ValueError in the first epoch ending of tensorflow training

im trying to read and solve all the francois’s “deep learning with python” book (page 253 chapter 7), and there i found this arquitecture

import keras
from keras import layers
from keras.datasets import imdb
from keras.preprocessing import sequence
max_features = 2000
max_len = 500
(x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features)
x_train = sequence.pad_sequences(x_train, maxlen=max_len)
x_test = sequence.pad_sequences(x_test, maxlen=max_len)
model = keras.models.Sequential()
model.add(layers.Embedding(max_features, 128, input_length=max_len, name='embed'))
model.add(layers.Conv1D(32, 7, activation='relu'))
model.add(layers.MaxPooling1D(5))
model.add(layers.Conv1D(32, 7, activation='relu'))
model.add(layers.GlobalMaxPooling1D())
model.add(layers.Dense(1))
model.summary()
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['acc'])

callbacks = [
keras.callbacks.TensorBoard(
log_dir='my_log_dir',
histogram_freq=1,
embeddings_freq=1,
)
]
history = model.fit(x_train, y_train,
epochs=20,
batch_size=128,
validation_split=0.2,
callbacks=callbacks)

now when i try to train in the ending of the first epoch i get this error(actually it freze on the last step of the epoch i thing in the validation proces)

Instructions for updating:
Deprecated in favor of operator or tf.math.divide.
Train on 20000 samples, validate on 5000 samples
Epoch 1/20
20000/20000 [==============================] - 52s 3ms/step - loss: 0.8421 - acc: 0.5126 - val_loss: 0.6876 - val_acc: 0.5532
ValueError                                Traceback (most recent call last)
    <ipython-input-5-1a0c8832065d> in <module>
          1 callbacks = [keras.callbacks.TensorBoard(log_dir='my_log_dir', histogram_freq=1, embeddings_freq=1,)]
    ----> 2 history = model.fit(x_train, y_train, epochs=20, batch_size=512, validation_split=0.2, callbacks=callbacks)

    ~Anaconda3envstensorflowlibsite-packageskerasenginetraining.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, **kwargs)
       1037                                         initial_epoch=initial_epoch,
       1038                                         steps_per_epoch=steps_per_epoch,
    -> 1039                                         validation_steps=validation_steps)
       1040 
       1041     def evaluate(self, x=None, y=None,

    ~Anaconda3envstensorflowlibsite-packageskerasenginetraining_arrays.py in fit_loop(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
        215                         for l, o in zip(out_labels, val_outs):
        216                             epoch_logs['val_' + l] = o
    --> 217         callbacks.on_epoch_end(epoch, epoch_logs)
        218         if callback_model.stop_training:
        219             break

    ~Anaconda3envstensorflowlibsite-packageskerascallbacks.py in on_epoch_end(self, epoch, logs)
         77         logs = logs or {}
         78         for callback in self.callbacks:
    ---> 79             callback.on_epoch_end(epoch, logs)
         80 
         81     def on_batch_begin(self, batch, logs=None):

    ~Anaconda3envstensorflowlibsite-packageskerascallbacks.py in on_epoch_end(self, epoch, logs)
        913                              "provided, and cannot be a generator.")
        914         if self.embeddings_data is None and self.embeddings_freq:
    --> 915             raise ValueError("To visualize embeddings, embeddings_data must "
        916                              "be provided.")
        917         if self.validation_data and self.histogram_freq:

    ValueError: To visualize embeddings, embeddings_data must be provided.

i cant figure out what could be the error U.U where do i need to set the embeddings_data? thank you in advance guys!

edit:

now changing the callback to

callbacks = [keras.callbacks.TensorBoard(log_dir='my_log_dir', histogram_freq=1, embeddings_freq=1, embeddings_data=x_test)]

i get this new error

    WARNING:tensorflow:From C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonopsmath_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
WARNING:tensorflow:From C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonopsmath_grad.py:102: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Deprecated in favor of operator or tf.math.divide.
Train on 17500 samples, validate on 7500 samples
Epoch 1/20

---------------------------------------------------------------------------
ResourceExhaustedError                    Traceback (most recent call last)
~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _do_call(self, fn, *args)
   1333     try:
-> 1334       return fn(*args)
   1335     except errors.OpError as e:

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1318       return self._call_tf_sessionrun(
-> 1319           options, feed_dict, fetch_list, target_list, run_metadata)
   1320 

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1406         self._session, options, feed_dict, fetch_list, target_list,
-> 1407         run_metadata)
   1408 

ResourceExhaustedError: OOM when allocating tensor of shape [25000,64000] and type float
     [[{{node zeros}}]]

During handling of the above exception, another exception occurred:

ResourceExhaustedError                    Traceback (most recent call last)
<ipython-input-2-d7e702b62530> in <module>
      3 callbacks = [keras.callbacks.TensorBoard(log_dir='my_log_dir', histogram_freq=1, embeddings_freq=1, embeddings_data=x_test)]
      4 
----> 5 history = model.fit(x_train, y_train, epochs=20, batch_size=128, validation_split=0.3, callbacks=callbacks)

~Anaconda3envstensorflow_glibsite-packageskerasenginetraining.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, **kwargs)
   1037                                         initial_epoch=initial_epoch,
   1038                                         steps_per_epoch=steps_per_epoch,
-> 1039                                         validation_steps=validation_steps)
   1040 
   1041     def evaluate(self, x=None, y=None,

