tf.raw_ops.AvgPoolGrad

Computes gradients of the average pooling function.

Compat aliases for migration

tf.compat.v1.raw_ops.AvgPoolGrad

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`.

Args