribution_strategy, x, y, sample_weights)
    306   # If each element of x and y are not tensors, we cannot standardize and
    307   # validate the input and targets.
--> 308   x_values_list = validate_per_replica_inputs(distribution_strategy, x)
    309 
    310   if y is not None:

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in validate_per_replica_inputs(distribution_strategy, x)
    354     if not context.executing_eagerly():
    355       # Validate that the shape and dtype of all the elements in x are the same.
--> 356       validate_all_tensor_shapes(x, x_values)
    357     validate_all_tensor_types(x, x_values)
    358 

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/distribute/distributed_training_utils.py in validate_all_tensor_shapes(x, x_values)
    371 def validate_all_tensor_shapes(x, x_values):
    372   # Validate that the shape of all the elements in x have the same shape
--> 373   x_shape = x_values[0].shape.as_list()
    374   for i in range(1, len(x_values)):
    375     if x_shape != x_values[i].shape.as_list():

/usr/local/Cellar/python3/3.6.4_2/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/framework/tensor_shape.py in as_list(self)
   1169     """
   1170     if self._dims is None:
-> 1171       raise ValueError("as_list() is not defined on an unknown TensorShape.")
   1172     return [dim.value for dim in self._dims]
   1173 

ValueError: as_list() is not defined on an unknown TensorShape.