我的意思是上面的代码不完整继续写下去
时间: 2024-04-12 20:29:33 浏览: 21
非常抱歉,下面是继续写下去的代码:
```python
input_tensor = tf.keras.layers.Conv2D(filters3, (1, 1), strides=strides, name=conv_name_base + '1')(input_tensor)
input_tensor = tf.keras.layers.BatchNormalization(name=bn_name_base + '1')(input_tensor)
x = tf.keras.layers.add([x, input_tensor])
x = tf.keras.layers.Activation('relu')(x)
return x
def ResNet50(input_shape=(224, 224, 3), classes=1000):
input_tensor = tf.keras.Input(shape=input_shape)
x = tf.keras.layers.ZeroPadding2D((3, 3))(input_tensor)
x = tf.keras.layers.Conv2D(64, (7, 7), strides=(2, 2), name='conv1')(x)
x = tf.keras.layers.BatchNormalization(name='bn_conv1')(x)
x = tf.keras.layers.Activation('relu')(x)
x = tf.keras.layers.MaxPooling2D((3, 3), strides=(2, 2))(x)
x = conv_block(x, 3, [64, 64, 256], stage=2, block='a', strides=(1, 1))
x = identity_block(x, 3, [64, 64, 256], stage=2, block='b')
x = identity_block(x, 3, [64, 64, 256], stage=2, block='c')
x = conv_block(x, 3, [128, 128, 512], stage=3, block='a')
x = identity_block(x, 3, [128, 128, 512], stage=