early_stop = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=10)
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy'])

# fit the model
model.fit(X_train,
         y_train,
         epochs=40,
         batch_size=512,
         validation_data=(X_test, y_test),
         verbose=1,
         callbacks=[early_stop]
)

CancelledError                            Traceback (most recent call last)
/var/folders/7t/tgrdz77j2r93smmw74pd9ny40000gn/T/ipykernel_4079/1037202941.py in <module>
      4 
      5 # fit the model
----> 6 model.fit(X_train,
      7          y_train,
      8          epochs=10,

~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_v1.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)
    793 
    794     func = self._select_training_loop(x)
--> 795     return func.fit(
    796         self,
    797         x=x,

~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_arrays_v1.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)
    642       val_x, val_y, val_sample_weights = None, None, None
    643 
--> 644     return fit_loop(
    645         model,
    646         inputs=x,

~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_arrays_v1.py in model_iteration(model, inputs, targets, sample_weights, batch_size, epochs, verbose, callbacks, val_inputs, val_targets, val_sample_weights, shuffle, initial_epoch, steps_per_epoch, validation_steps, validation_freq, mode, validation_in_fit, prepared_feed_values_from_dataset, steps_name, **kwargs)
    378 
    379         # Get outputs.
--> 380         batch_outs = f(ins_batch)
    381         if not isinstance(batch_outs, list):
    382           batch_outs = [batch_outs]

~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/backend.py in __call__(self, inputs)
   4052       self._make_callable(feed_arrays, feed_symbols, symbol_vals, session)
   4053 
-> 4054     fetched = self._callable_fn(*array_vals,
   4055                                 run_metadata=self.run_metadata)
   4056     self._call_fetch_callbacks(fetched[-len(self._fetches):])

~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/client/session.py in __call__(self, *args, **kwargs)
   1478       try:
   1479         run_metadata_ptr = tf_session.TF_NewBuffer() if run_metadata else None
-> 1480         ret = tf_session.TF_SessionRunCallable(self._session._session,
   1481                                                self._handle, args,
   1482                                                run_metadata_ptr)

CancelledError: [_Derived_]RecvAsync is cancelled.
	 [[{{node keras_layer/StatefulPartitionedCall}}]]