|
|
|
@ -538,11 +538,11 @@ class Unfold(Cell):
|
|
|
|
|
and the shape is [out_batch, out_depth, out_row, out_col], the out_batch is the same as the in_batch.
|
|
|
|
|
|
|
|
|
|
Examples:
|
|
|
|
|
>>> net = Unfold(ksizes=[1, 2, 2, 1], strides=[1, 1, 1, 1], rates=[1, 1, 1, 1])
|
|
|
|
|
>>> image = Tensor(np.ones([1, 1, 3, 3]), dtype=mstype.float16)
|
|
|
|
|
>>> net = Unfold(ksizes=[1, 2, 2, 1], strides=[1, 2, 2, 1], rates=[1, 2, 2, 1])
|
|
|
|
|
>>> image = Tensor(np.ones([2, 3, 6, 6]), dtype=mstype.float16)
|
|
|
|
|
>>> net(image)
|
|
|
|
|
Tensor ([[[[1, 1] [1, 1]] [[1, 1], [1, 1]] [[1, 1] [1, 1]], [[1, 1], [1, 1]]]],
|
|
|
|
|
shape=(1, 4, 2, 2), dtype=mstype.float16)
|
|
|
|
|
Tensor ([[[[1, 1] [1, 1]] [[1, 1], [1, 1]] [[1, 1] [1, 1]], [[1, 1] [1, 1]], [[1, 1] [1, 1]],
|
|
|
|
|
[[1, 1], [1, 1]]]], shape=(2, 12, 2, 2), dtype=mstype.float16)
|
|
|
|
|
"""
|
|
|
|
|
|
|
|
|
|
def __init__(self, ksizes, strides, rates, padding="valid"):
|
|
|
|
|