Reduce sample inputs for prototype transform kernels #6714
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pmeier
commented
Oct 6, 2022
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| def xfail_python_scalar_arg_jit(name, *, reason=None): | ||
| def xfail_jit_python_scalar_arg(name, *, reason=None): |
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Just a rename that moves the jit term to the front of the name to make it clear this is only a JIT issue.
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| # TODO: check if this is a regression since it seems that should be supported if `int` is ok | ||
| xfail_jit_list_of_ints("fill"), |
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We have a few of these. I'm not sure if this is a regression of #6636. Will check and send a follow-up PR since this is one is only test changes.
| kernel = _get_gaussian_kernel2d(kernel_size, sigma, dtype=dtype, device=img.device) | ||
| kernel = kernel.expand(img.shape[-3], 1, kernel.shape[0], kernel.shape[1]) | ||
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| img, need_cast, need_squeeze, out_dtype = _cast_squeeze_in( |
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Just a formatting change like #5880 that I saw while going through the kernels.
vfdev-5
reviewed
Oct 6, 2022
| and args_kwargs.kwargs.get("padding_mode", "constant") == "constant", | ||
| ) | ||
| ), | ||
| xfail_jit_python_scalar_arg("padding"), |
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I wonder why all this xfail appeared in this PR and not before ?
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Because we didn't test scalar padding before
Thus, while reducing the number of sample inputs now, the tests are actually more comprehensive.
vfdev-5
approved these changes
Oct 6, 2022
facebook-github-bot
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Oct 17, 2022
Summary:
* pad_image_tensor
* pad_mask and pad_bounding_box
* resize_{image_tensor, mask, bounding_box}
* center_crop_{image_tensor, mask}
* {five, ten}_crop_image_tensor
* crop_{image_tensor, mask}
* convert_color_space_image_tensor
* affine_{image_tensor, mask, bounding_box}
* rotate_{image_tensor, mask}
* gaussian_blur_image_tensor
* cleanup
Reviewed By: NicolasHug
Differential Revision: D40427478
fbshipit-source-id: 4954886d7d0b8212ea92847b07092a8dfad809cb
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Addresses 3. from #6622.
This PR achieves a significant reduction of the number of sample inputs. Only for the bounding box kernels, the number goes up slightly. After manual inspection, it became clear that our previous sample inputs were not sufficient.
mainpad_image_tensorresize_image_tensorpad_maskcenter_crop_image_tensorresize_maskcenter_crop_maskaffine_image_tensorten_crop_image_tensorrotate_image_tensorcrop_image_tensoraffine_maskconvert_color_space_image_tensorcrop_maskgaussian_blur_image_tensoraffine_bounding_boxfive_crop_image_tensorpad_bounding_boxrotate_maskresize_bounding_boxIn total we cut the number of tests (and approximately the runtime) roughly to a third of what is was before. Plus, we even increase the coverage ever so slightly:
main: