Unsqueeze unbatched input of avg_pool

[wodesuck]

Onnx's AveragePool require input shape as N,C,H,W, but torch accept both N,C,H,W and C,H,W. Unsqueeze if input is unbatched, just like what max_pool does.

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[justinchuby]

Could you create a test in https://github.com/microsoft/onnxscript/blob/main/tests/function_libs/torch_lib/e2e_ops_tests.py ?

[codecov]

Codecov Report

❌ Patch coverage is 63.63636% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 70.45%. Comparing base (8a94ad6) to head (106bca7).

Files with missing lines	Patch %	Lines
onnxscript/function_libs/torch_lib/ops/nn.py	63.63%	2 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2646      +/-   ##
==========================================
- Coverage   70.46%   70.45%   -0.01%     
==========================================
  Files         224      224              
  Lines       26572    26577       +5     
  Branches     2637     2639       +2     
==========================================
+ Hits        18723    18724       +1     
- Misses       6928     6930       +2     
- Partials      921      923       +2     

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[wodesuck]

@justinchuby Test added.

[Copilot]

Pull Request Overview

This PR adds support for unbatched input tensors in average pooling operations to match PyTorch's behavior. While ONNX's AveragePool requires NCHW format, PyTorch accepts both batched (NCHW) and unbatched (CHW) inputs. The changes handle unbatched inputs by automatically unsqueezing/squeezing dimensions, similar to the existing max_pool implementation.

Key Changes:

• Introduced a helper function _aten_avg_pool_onnx that handles both batched and unbatched inputs
• Refactored avg_pool1d, avg_pool2d, and avg_pool3d to use the new helper function
• Added comprehensive tests covering all pooling dimensions with both batched and unbatched inputs

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.

File	Description
onnxscript/function_libs/torch_lib/ops/nn.py	Refactored avg_pool operations to support unbatched inputs via new helper function
tests/function_libs/torch_lib/e2e_ops_tests.py	Added test cases for avg_pool operations with various input dimensions

[titaiwangms]

Thank you. Minor comments and please check this page for lint: https://github.com/microsoft/onnxscript#coding-style

[titaiwangms]

There is still something wrong with lint. Would you check?

[wodesuck]

@titaiwangms Pylint says "torch.nn.functional.avg_pool1d is not callable", that's not true. I have run lintrunner locally without wrong, don't known why it still blame.

[titaiwangms]

@titaiwangms Pylint says "torch.nn.functional.avg_pool1d is not callable", that's not true. I have run lintrunner locally without wrong, don't known why it still blame.

You can go ahead and disable it: To disable, use # pylint: disable=not-callable