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[ONNX] Fix any and all outputs' shape #79371

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[ONNX] Fix any and all outputs' shape #79371

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@qqaatw qqaatw commented Jun 12, 2022

Part of #79263

Before: When dim == None and keepdim == 0(False), the reduced output has [1] shape.
After: Squeeze the output so that the shape will be [] as PyTorch's behavior.

@qqaatw qqaatw requested a review from BowenBao as a code owner June 12, 2022 07:38
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@qqaatw qqaatw changed the title Fix shapes [ONNX] Fix any and all outputs' shape Jun 12, 2022
@qqaatw qqaatw mentioned this pull request Jun 12, 2022
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@mikaylagawarecki mikaylagawarecki added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label Jun 13, 2022
@justinchuby justinchuby added the module: onnx Related to torch.onnx label Jun 13, 2022
@qqaatw qqaatw force-pushed the fix_any_all_shape_onnx branch 2 times, most recently from 67e3fbb to ab599c5 Compare June 18, 2022 12:14
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qqaatw commented Jun 21, 2022

@pytorchbot rebase

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@pytorchbot successfully started a rebase job. Check the current status here

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Successfully rebased fix_any_all_shape_onnx onto refs/remotes/origin/master, please pull locally before adding more changes (for example, via git checkout fix_any_all_shape_onnx && git pull --rebase)

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qqaatw commented Jun 21, 2022

@pytorchbot merge

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@pytorchbot successfully started a merge job. Check the current status here

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@qqaatw your PR has been successfully merged.

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Hey @qqaatw.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

facebook-github-bot pushed a commit that referenced this pull request Jun 22, 2022
@qqaatw @facebook-github-bot
[ONNX] Fix any and all outputs' shape (#79371) (#79371)
b875a80 
Summary:
Part of #79263

Before: When `dim` == `None` and `keepdim` == `0`(`False`), the reduced output has `[1]` shape.
After: Squeeze the output so that the shape will be `[]` as PyTorch's behavior.

Pull Request resolved: #79371
Approved by: https://github.com/AllenTiTaiWang, https://github.com/BowenBao

Test Plan: contbuild & OSS CI, see https://hud.pytorch.org/commit/pytorch/pytorch/4b52babcd972ffe92ee55412af1da131f61ffa06

Reviewed By: atalman

Differential Revision: D37343997

Pulled By: atalman

fbshipit-source-id: 07558d99636a1552a99ddfc53b4143c8eea0650c
miladm pushed a commit to miladm/pytorch that referenced this pull request Jun 27, 2022
@qqaatw @miladm
[ONNX] Fix any and all outputs' shape (pytorch#79371)
9848bec 
Part of pytorch#79263

Before: When `dim` == `None` and `keepdim` == `0`(`False`), the reduced output has `[1]` shape.
After: Squeeze the output so that the shape will be `[]` as PyTorch's behavior.

Pull Request resolved: pytorch#79371
Approved by: https://github.com/AllenTiTaiWang, https://github.com/BowenBao
@justinchuby justinchuby mentioned this pull request Jul 27, 2022
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justinchuby pushed a commit to justinchuby/pytorch that referenced this pull request Jul 27, 2022
@qqaatw @justinchuby
[ONNX] Fix any and all outputs' shape (pytorch#79371)
2b19ec7 
Part of pytorch#79263

Before: When `dim` == `None` and `keepdim` == `0`(`False`), the reduced output has `[1]` shape.
After: Squeeze the output so that the shape will be `[]` as PyTorch's behavior.

Pull Request resolved: pytorch#79371
Approved by: https://github.com/AllenTiTaiWang, https://github.com/BowenBao
pytorchmergebot pushed a commit that referenced this pull request Aug 10, 2022
@qqaatw @pytorchmergebot
[ONNX] Add dtype check in onnx verification (#79263)
d9a7e93 
Currently we don't have a dtype check in verifying the consistency between PyTorch and ONNX outputs. As a result, some of dtype inconsistencies were found and reported: #77842 #77845

This is a POC.

