tf_util.py 文件源码

def avg_pool3d(inputs,
               kernel_size,
               scope,
               stride=[2, 2, 2],
               padding='VALID'):
  """ 3D avg pooling.

  Args:
    inputs: 5-D tensor BxDxHxWxC
    kernel_size: a list of 3 ints
    stride: a list of 3 ints

  Returns:
    Variable tensor
  """
  with tf.variable_scope(scope) as sc:
    kernel_d, kernel_h, kernel_w = kernel_size
    stride_d, stride_h, stride_w = stride
    outputs = tf.nn.avg_pool3d(inputs,
                               ksize=[1, kernel_d, kernel_h, kernel_w, 1],
                               strides=[1, stride_d, stride_h, stride_w, 1],
                               padding=padding,
                               name=sc.name)
    return outputs