InvalidArgumentError: indices[24,0] = 335 is not in [0, 304) [[{{node user-embedding-mlp_1/GatherV2}}]]

Question

I am using tensorflow 1.15 and keras 2.1.2 with python 3.7 This is a multilayer perceptron code for collaborative filtering. Model was already built and there was no error in model summary. But when getting epochs and accuracy below error are getting. I have included my model code and the accuracy code with here.

latent_dim = 10

*# Define inputs*
article_input = Input(shape=[1],name='article-input')
user_input = Input(shape=[1], name='user-input')

*# MLP Embeddings*
article_embedding_mlp = Embedding(num_article + 1, latent_dim, name='article-embedding-mlp')(article_input)
article_vec_mlp = Flatten(name='flatten-article-mlp')(article_embedding_mlp)

user_embedding_mlp = Embedding(num_user + 1, latent_dim, name='user-embedding-mlp')(user_input)
user_vec_mlp = Flatten(name='flatten-user-mlp')(user_embedding_mlp)

*# MF Embeddings*
article_embedding_mf = Embedding(num_article + 1, latent_dim, name='article-embedding-mf')(article_input)
article_vec_mf = Flatten(name='flatten-article-mf')(article_embedding_mf)

user_embedding_mf = Embedding(num_user + 1, latent_dim, name='user-embedding-mf')(user_input)
user_vec_mf = Flatten(name='flatten-user-mf')(user_embedding_mf)

*# MLP layers*
concat = merge([article_vec_mlp, user_vec_mlp], mode='concat', name='concat')
concat_dropout = Dropout(0.2)(concat)
fc_1 = Dense(100, name='fcs-1', activation='relu')(concat_dropout)
fc_1_bn = BatchNormalization(name='batch-norm-1s')(fc_1)
fc_1_dropout = Dropout(0.2)(fc_1_bn)
fc_2 = Dense(50, name='fcs-2', activation='relu')(fc_1_dropout)
fc_2_bn = BatchNormalization(name='batch-norm-2s')(fc_2)
fc_2_dropout = Dropout(0.2)(fc_2_bn)

*# Prediction from both layers*
pred_mlp = Dense(10, name='pred-mlp', activation='relu')(fc_2_dropout)
pred_mf = merge([article_vec_mf, article_vec_mf], mode='dot', name='pred-mf')
combine_mlp_mf = merge([pred_mf, pred_mlp], mode='concat', name='combine-mlp-mf')

result = Dense(1, name='result', activation='relu')(combine_mlp_mf)

model = Model([article_input, user_input], result)
model.compile(optimizer='rmsprop', loss='mean_squared_error')

model.summary()

#Train the Model

history = model.fit([train.id, train.user_id], train.user_like, nb_epoch=3)
pd.Series(history.history['loss']).plot(logy=True)
plt.xlabel("Epoch")
plt.ylabel("Train Error")
plt.show()

y_hat = np.round(model.predict([test.id, test.user_id]), decimals=2)
y_true = test.user_like
mean_absolute_error(y_true, y_hat)

And below errors are what i am getting. Can I have a solution for my collaborative filtering one?

InvalidArgumentError                      Traceback (most recent call last)
E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _do_call(self, fn, *args)
   1364     try:
-> 1365       return fn(*args)
   1366     except errors.OpError as e:

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1349       return self._call_tf_sessionrun(options, feed_dict, fetch_list,
-> 1350                                       target_list, run_metadata)
   1351 

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1442                                             fetch_list, target_list,
-> 1443                                             run_metadata)
   1444 

InvalidArgumentError: indices[24,0] = 335 is not in [0, 304)
     [[{{node user-embedding-mlp_1/GatherV2}}]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-13-1444472fcfba> in <module>
----> 1 history = model.fit([train.id, train.user_id], train.user_like, nb_epoch=3)
      2 pd.Series(history.history['loss']).plot(logy=True)
      3 plt.xlabel("Epoch")
      4 plt.ylabel("Train Error")
      5 plt.show()

E:\My\Ananconda\envs\tensor\lib\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, **kwargs)
   1655                               initial_epoch=initial_epoch,
   1656                               steps_per_epoch=steps_per_epoch,
-> 1657                               validation_steps=validation_steps)
   1658 
   1659     def evaluate(self, x=None, y=None,

E:\My\Ananconda\envs\tensor\lib\site-packages\keras\engine\training.py in _fit_loop(self, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
   1211                     batch_logs['size'] = len(batch_ids)
   1212                     callbacks.on_batch_begin(batch_index, batch_logs)
-> 1213                     outs = f(ins_batch)
   1214                     if not isinstance(outs, list):
   1215                         outs = [outs]

