dense_2错误:检查目标时出错:要求keras具有形状(2，)，但得到形状为(1，)的数组

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

# 创建一个简单的模型
model = Sequential()
model.add(Dense(16, input_shape=(10,), activation='relu'))
model.add(Dense(2, activation='softmax'))

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

# 准备训练数据和目标值
train_data = ...
train_labels = ...

# 检查数据集形状
print(train_data.shape)  # (样本数量, 特征数量)
print(train_labels.shape)  # (样本数量,)

# 如果目标形状不匹配，可以进行处理
# train_labels = tf.keras.utils.to_categorical(train_labels, num_classes=2)

# 训练模型
model.fit(train_data, train_labels, epochs=10, batch_size=32)