From: @wuxuejian
Reviewed-by: @liangchenghui,@c_34
Signed-off-by: @liangchenghui
pull/8374/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit 0dedcceefa

@ -85,7 +85,7 @@ void TileCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs, const st
std::vector<size_t> cargo_x(d, 1);
std::vector<size_t> cargo_y = x_shape_;
for (int i = d - 2; i >= 0; --i) {
cargo_x[i] = x_shape_[i + 1] * cargo_x[i];
cargo_x[i] = x_shape_[i + 1] * cargo_x[i + 1];
cargo_y[i] *= cargo_y[i + 1] * multiples_[i + 1];
}
size_t offset = 0;

@ -380,10 +380,18 @@ def get_bprop_gather_v2(self):
@bprop_getters.register(P.GatherD)
def get_bprop_gather_d(self):
"""Generate bprop for GatherD"""
gather_d = P.GatherD()
def bprop(x, dim, index, out, dout):
return P.GatherDGrad(dim)(index, dout)
def bprop_ascend(x, dim, index, out, dout):
return (gather_d(dout, dim, index), zeros_like(dim), zeros_like(index))
if context.get_context('device_target') == 'Ascend':
return bprop_ascend
return bprop

@ -44,9 +44,9 @@ class CropAndResize(PrimitiveWithInfer):
mapped to [0, image_height - 1] in image height coordinates. We do allow y1 > y2, in which case the sampled
crop is an up-down flipped version of the original image. The width dimension is treated similarly.
Normalized coordinates outside the [0, 1] range are allowed, in which case we use extrapolation_value to
extrapolate the input image values. Types allowd: float32.
extrapolate the input image values. Types allowed: float32.
- **box_index** (Tensor) - A 1-D tensor of shape [num_boxes] with int32 values in [0, batch).
The value of box_ind[i] specifies the image that the i-th box refers to. Types allowd: int32.
The value of box_ind[i] specifies the image that the i-th box refers to. Types allowed: int32.
- **crop_size** (Tuple[int]) - A tuple of two int32 elements: (crop_height, crop_width).
Only constant value is allowed. All cropped image patches are resized to this size.
The aspect ratio of the image content is not preserved. Both crop_height and crop_width need to be positive.

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