crops
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A Tensor . Must be one of the following types: int32 , int64 . 2-D
with shape [M, 2] , all values must be >= 0. crops[i] = [crop_start,
crop_end] specifies the amount to crop from input dimension i + 1 ,
which corresponds to spatial dimension i . It is required that
crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1] .
This operation is equivalent to the following steps:
- Reshape
input to reshaped of shape: [block_shape[0], ...,
block_shape[M-1], batch / prod(block_shape), input_shape[1], ...,
input_shape[N-1]] 2. Permute dimensions of reshaped to produce
permuted of shape [batch / prod(block_shape), input_shape[1],
block_shape[0], ..., input_shape[M], block_shape[M-1],
input_shape[M+1], ..., input_shape[N-1]] 3. Reshape permuted to
produce reshaped_permuted of shape [batch / prod(block_shape),
input_shape[1] * block_shape[0], ..., input_shape[M] * block_shape[M-1],
input_shape[M+1], ..., input_shape[N-1]] 4. Crop the start and end of
dimensions [1, ..., M] of reshaped_permuted according to crops to
produce the
output of shape: [batch / prod(block_shape), input_shape[1] *
block_shape[0] - crops[0,0] - crops[0,1], ..., input_shape[M] *
block_shape[M-1] - crops[M-1,0] - crops[M-1,1], input_shape[M+1],
..., input_shape[N-1]]
Some examples: (1) For the following input of shape [4, 1, 1, 1] ,
block_shape = [2, 2] , and crops = [[0, 0], [0, 0]] : [[[[1]]],
[[[2]]], [[[3]]], [[[4]]]]
The output tensor has shape [1, 2, 2, 1] and value: x = [[[[1],
[2]], [[3], [4]]]] (2) For the following input of shape [4, 1, 1,
3] ,
block_shape = [2, 2] , and crops = [[0, 0], [0, 0]] : [[[1, 2,
3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
The output tensor has shape [1, 2, 2, 3] and value: x = [[[[1, 2,
3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]] (3) For the following
input of shape [4, 2, 2, 1] ,
block_shape = [2, 2] , and crops = [[0, 0], [0, 0]] : x =
[[[[1], [3]], [[9], [11]]], [[[2], [4]], [[10], [12]]], [[[5], [7]],
[[13], [15]]], [[[6], [8]], [[14], [16]]]]
The output tensor has shape [1, 4, 4, 1] and value: x = [[[1],
[2], [3], [4]], [[5], [6], [7], [8]], [[9], [10], [11], [12]],
[[13], [14], [15], [16]]] (4) For the following input of shape
[8, 1, 3, 1] ,
block_shape = [2, 2] , and crops = [[0, 0], [2, 0]] : x =
[[[[0], [1], [3]]], [[[0], [9], [11]]], [[[0], [2], [4]]], [[[0],
[10], [12]]], [[[0], [5], [7]]], [[[0], [13], [15]]], [[[0], [6],
[8]]], [[[0], [14], [16]]]]
The output tensor has shape [2, 2, 4, 1] and value: x = [[[[1],
[2], [3], [4]], [[5], [6], [7], [8]]], [[[9], [10], [11], [12]],
[[13], [14], [15], [16]]]]
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