Failed workflows:
- [linux-xenial-py3.7-clang7-onnx / test (default, 2, 2, linux.2xlarge)]
  - inconsistent shape
    - TestONNXRuntime_opset10.test_all (#79371)
    - TestONNXRuntime_opset10.test_any (#79371)
    - TestONNXRuntime_opset10.test_argmin_argmax (#79503)
    - TestONNXRuntime_opset10.test_hardshrink (#79695)
    - TestONNXRuntime_opset10.test_linalg_norm (#79506)
    - TestONNXRuntime_opset10.test_linalg_vector_norm (#79506)
    - TestONNXRuntime_opset10.test_prelu_scalar (#79846)
    - TestONNXRuntime_opset10.test_softshrink (#79695)
    - TestONNXRuntime_opset10.test_sum_empty_tensor (skipped)
    - TestONNXRuntime_opset10.test_tolist (skipped)
  - inconsistent dtype
    - test_arithmetic_prim_bool (skipped)
    - test_arithmeticOps_with_low_precision (skipped)
    - test_arithmetic_prim_float (skipped)
    - test_logical_and (#79339)
    - test_logical_or (#79339)
    - test_logical_xor (#79339)
    - test_pow (skipped)
    - test_primitive_input_floating (skipped)
    - test_quantize_per_tensor (#79690)
    - test_quantized_adaptive_avg_pool2d (#79690)
    - test_quantized_arithmetic (#79690)
    - test_quantized_arithmetic_qfunctional (#79690)
    - test_quantized_conv2d (#79690)
    - test_quantized_conv2d_relu (#79690)
    - test_quantized_flatten (#79690)
    - test_quantized_hardsigmoid (#79690)
    - test_quantized_hardswish (#79690)
    - test_quantized_linear (#79690)
    - test_quantized_sigmoid (#79690)
    - test_item (skipped)
    - test_full_like_value (skipped)
    - TestONNXRuntime_opset7.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset8.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset9.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset9_IRv4.test_div_rounding_mode (skipped)
    - test_outer (skipped)
    - test_symbolic_shape_inference_arange_2 (skipped)
Pull Request resolved: #79263
Approved by: https://github.com/justinchuby, https://github.com/BowenBao
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qqaatw commented Aug 10, 2022

@pytorchbot label "release notes: onnx" "topic: bug fixes"

@pytorch-bot pytorch-bot bot added release notes: onnx torch.onnx related changes that should show up in the release notes topic: bug fixes topic category labels Aug 10, 2022
facebook-github-bot pushed a commit that referenced this pull request Aug 10, 2022
@qqaatw @facebook-github-bot
[ONNX] Add dtype check in onnx verification (#79263) (#79263)
dbbf9be 
Summary:
Currently we don't have a dtype check in verifying the consistency between PyTorch and ONNX outputs. As a result, some of dtype inconsistencies were found and reported: #77842 #77845

This is a POC.

Failed workflows:
- [linux-xenial-py3.7-clang7-onnx / test (default, 2, 2, linux.2xlarge)]
  - inconsistent shape
    - TestONNXRuntime_opset10.test_all (#79371)
    - TestONNXRuntime_opset10.test_any (#79371)
    - TestONNXRuntime_opset10.test_argmin_argmax (#79503)
    - TestONNXRuntime_opset10.test_hardshrink (#79695)
    - TestONNXRuntime_opset10.test_linalg_norm (#79506)
    - TestONNXRuntime_opset10.test_linalg_vector_norm (#79506)
    - TestONNXRuntime_opset10.test_prelu_scalar (#79846)
    - TestONNXRuntime_opset10.test_softshrink (#79695)
    - TestONNXRuntime_opset10.test_sum_empty_tensor (skipped)
    - TestONNXRuntime_opset10.test_tolist (skipped)
  - inconsistent dtype
    - test_arithmetic_prim_bool (skipped)
    - test_arithmeticOps_with_low_precision (skipped)
    - test_arithmetic_prim_float (skipped)
    - test_logical_and (#79339)
    - test_logical_or (#79339)
    - test_logical_xor (#79339)
    - test_pow (skipped)
    - test_primitive_input_floating (skipped)
    - test_quantize_per_tensor (#79690)
    - test_quantized_adaptive_avg_pool2d (#79690)
    - test_quantized_arithmetic (#79690)
    - test_quantized_arithmetic_qfunctional (#79690)
    - test_quantized_conv2d (#79690)
    - test_quantized_conv2d_relu (#79690)
    - test_quantized_flatten (#79690)
    - test_quantized_hardsigmoid (#79690)
    - test_quantized_hardswish (#79690)
    - test_quantized_linear (#79690)
    - test_quantized_sigmoid (#79690)
    - test_item (skipped)
    - test_full_like_value (skipped)
    - TestONNXRuntime_opset7.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset8.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset9.test_div_rounding_mode (skipped)
    - TestONNXRuntime_opset9_IRv4.test_div_rounding_mode (skipped)
    - test_outer (skipped)
    - test_symbolic_shape_inference_arange_2 (skipped)

Pull Request resolved: #79263
Approved by: https://github.com/justinchuby, https://github.com/BowenBao

Test Plan: contbuild & OSS CI, see https://hud.pytorch.org/commit/pytorch/pytorch/d9a7e93aaf3166e639ea413123bd6c38b9144adc

Reviewed By: seemethere

Differential Revision: D38585848

fbshipit-source-id: 9da98581ceec51142ae31d3f8a06f9f296a16b23
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