model.py 文件源码

def conv2d_fixed_padding(self, inputs, filters, kernel_size, strides, name=None, relu=True):
        if strides > 1:
            inputs = self.fixed_padding(inputs, kernel_size)

        inputs = tf.layers.conv2d(
            inputs=inputs, filters=filters, kernel_size=kernel_size, strides=strides,
            padding=('SAME' if strides == 1 else 'VALID'), use_bias=False,
            kernel_initializer=tf.variance_scaling_initializer(), name=name)
        if relu:
            return self.batch_norm_relu(inputs, name)
        else:
            return self.batch_norm(inputs, name)