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Arm backend: Replace Tensor_Scalar with Tensor_Tensor in sqrt op #11783

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Arm backend: Replace Tensor_Scalar with Tensor_Tensor in sqrt op #11783

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@wwwind wwwind commented Jun 18, 2025 •
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Arm backend: Replace Tensor_Scalar with Tensor_Tensor in sqrt op

Change-Id: Ia3e596f855ec97b0ad59161bccc906b13e96c770

Signed-off-by: Elena Zhelezina [email protected]

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218

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Arm backend: Replace Tensor_Scalar with Tensor_Tensor in sqrt op
481a827 
Signed-off-by: Elena Zhelezina <[email protected]>
Change-Id: Ia3e596f855ec97b0ad59161bccc906b13e96c770
@wwwind wwwind requested a review from digantdesai as a code owner June 18, 2025 12:08
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pytorch-bot bot commented Jun 18, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/11783

Note: Links to docs will display an error until the docs builds have been completed.

❌ 3 New Failures, 1 Cancelled Job, 2 Unrelated Failures

As of commit 1774308 with merge base 121714a (image):

NEW FAILURES - The following jobs have failed:

CANCELLED JOB - The following job was cancelled. Please retry:

FLAKY - The following jobs failed but were likely due to flakiness present on trunk:

This comment was automatically generated by Dr. CI and updates every 15 minutes.

@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Jun 18, 2025
@wwwind wwwind requested a review from zingo June 18, 2025 12:08
@wwwind wwwind added partner: arm For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm release notes: arm Changes to the ARM backend delegate ciflow/trunk labels Jun 18, 2025
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zingo commented Jun 19, 2025 •
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fails in 2 Arm jobs, trying a rebase to see if it helps

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digantdesai commented Jul 10, 2025

Please rebase?

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digantdesai reviewed Jul 10, 2025
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LGTM at a high level, left some comments.

backends/arm/operator_support/tosa_supported_operators.py

input_quantized = input_quantized or all(
(input_node.target in dq_ops)
or (node.name == "aten_pow_tensor_tensor")
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Why are we using name here? Also didn't we already have support for torch.ops.aten.pow.Tensor_Tensor?

backends/arm/operator_support/tosa_supported_operators.py
exir_ops.edge.aten.squeeze_copy.dims,
exir_ops.edge.aten.pow.Tensor_Scalar,
exir_ops.edge.aten.pow.Tensor_Tensor,
torch.ops.aten.pow.Tensor_Tensor,
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why add aten target too?

backends/arm/quantizer/quantization_annotator.py
torch.ops.aten.hardswish_.default,
torch.ops.aten.full_like.default,
torch.ops.aten.pow.Tensor_Scalar,
torch.ops.aten.pow.Tensor_Tensor,
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Add BI + quantize tests in test_pow.py?

backends/arm/_passes/annotate_channels_last_dim_order_pass.py
"""
if node.op == "placeholder":
# node is an input, weight or bias node
if not node.users:
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Nit: move the comment?

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zingo commented Jul 31, 2025

This will unfortunately need a rebase after the TOSA 0.80.1 removal :(

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github-actions bot commented Sep 30, 2025

Looks like this PR hasn't been updated in a while so we're going to go ahead and mark this as Stale.
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@github-actions github-actions bot added the stale PRs inactive for over 60 days label Sep 30, 2025
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github-actions bot commented Dec 2, 2025

Looks like this PR hasn't been updated in a while so we're going to go ahead and mark this as Stale.
Feel free to remove the Stale label if you feel this was a mistake.
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