Layer model_1 expects 2 input(s), but it received 3 input tensors. Inputs received

Question

前提・実現したいこと

ubuntu20.04
python3.8
tensorflow == 2.4.0
を使用しています。

現在、画像からキャプションを生成するために画像データを学習しているところですが下記のようなエラーが発生してしまいました。
形状が違うようなエラーだとは思いますが私自身詳しくなくどこを修正すればよいのか検討がつかない状態です。また、あるサイトにより、model→Modelに変え実行してもエラーが出てしまっています。
申し訳ございませんがご教示いただけないでしょうか
よろしくお願い致します。

発生している問題・エラーメッセージ

/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:1844: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.
  warnings.warn('`Model.fit_generator` is deprecated and '
Traceback (most recent call last):
  File "1.py", line 337, in <module>
    model.fit_generator(generator,epochs=1,steps_per_epoch=steps,verbose=1)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1847, in fit_generator
    return self.fit(
  File "/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit
    tmp_logs = self.train_function(iterator)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
    result = self._call(*args, **kwds)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 871, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 725, in _initialize
    self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2969, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3361, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3196, in _create_graph_function
    func_graph_module.func_graph_from_py_func(
  File "/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 990, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 634, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 977, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

  /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:805 train_function  *
        return step_function(self, iterator)
    /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:795 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:1259 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    /.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:2730 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    /.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:3417 _call_for_each_replica
        return fn(*args, **kwargs)
    /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:788 run_step  **
        outputs = model.train_step(data)
    /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:754 train_step
        y_pred = self(x, training=True)
   /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:998 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
    /.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/input_spec.py:204 assert_input_compatibility
        raise ValueError('Layer ' + layer_name + ' expects ' +

    ValueError: Layer model_1 expects 2 input(s), but it received 3 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, None) dtype=float32>, <tf.Tensor 'IteratorGetNext:1' shape=(None, None) dtype=int32>, <tf.Tensor 'IteratorGetNext:2' shape=(None, None) dtype=float32>]

該当のソースコード

def data_generator(descriptions, photos, tokenizer, max_length):
	# loop for ever over images
	while 1:
		for key, desc_list in descriptions.items():
			# retrieve the photo feature
			photo = photos[key][0]
			in_img, in_seq, out_word = create_sequences(tokenizer, max_length, desc_list, photo)
			yield [[in_img, in_seq], out_word]

# load training dataset (6K)
filename = 'Flickr_8k.trainImages.txt'
train = load_set(filename)
print('Dataset: %d' % len(train))
# descriptions
train_descriptions = load_clean_descriptions('descriptions.txt', train)
print('Descriptions: train=%d' % len(train_descriptions))
# photo features
train_features = load_photo_features('features.pkl', train)
print('Photos: train=%d' % len(train_features))
# prepare tokenizer
tokenizer = create_tokenizer(train_descriptions)

vocab_size = len(tokenizer.word_index) + 1
print('Vocabulary Size: %d' % vocab_size)
# determine the maximum sequence length
max_length = max_length1(train_descriptions)
print('Description Length: %d' % max_length)
# train the model
model = define_model(vocab_size, max_length)
# train the model, run epochs manually and save after each epoch
epochs = 20
steps = len(train_descriptions)
for i in range(epochs):
    
    generator =data_generator(train_descriptions,train_features,tokenizer,max_length)
    model.fit_generator(generator,epochs=1,steps_per_epoch=steps,verbose=1)
    #Model.fit_generator(generator,epochs=1,steps_per_epoch=steps,verbose=1)
    model.save('model_' + str(i) + '.h5')