keras error

ValueError                                Traceback (most recent call last)
~\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    490                 as_ref=input_arg.is_ref,
--> 491                 preferred_dtype=default_dtype)
    492           except TypeError as err:

~\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype)
    703         if ret is None:
--> 704           ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    705

~\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
    112   _ = as_ref
--> 113   return constant(v, dtype=dtype, name=name)
    114

~\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in constant(value, dtype, shape, name, verify_shape)
    101   tensor_value.tensor.CopyFrom(
--> 102       tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
    103   dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype)

~\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape)
    359     if values is None:
--> 360       raise ValueError("None values not supported.")
    361     # if dtype is provided, forces numpy array to be the type

ValueError: None values not supported.

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
~\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    504               observed = ops.internal_convert_to_tensor(
--> 505                   values, as_ref=input_arg.is_ref).dtype.name
    506             except ValueError as err:

~\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype)
    703         if ret is None:
--> 704           ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    705

~\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
    112   _ = as_ref
--> 113   return constant(v, dtype=dtype, name=name)
    114

~\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in constant(value, dtype, shape, name, verify_shape)
    101   tensor_value.tensor.CopyFrom(
--> 102       tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
    103   dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype)

~\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape)
    359     if values is None:
--> 360       raise ValueError("None values not supported.")
    361     # if dtype is provided, forces numpy array to be the type

ValueError: None values not supported.

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-51-d775b4f78c50> in <module>()
     99
    100     train_err, valid_err, train_eff, valid_eff = run_epoch( recc_model,
--> 101             train_iter, valid_iter, tot_size)
    102     #train_loss.append(train_err)
    103     #valid_loss.append(valid_err)

<ipython-input-51-d775b4f78c50> in run_epoch(model, train_iter, valid_iter, tot_size)
     34     for train, valid in zip(train_iter, valid_iter):
     35         # Training data.
---> 36         errors, num_triplets, correct = run_batch(model, train)
     37         tot += num_triplets
     38         train_seq_len += num_triplets

<ipython-input-51-d775b4f78c50> in run_batch(model, iterator, isTrain)
     10         targets = to_categorical(targets, num_items+1)
     11         if isTrain:
---> 12             loss, metrics = model.train_on_batch(inputs, targets)
     13         else:
     14             loss, metrics = model.test_on_batch(inputs, targets)

~\Anaconda3\lib\site-packages\keras\engine\training.py in train_on_batch(self, x, y, sample_weight, class_weight)
   1836         else:
   1837             ins = x + y + sample_weights
-> 1838         self._make_train_function()
   1839         outputs = self.train_function(ins)
   1840         if len(outputs) == 1:

~\Anaconda3\lib\site-packages\keras\engine\training.py in _make_train_function(self)
    988                     training_updates = self.optimizer.get_updates(
    989                         params=self._collected_trainable_weights,
--> 990                         loss=self.total_loss)
    991                 updates = self.updates + training_updates
    992                 # Gets loss and metrics. Updates weights at each call.

~\Anaconda3\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs)
     85                 warnings.warn('Update your `' + object_name +
     86                               '` call to the Keras 2 API: ' + signature, stacklevel=2)
---> 87             return func(*args, **kwargs)
     88         wrapper._original_function = func
     89         return wrapper

~\Anaconda3\lib\site-packages\keras\optimizers.py in get_updates(self, loss, params)
    235         for p, g, a in zip(params, grads, accumulators):
    236             # update accumulator
--> 237             new_a = self.rho * a + (1. - self.rho) * K.square(g)
    238             self.updates.append(K.update(a, new_a))
    239             new_p = p - lr * g / (K.sqrt(new_a) + self.epsilon)

~\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py in square(x)
   1415         A tensor.
   1416     """
-> 1417     return tf.square(x)
   1418
   1419

~\Anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py in square(x, name)
    410           indices=x.indices, values=x_square, dense_shape=x.dense_shape)
    411     else:
--> 412       return gen_math_ops.square(x, name=name)
    413
    414

~\Anaconda3\lib\site-packages\tensorflow\python\ops\gen_math_ops.py in square(x, name)
   2583     A `Tensor`. Has the same type as `x`.
   2584   """
-> 2585   result = _op_def_lib.apply_op("Square", x=x, name=name)
   2586   return result
   2587

~\Anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    507               raise ValueError(
    508                   "Tried to convert '%s' to a tensor and failed. Error: %s" %
--> 509                   (input_name, err))
    510             prefix = ("Input '%s' of '%s' Op has type %s that does not match" %
    511                       (input_name, op_type_name, observed))

ValueError: Tried to convert 'x' to a tensor and failed. Error: None values not supported.