Converting sparse IndexedSlices to a dense Tensor of unknown shape.

[emad-adly-abdelzaher]

When running the training I am getting the following error messages

/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/indexed_slices.py:433: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory. "Converting sparse IndexedSlices to a dense Tensor of unknown shape. " ValueError Traceback (most recent call last) in 2 model_log = model.fit(x_train, y_train, validation_data=(x_val, y_val), 3 epochs=200, batch_size=128, ----> 4 callbacks=[tensorboard, model_checkpoints]) 5 6 pandas.DataFrame(model_log.history).to_csv("history-balance.csv") ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/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) 1211 else: 1212 fit_inputs = x + y + sample_weights -> 1213 self._make_train_function() 1214 fit_function = self.train_function 1215 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/keras/engine/training.py in _make_train_function(self) 314 training_updates = self.optimizer.get_updates( 315 params=self._collected_trainable_weights, --> 316 loss=self.total_loss) 317 updates = self.updates + training_updates 318 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/keras/legacy/interfaces.py in wrapper(*args, **kwargs) 89 warnings.warn('Update your `' + object_name + '` call to the ' + 90 'Keras 2 API: ' + signature, stacklevel=2) ---> 91 return func(*args, **kwargs) 92 wrapper._original_function = func 93 return wrapper ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in symbolic_fn_wrapper(*args, **kwargs) 73 if _SYMBOLIC_SCOPE.value: 74 with get_graph().as_default(): ---> 75 return func(*args, **kwargs) 76 else: 77 return func(*args, **kwargs) ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/keras/optimizers.py in get_updates(self, loss, params) 433 434 # use the new accumulator and the *old* delta_accumulator --> 435 update = g * K.sqrt(d_a + self.epsilon) / K.sqrt(new_a + self.epsilon) 436 new_p = p - lr * update 437 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/ops/variables.py in _run_op(a, *args, **kwargs) 1080 def _run_op(a, *args, **kwargs): 1081 # pylint: disable=protected-access -> 1082 return tensor_oper(a.value(), *args, **kwargs) 1083 1084 functools.update_wrapper(_run_op, tensor_oper) ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/ops/math_ops.py in binary_op_wrapper(x, y) 904 try: 905 y = ops.convert_to_tensor_v2( --> 906 y, dtype_hint=x.dtype.base_dtype, name="y") 907 except TypeError: 908 # If the RHS is not a tensor, it might be a tensor aware object ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py in convert_to_tensor_v2(value, dtype, dtype_hint, name) 1254 name=name, 1255 preferred_dtype=dtype_hint, -> 1256 as_ref=False) 1257 1258 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types) 1312 1313 if ret is None: -> 1314 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) 1315 1316 if ret is NotImplemented: ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref) 315 as_ref=False): 316 _ = as_ref --> 317 return constant(v, dtype=dtype, name=name) 318 319 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py in constant(value, dtype, shape, name) 256 """ 257 return _constant_impl(value, dtype, shape, name, verify_shape=False, --> 258 allow_broadcast=True) 259 260 ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast) 294 tensor_util.make_tensor_proto( 295 value, dtype=dtype, shape=shape, verify_shape=verify_shape, --> 296 allow_broadcast=allow_broadcast)) 297 dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype) 298 const_tensor = g._create_op_internal( # pylint: disable=protected-access ~/PycharmProjects/text-emotion-classification/venv/lib/python3.6/site-packages/tensorflow_core/python/framework/tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape, allow_broadcast) 437 else: 438 if values is None: --> 439 raise ValueError("None values not supported.") 440 # if dtype is provided, forces numpy array to be the type 441 # provided if possible. ValueError: None values not supported.