[ez][release blocker fix] Insert linalg_vector_norm into decomp table used for Edge export

[SS-JIA]

Summary:

Context

Addresses this release blocker issue. Some models cannot export because they use linalg_vector_norm which is not currently an ATen operator.

I initially tried adding the op to the core decomp table, but the decomp is not passing pytorch correctness tests. Please see pytorch/pytorch#150241 for more details.

Changes

Since we currently cannot include the op in PyTorch's decomp table, instead we can insert the op into the edge decomp table directly.

This PR is a simple change to add linalg_vector_norm directly to the edge decomp table.

Test Plan:
Tested exporting and running a model with the linalg_vector_norm op via the following script.

import torch
from executorch.exir import to_edge_transform_and_lower, EdgeCompileConfig
from torch.export import Dim, export

from executorch.extension.pybindings.portable_lib import (  # @manual
    _load_for_executorch_from_buffer,
)

class Model(torch.nn.Module):
    def __init__(self):
        super().__init__()

    def forward(self, x):
        return torch.linalg.vector_norm(x, 2)

model = Model()
inputs = (torch.randn(1,1,16,16),)
dynamic_shapes = {
    "x": {
        2: Dim("h", min=16, max=1024),
        3: Dim("w", min=16, max=1024),
    }
}

exported_program = export(model, inputs, dynamic_shapes=dynamic_shapes)
executorch_program = to_edge_transform_and_lower(
    exported_program,
    compile_config=EdgeCompileConfig(_check_ir_validity=False),
).to_executorch()


executorch_module = _load_for_executorch_from_buffer(
    executorch_program.buffer
)

model_output = executorch_module.run_method(
    "forward", tuple(inputs)
)

print(model_output)

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/9938

• 📄 Preview Python docs built from this PR

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

❌ 2 New Failures

As of commit 60b6d51 with merge base f28b5db ():

NEW FAILURES - The following jobs have failed:

• Check Labels / Check labels (gh)
  RuntimeError: Error checking labels: PR does not have required labels
• pull / unittest-arm / linux-job (gh)
  RuntimeError: Command docker exec -t d86e40722f6eb2ed8235613b9c66ab12546d3bca7f836a90efd34dbcee0b738f /exec failed with exit code 1

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

[github-actions]

This PR needs a release notes: label

If your changes are user facing and intended to be a part of release notes, please use a label starting with release notes:.

If not, please add the topic: not user facing label.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "topic: not user facing"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

[guangy10]

Can we add a unit test for it? Something you mentioned in the test plan can be placed to the test to prevent regression

[SS-JIA]

Fix test by swapping to another non core op.

[SS-JIA]

@pytorchbot cherry-pick --onto release/0.6 -c critical

[pytorchbot]

Cherry picking #9938

The cherry pick PR is at #9999 and it is recommended to link a critical cherry pick PR with an issue. The following tracker issues are updated:

• [v0.6.0] Release Tracker #9253 (comment)

Details for Dev Infra team

Raised by workflow job