~Anaconda3envstensorflow_glibsite-packageskerasenginetraining_arrays.py in fit_loop(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
    197                     ins_batch[i] = ins_batch[i].toarray()
    198 
--> 199                 outs = f(ins_batch)
    200                 outs = to_list(outs)
    201                 for l, o in zip(out_labels, outs):

~Anaconda3envstensorflow_glibsite-packageskerasbackendtensorflow_backend.py in __call__(self, inputs)
   2695 
   2696     def __call__(self, inputs):
-> 2697         if hasattr(get_session(), '_make_callable_from_options'):
   2698             if py_any(is_sparse(x) for x in self.inputs):
   2699                 if py_any(is_tensor(x) for x in inputs):

~Anaconda3envstensorflow_glibsite-packageskerasbackendtensorflow_backend.py in get_session()
    204                     v._keras_initialized = True
    205                 if uninitialized_vars:
--> 206                     session.run(tf.variables_initializer(uninitialized_vars))
    207     # hack for list_devices() function.
    208     # list_devices() function is not available under tensorflow r1.3.

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in run(self, fetches, feed_dict, options, run_metadata)
    927     try:
    928       result = self._run(None, fetches, feed_dict, options_ptr,
--> 929                          run_metadata_ptr)
    930       if run_metadata:
    931         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1150     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1151       results = self._do_run(handle, final_targets, final_fetches,
-> 1152                              feed_dict_tensor, options, run_metadata)
   1153     else:
   1154       results = []

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1326     if handle is None:
   1327       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328                            run_metadata)
   1329     else:
   1330       return self._do_call(_prun_fn, handle, feeds, fetches)

~Anaconda3envstensorflow_glibsite-packagestensorflowpythonclientsession.py in _do_call(self, fn, *args)
   1346           pass
   1347       message = error_interpolation.interpolate(message, self._graph)
-> 1348       raise type(e)(node_def, op, message)
   1349 
   1350   def _extend_graph(self):

ResourceExhaustedError: OOM when allocating tensor of shape [25000,64000] and type float
     [[node zeros (defined at C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerascallbacks.py:880) ]]

Caused by op 'zeros', defined at:
  File "C:UsersmimusAnaconda3envstensorflow_glibrunpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "C:UsersmimusAnaconda3envstensorflow_glibrunpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestraitletsconfigapplication.py", line 658, in launch_instance
    app.start()
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelkernelapp.py", line 505, in start
    self.io_loop.start()
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadoplatformasyncio.py", line 148, in start
    self.asyncio_loop.run_forever()
  File "C:UsersmimusAnaconda3envstensorflow_glibasynciobase_events.py", line 539, in run_forever
    self._run_once()
  File "C:UsersmimusAnaconda3envstensorflow_glibasynciobase_events.py", line 1775, in _run_once
    handle._run()
  File "C:UsersmimusAnaconda3envstensorflow_glibasyncioevents.py", line 88, in _run
    self._context.run(self._callback, *self._args)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadoioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadoioloop.py", line 743, in _run_callback
    ret = callback()
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadogen.py", line 781, in inner
    self.run()
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadogen.py", line 742, in run
    yielded = self.gen.send(value)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelkernelbase.py", line 365, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadogen.py", line 209, in wrapper
    yielded = next(result)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelkernelbase.py", line 272, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadogen.py", line 209, in wrapper
    yielded = next(result)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelkernelbase.py", line 542, in execute_request
    user_expressions, allow_stdin,
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestornadogen.py", line 209, in wrapper
    yielded = next(result)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelipkernel.py", line 294, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesipykernelzmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreinteractiveshell.py", line 2848, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreinteractiveshell.py", line 2874, in _run_cell
    return runner(coro)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreasync_helpers.py", line 67, in _pseudo_sync_runner
    coro.send(None)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreinteractiveshell.py", line 3049, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreinteractiveshell.py", line 3214, in run_ast_nodes
    if (yield from self.run_code(code, result)):
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagesIPythoncoreinteractiveshell.py", line 3296, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-d7e702b62530>", line 5, in <module>
    history = model.fit(x_train, y_train, epochs=20, batch_size=128, validation_split=0.3, callbacks=callbacks)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerasenginetraining.py", line 1039, in fit
    validation_steps=validation_steps)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerasenginetraining_arrays.py", line 117, in fit_loop
    callbacks.set_model(callback_model)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerascallbacks.py", line 54, in set_model
    callback.set_model(model)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerascallbacks.py", line 880, in set_model
    embedding = tf.Variable(tf.zeros(shape),
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonopsarray_ops.py", line 1817, in zeros
    output = fill(shape, constant(zero, dtype=dtype), name=name)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonopsgen_array_ops.py", line 3367, in fill
    "Fill", dims=dims, value=value, name=name)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonframeworkop_def_library.py", line 788, in _apply_op_helper
    op_def=op_def)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonutildeprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonframeworkops.py", line 3300, in create_op
    op_def=op_def)
  File "C:UsersmimusAnaconda3envstensorflow_glibsite-packagestensorflowpythonframeworkops.py", line 1801, in __init__
    self._traceback = tf_stack.extract_stack()

ResourceExhaustedError (see above for traceback): OOM when allocating tensor of shape [25000,64000] and type float
     [[node zeros (defined at C:UsersmimusAnaconda3envstensorflow_glibsite-packageskerascallbacks.py:880) ]]