tf.raw_ops.AvgPoolGrad

Computes gradients of the average pooling function.

tf.raw_ops.AvgPoolGrad(
    orig_input_shape, grad, ksize, strides, padding, data_format='NHWC', name=None
)

Args:

  • orig_input_shape: A Tensor of type int32. 1-D. Shape of the original input to avg_pool.
  • grad: A Tensor. Must be one of the following types: half, bfloat16, float32, float64. 4-D with shape [batch, height, width, channels]. Gradients w.r.t. the output of avg_pool.
  • ksize: A list of ints that has length >= 4. The size of the sliding window for each dimension of the input.
  • strides: A list of ints that has length >= 4. The stride of the sliding window for each dimension of the input.
  • padding: A string from: "SAME", "VALID". The type of padding algorithm to use.
  • data_format: An optional string from: "NHWC", "NCHW". Defaults to "NHWC". Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: [batch, in_height, in_width, in_channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, in_channels, in_height, in_width].
  • name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as grad.