tf.raw_ops.AvgPool3DGrad

Computes gradients of average pooling function.

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

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).