tf.raw_ops.AvgPool3DGrad

Computes gradients of average pooling function.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.AvgPool3DGrad

tf.raw_ops.AvgPool3DGrad(
    orig_input_shape, grad, ksize, strides, padding, data_format='NDHWC', name=None
)

Args
orig_input_shape	A Tensor of type int32. The original input dimensions.
grad	A Tensor. Must be one of the following types: half, bfloat16, float32, float64. Output backprop of shape [batch, depth, rows, cols, channels].
ksize	A list of ints that has length >= 5. 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have ksize[0] = ksize[4] = 1.
strides	A list of ints that has length >= 5. 1-D tensor of length 5. The stride of the sliding window for each dimension of input. Must have strides[0] = strides[4] = 1.
padding	A string from: "SAME", "VALID". The type of padding algorithm to use.
data_format	An optional string from: "NDHWC", "NCDHW". Defaults to "NDHWC". The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].
name	A name for the operation (optional).

Returns
A Tensor. Has the same type as grad.