模型错误: Layer model_1需要%1个输入，但它收到了%2个输入张量

import numpy as np

# 假设模型期望的输入维度是 (batch_size, height, width, channels)
expected_shape = (batch_size, height, width, channels)

# 检查输入数据的维度
input_data = ...  # 你的输入数据
if input_data.shape != expected_shape:
    input_data = np.reshape(input_data, expected_shape)

# 假设模型期望的输入数量是 batch_size
batch_size = ...  # 你的批次大小

# 确保输入数据的数量与批次大小一致
input_data = ...  # 你的输入数据
if len(input_data) != batch_size:
    raise ValueError(f"Expected {batch_size} input samples, but got {len(input_data)}")

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D

model = Sequential()
model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(height, width, channels)))
model.add(Dense(64, activation='relu'))