E:\My\Ananconda\envs\tensor\lib\site-packages\keras\backend\tensorflow_backend.py in __call__(self, inputs)
   2355         session = get_session()
   2356         updated = session.run(fetches=fetches, feed_dict=feed_dict,
-> 2357                               **self.session_kwargs)
   2358         return updated[:len(self.outputs)]
   2359 

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
    954     try:
    955       result = self._run(None, fetches, feed_dict, options_ptr,
--> 956                          run_metadata_ptr)
    957       if run_metadata:
    958         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1178     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1179       results = self._do_run(handle, final_targets, final_fetches,
-> 1180                              feed_dict_tensor, options, run_metadata)
   1181     else:
   1182       results = []

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1357     if handle is None:
   1358       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1359                            run_metadata)
   1360     else:
   1361       return self._do_call(_prun_fn, handle, feeds, fetches)

E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\client\session.py in _do_call(self, fn, *args)
   1382                     '\nsession_config.graph_options.rewrite_options.'
   1383                     'disable_meta_optimizer = True')
-> 1384       raise type(e)(node_def, op, message)
   1385 
   1386   def _extend_graph(self):

InvalidArgumentError: indices[24,0] = 335 is not in [0, 304)
     [[node user-embedding-mlp_1/GatherV2 (defined at E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\framework\ops.py:1748) ]]

Original stack trace for 'user-embedding-mlp_1/GatherV2':
  File "E:\My\Ananconda\envs\tensor\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "E:\My\Ananconda\envs\tensor\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\traitlets\config\application.py", line 664, in launch_instance
    app.start()
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\kernelapp.py", line 583, in start
    self.io_loop.start()
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\platform\asyncio.py", line 149, in start
    self.asyncio_loop.run_forever()
  File "E:\My\Ananconda\envs\tensor\lib\asyncio\base_events.py", line 442, in run_forever
    self._run_once()
  File "E:\My\Ananconda\envs\tensor\lib\asyncio\base_events.py", line 1462, in _run_once
    handle._run()
  File "E:\My\Ananconda\envs\tensor\lib\asyncio\events.py", line 145, in _run
    self._callback(*self._args)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
    lambda f: self._run_callback(functools.partial(callback, future))
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
    ret = callback()
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\gen.py", line 787, in inner
    self.run()
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\gen.py", line 748, in run
    yielded = self.gen.send(value)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\kernelbase.py", line 361, in process_one
    yield gen.maybe_future(dispatch(*args))
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\kernelbase.py", line 268, in dispatch_shell
    yield gen.maybe_future(handler(stream, idents, msg))
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\kernelbase.py", line 541, in execute_request
    user_expressions, allow_stdin,
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tornado\gen.py", line 209, in wrapper
    yielded = next(result)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\ipkernel.py", line 300, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\interactiveshell.py", line 2858, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\interactiveshell.py", line 2886, in _run_cell
    return runner(coro)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
    coro.send(None)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\interactiveshell.py", line 3063, in run_cell_async
    interactivity=interactivity, compiler=compiler, result=result)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\interactiveshell.py", line 3254, in run_ast_nodes
    if (await self.run_code(code, result,  async_=asy)):
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\IPython\core\interactiveshell.py", line 3331, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-10-fe3553834f55>", line 11, in <module>
    user_embedding_mlp = Embedding(num_user + 1, latent_dim, name='user-embedding-mlp')(user_input)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\keras\engine\topology.py", line 603, in __call__
    output = self.call(inputs, **kwargs)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\keras\layers\embeddings.py", line 134, in call
    out = K.gather(self.embeddings, inputs)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\keras\backend\tensorflow_backend.py", line 1193, in gather
    return tf.gather(reference, indices)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\util\dispatch.py", line 180, in wrapper
    return target(*args, **kwargs)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\ops\array_ops.py", line 3956, in gather
    params, indices, axis, name=name)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\ops\gen_array_ops.py", line 4082, in gather_v2
    batch_dims=batch_dims, name=name)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\framework\op_def_library.py", line 794, in _apply_op_helper
    op_def=op_def)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\util\deprecation.py", line 507, in new_func
    return func(*args, **kwargs)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3357, in create_op
    attrs, op_def, compute_device)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\framework\ops.py", line 3426, in _create_op_internal
    op_def=op_def)
  File "E:\My\Ananconda\envs\tensor\lib\site-packages\tensorflow_core\python\framework\ops.py", line 1748, in __init__
    self._traceback = tf_stack.extract_stack()

Answer 1

redefine num_user and num_article in this way....

num_user = int(articles.user_id.max())
num_article = int(articles.id.max())