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!2406 fix inv 

Merge pull request !2406 from jiangjinsheng/issue_fix4
This commit is contained in:
mindspore-ci-bot 2020-06-20 16:26:41 +08:00 committed by Gitee
parent 8a913d7586 e9d4b9864f
commit 9bc2ffde54
3 changed files with 7 additions and 7 deletions
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2
mindspore/ops/_grad/grad_math_ops.py
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@ -1044,6 +1044,6 @@ def get_bprop_inv(self):
inv_grad = G.InvGrad()
def bprop(x, out, dout):
dx = inv_grad(x, dout)
dx = inv_grad(out, dout)
return (dx,)
return bprop

2
mindspore/ops/operations/array_ops.py
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@ -2649,7 +2649,7 @@ class BatchToSpaceND(PrimitiveWithInfer):
The length of block_shape is M correspoding to the number of spatial dimensions.
crops (list): The crop value for H and W dimension, containing 2 sub list, each containing 2 int value.
All values must be >= 0. crops[i] specifies the crop values for spatial dimension i, which corresponds to
input dimension i+2. It is required that input_shape[i+2]*block_size[i] >= crops[i][0]+crops[i][1].
input dimension i+2. It is required that input_shape[i+2]*block_size[i] > crops[i][0]+crops[i][1].
Inputs:
- **input_x** (Tensor) - The input tensor.

10
mindspore/ops/operations/other_ops.py
View File

@ -228,20 +228,20 @@ class IOU(PrimitiveWithInfer):
Inputs:
- **anchor_boxes** (Tensor) - Anchor boxes, tensor of shape (N, 4). "N" indicates the number of anchor boxes,
and the value "4" refers to "x0", "x1", "y0", and "y1".
and the value "4" refers to "x0", "x1", "y0", and "y1". Data type must be float16.
- **gt_boxes** (Tensor) - Ground truth boxes, tensor of shape (M, 4). "M" indicates the number of ground
truth boxes, and the value "4" refers to "x0", "x1", "y0", and "y1".
truth boxes, and the value "4" refers to "x0", "x1", "y0", and "y1". Data type must be float16.
Outputs:
Tensor, the 'iou' values, tensor of shape (M, N).
Tensor, the 'iou' values, tensor of shape (M, N), with data type float16.
Raises:
KeyError: When `mode` is not 'iou' or 'iof'.
Examples:
>>> iou = P.IOU()
>>> anchor_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float32)
>>> gt_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float32)
>>> anchor_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float16)
>>> gt_boxes = Tensor(np.random.randint(1.0, 5.0, [3, 4]), mindspore.float16)
>>> iou(anchor_boxes, gt_boxes)
"""