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ValueError: 没有为任何变量提供梯度:['conv2d/kernel:0', 'conv2d/bias:0', 'conv2d_1/kernel:0', 'conv2d_1/bias:0',

系统信息 Colab tensorflow 2.2.0

描述当前的行为:当我尝试解决我自己的数据问题时遇到了这个错误,即多标签语义分割。

下面是代码

import tensorflow as tf
import tensorflow.keras.backend as K

IMG_WIDTH = 512
IMG_HEIGHT = 512
IMG_CHANNELS = 3

# batch_shape=(512,512,3)
# inputs = Input(batch_shape=(4, 512, 512, 3))
#Build the model
inputs = tf.keras.layers.Input((IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS))
#s = tf.keras.layers.Lambda(lambda x: x / 255)(inputs)

#Contraction path
c1 = tf.keras.layers.Conv2D(16, (3, 3), activation='relu', kernel_initializer='he_normal', padding='same')(inputs)
c1 = tf.keras.layers.Dropout(0.1)(c1)
c1 = tf.keras.layers.Conv2D(16, (3, 3), activation='relu', kernel_initializer='he_normal', padding='same')(c1)
p1 = tf.keras.layers.MaxPooling2D((2, 2))(c1)

c2 = tf.keras.layers.Conv2D(32, (3, 3), activation='relu', kernel_initializer='he_normal', padding='same')(p1) …
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keras tensorflow cnn

4
推荐指数
1
解决办法
3844
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标签 统计

cnn ×1

keras ×1

tensorflow ×1