tensorflow卷积层&池化层

卷积层

tensorflow提供了tf.nn.conv2d()和tf.nn.bias_add()函数来创建卷积层
下面示例用tf.nn.conv2d()函数来创建一个卷积层

# Output depth
k_output = 64

# Image Properties
image_width = 10
image_height = 10
color_channels = 3

# Convolution filter
filter_size_width = 5
filter_size_height = 5

# Input/Image
input = tf.placeholder(
    tf.float32,
    shape=[None, image_height, image_width, color_channels])

# Weight and bias
weight = tf.Variable(tf.truncated_normal(
    [filter_size_height, filter_size_width, color_channels, k_output]))
bias = tf.Variable(tf.zeros(k_output))

# Apply Convolution
conv_layer = tf.nn.conv2d(input=input,
                          filter=weights,
                          strides=[1, 2, 2, 1],
                          padding='SAME')
# Add bias
conv_layer = tf.nn.bias_add(conv_layer, bias)
# Apply activation function
conv_layer = tf.nn.relu(conv_layer)

weights作为滤波器，[1, 2, 2, 1]作为strides。TensorFlow 对每一个 input