kerasでIndexError: tuple index out of rangeが出てしまったので解決したい。

Question

実現したいこと

kerasでIndexError: tuple index out of rangeが出てしまったので解決したい。

前提

pythonのkerasで画像認識を学習中に前述のエラーが出てしまいました。
kerasを始めたばかりで、調べてみても具体的な原因や解決方法がわかりませんでした。

発生している問題・エラーメッセージ

2023-11-22 09:12:44.959479: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE SSE2 SSE3 SSE4.1 SSE4.2 AVX AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
  File "c:\Users\user\Documents\AI\ai_test2.py", line 54, in <module>
    model.fit(x, y, epochs=1)
  File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\utils\traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Users\user~1\AppData\Local\Temp\__autograph_generated_file5q6yansm.py", line 15, in tf__train_function
    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
    ^^^^^
TypeError: in user code:

    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\engine\training.py", line 1377, in train_function  *       
        return step_function(self, iterator)
    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\engine\training.py", line 1360, in step_function  **       
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\engine\training.py", line 1349, in run_step  **
        outputs = model.train_step(data)
    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\engine\training.py", line 1126, in train_step
        y_pred = self(x, training=True)
    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\utils\traceback_utils.py", line 70, in error_handler       
        raise e.with_traceback(filtered_tb) from None
    File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\engine\base_layer.py", line 2800, in _name_scope
        name_scope += "/"

    TypeError: unsupported operand type(s) for +=: 'Dense' and 'str'

PS C:\Users\user\Documents\AI> & C:/Users/user/AppData/Local/Programs/Python/Python311/python.exe c:/Users/user/Documents/AI/ai_test2.py
2023-11-22 09:13:06.603065: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE SSE2 SSE3 SSE4.1 SSE4.2 AVX AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
  File "c:\Users\user\Documents\AI\ai_test2.py", line 54, in <module>
    model.fit(x, y, epochs=1)
  File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\src\utils\traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Users\user\AppData\Local\Programs\Python\Python311\Lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 959, in __getitem__ 
    return self._dims[key]
           ~~~~~~~~~~^^^^^
IndexError: tuple index out of range

該当のソースコード

import keras
from keras.models import Sequential
from keras.layers import Dense
from keras.preprocessing.image import load_img
import numpy as np
import glob

# 'test_data/train/'の中のrock, paper, scissorsディレクトリの中に
# 各5枚ずつ画像が入っている

rps = ['rock/', 'paper/', 'scissors/']

BASE_DIR = 'test_data/train/'

# 学習用データを格納
x = []
# 学習用データに対応するラベルを格納
y = []

# rock, paper, scissorsのラベルはそれぞれ0, 1, 2
for idx, name in enumerate(rps):
    path = BASE_DIR + name + '*.jpg'
    files = glob.glob(path)
    for file in files:
        image = load_img(file)
        image = np.asarray(image)/255.0
        x.append(image)
        y.append(np.asarray(idx))

# モデルを作成
model = Sequential(
    Dense(784, input_shape=(300, 300), activation='relu'),
    Dense(3, activation='softmax')
)

model.compile(
    optimizer='adam',
    loss='categorical_crossentropy',
    metrics=['accuracy']
)

# 学習中なのでepochsは1
model.fit(x, y, epochs=1)

model.summary()

試したこと

範囲外を指定している可能を考慮し、
model.fit(x[0:15], y[0:15], epochs=1)
としてみたが以前同じ結果だった。

補足情報（FW/ツールのバージョンなど）

>>> tensorflow.__version__
'2.14.0'
>>> keras.__version__ 
'2.14.0'