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ONNX Export Slice and Flip ops for opset 10 #20533

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@pytorchbot pytorchbot added the module: onnx Related to torch.onnx label May 15, 2019
@lara-hdr lara-hdr changed the title ONNX Export Slice op for opset 10 ONNX Export Slice and Flip op for opset 10 May 15, 2019
@lara-hdr lara-hdr changed the title ONNX Export Slice and Flip op for opset 10 ONNX Export Slice and Flip ops for opset 10 May 15, 2019
@li-roy li-roy added the triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module label May 16, 2019
@li-roy li-roy requested a review from houseroad May 16, 2019 23:53
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Check the inline comments.

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@houseroad has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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lara-hdr commented Jun 3, 2019

@houseroad any updates on this?

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@houseroad has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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@pytorchbot retest this please

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@houseroad has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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lara-hdr commented Jun 7, 2019

@pytorchbot rebase this please

@@ -118,3 +117,45 @@ def symbolic_fn(g, input, kernel_size, stride, padding, ceil_mode, count_include
avg_pool1d = _avg_pool('avg_pool1d', _single)
avg_pool2d = _avg_pool('avg_pool2d', _pair)
avg_pool3d = _avg_pool('avg_pool3d', _triple)


def slice_op(g, input, axes, starts, ends, steps=None, dynamic_slice=False):
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wait, is this still necessary? oh you call it in the _slice_op...

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@houseroad has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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Looks good.

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lara-hdr commented Jun 7, 2019

Thank you @houseroad!!

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@houseroad merged this pull request in cc85c3d.

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