在Keras中定义steps_per_epoch

from keras.models import Sequential
from keras.layers import Dense
from keras.utils import Sequence

# 假设我们有一个自定义的数据生成器
class CustomDataGenerator(Sequence):
    def __init__(self, data, batch_size):
        self.data = data
        self.batch_size = batch_size

    def __len__(self):
        return len(self.data) // self.batch_size  # 计算每个epoch的步数

    def __getitem__(self, index):
        batch_data = self.data[index * self.batch_size:(index + 1) * self.batch_size]
        # 对batch_data进行处理，返回X和y
        return batch_data, batch_data  # 假设返回的数据和标签相同

# 创建模型
model = Sequential()
model.add(Dense(10, input_shape=(784,)))
model.add(Dense(10, activation='softmax'))

# 编译模型
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

# 创建数据生成器实例
data_generator = CustomDataGenerator(data, batch_size=32)

# 训练模型，使用steps_per_epoch参数
model.fit(data_generator, epochs=10, steps_per_epoch=len(data_generator))