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@ -7506,9 +7506,16 @@ def space_to_depth(x, blocksize, name=None):
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space_to_depth is used to This operation is useful for resizing the activations between convolutions
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(but keeping all data)
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- Non-overlapping blocks of size block_size x block size are rearranged into depth at each location.
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- The depth of the output tensor is block_size * block_size * input channel
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- The Y, X coordinates within each block of the input become the high order component of the output channel index
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- channel should be divisible by square of blocksize
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- height, width should be divsible by blocksize
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Args:
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x(variable): The input LoDtensor.
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blocksize(variable): The blocksize to select the element on each feature map
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blocksize(variable): The blocksize to select the element on each feature map should be > 2
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Returns:
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Variable: The output LoDtensor.
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