pytorch - 💡(How to fix) Fix DISABLED test_grad_freevar_python_scalar (main.FuncTorchHigherOrderOpTestsWithCompiledAutograd) [2 comments, 1 participants]

pytorch2026-04-08 19:04:11

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pytorch/pytorch#179742•Fetched 2026-04-09 07:50:15

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Error Message

Traceback (most recent call last): File "/var/lib/jenkins/workspace/test/dynamo/test_higher_order_ops.py", line 4645, in test_grad_freevar_python_scalar self.assertExpectedInline( File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/internal/common_utils.py", line 3386, in assertExpectedInline return super().assertExpectedInline(actual if isinstance(actual, str) else str(actual), expect, skip + 1) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/init.py", line 413, in assertExpectedInline assert_expected_inline( File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/init.py", line 378, in assert_expected_inline assert_eq(expect, actual, msg=help_text) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/init.py", line 450, in assertMultiLineEqualMaybeCppStack self.assertMultiLineEqual(expect, actual, *args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 1226, in assertMultiLineEqual self.fail(self.formatMessage(msg, standardMsg)) File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 675, in fail raise self.failureException(msg) AssertionError: 'clas[1105 chars]= sin + 3; sin = None\n output: "f32[][736 chars],)\n' != 'clas[1105 chars]= sin.add(3); sin = None\n output: "f3[739 chars],)\n' class GraphModule(torch.nn.Module): def forward(self, L_x: "f32[3, 3, 3]"): l_x = L_x_

      _saved_tensors_hooks_disable = torch._C._autograd._saved_tensors_hooks_disable("torch.func.{grad, vjp, jacrev, hessian} don't yet support saved tensor hooks. Please open an issue with your use case.");  _saved_tensors_hooks_disable = None
      _grad_increment_nesting = torch._C._functorch._grad_increment_nesting();  _grad_increment_nesting = None

      diff_args: "f32[3, 3, 3]" = torch._C._functorch._wrap_for_grad(l_x_, 1);  l_x_ = None

      set_inplace_requires_grad_allowed = torch._C._functorch.set_inplace_requires_grad_allowed(True);  set_inplace_requires_grad_allowed = None

      _set_tensor_requires_grad: "f32[3, 3, 3]" = torch._functorch.eager_transforms._set_tensor_requires_grad(diff_args);  _set_tensor_requires_grad = None

      set_inplace_requires_grad_allowed_1 = torch._C._functorch.set_inplace_requires_grad_allowed(False);  set_inplace_requires_grad_allowed_1 = None

      sin: "f32[3, 3, 3]" = diff_args.sin()

    add: "f32[3, 3, 3]" = sin + 3;  sin = None

? ^^^

    add: "f32[3, 3, 3]" = sin.add(3);  sin = None

? ^^^^^ + output: "f32[]" = add.sum(); add = None

      _autograd_grad = torch._functorch.eager_transforms._autograd_grad((output,), [diff_args], create_graph = True);  diff_args = None
      grad_input: "f32[3, 3, 3]" = _autograd_grad[0];  _autograd_grad = None

      grad_input_1: "f32[3, 3, 3]" = torch._C._functorch._unwrap_for_grad(grad_input, 1);  grad_input = None
      output_1: "f32[]" = torch._C._functorch._unwrap_for_grad(output, 1);  output = output_1 = None

      _grad_decrement_nesting = torch._C._functorch._grad_decrement_nesting();  _grad_decrement_nesting = None
      _saved_tensors_hooks_enable = torch._C._autograd._saved_tensors_hooks_enable();  _saved_tensors_hooks_enable = None
      return (grad_input_1,)

: To accept the new output, re-run test with envvar EXPECTTEST_ACCEPT=1 (we recommend staging/committing your changes before doing this)

To execute this test, run the following from the base repo dir: python test/dynamo/test_higher_order_ops.py FuncTorchHigherOrderOpTestsWithCompiledAutograd.test_grad_freevar_python_scalar

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

Root Cause

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.

Code Example

Traceback (most recent call last):
  File "/var/lib/jenkins/workspace/test/dynamo/test_higher_order_ops.py", line 4645, in test_grad_freevar_python_scalar
    self.assertExpectedInline(
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3386, in assertExpectedInline
    return super().assertExpectedInline(actual if isinstance(actual, str) else str(actual), expect, skip + 1)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 413, in assertExpectedInline
    assert_expected_inline(
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 378, in assert_expected_inline
    assert_eq(expect, actual, msg=help_text)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 450, in assertMultiLineEqualMaybeCppStack
    self.assertMultiLineEqual(expect, actual, *args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 1226, in assertMultiLineEqual
    self.fail(self._formatMessage(msg, standardMsg))
  File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 675, in fail
    raise self.failureException(msg)
AssertionError: 'clas[1105 chars]= sin + 3;  sin = None\n        output: "f32[][736 chars],)\n' != 'clas[1105 chars]= sin.add(3);  sin = None\n        output: "f3[739 chars],)\n'
  class GraphModule(torch.nn.Module):
      def forward(self, L_x_: "f32[3, 3, 3]"):
          l_x_ = L_x_
  
          _saved_tensors_hooks_disable = torch._C._autograd._saved_tensors_hooks_disable("torch.func.{grad, vjp, jacrev, hessian} don't yet support saved tensor hooks. Please open an issue with your use case.");  _saved_tensors_hooks_disable = None
          _grad_increment_nesting = torch._C._functorch._grad_increment_nesting();  _grad_increment_nesting = None
  
          diff_args: "f32[3, 3, 3]" = torch._C._functorch._wrap_for_grad(l_x_, 1);  l_x_ = None
  
          set_inplace_requires_grad_allowed = torch._C._functorch.set_inplace_requires_grad_allowed(True);  set_inplace_requires_grad_allowed = None
  
          _set_tensor_requires_grad: "f32[3, 3, 3]" = torch._functorch.eager_transforms._set_tensor_requires_grad(diff_args);  _set_tensor_requires_grad = None
  
          set_inplace_requires_grad_allowed_1 = torch._C._functorch.set_inplace_requires_grad_allowed(False);  set_inplace_requires_grad_allowed_1 = None
  
          sin: "f32[3, 3, 3]" = diff_args.sin()
-         add: "f32[3, 3, 3]" = sin + 3;  sin = None
?                                  ^^^
+         add: "f32[3, 3, 3]" = sin.add(3);  sin = None
?                                  ^^^^^ +
          output: "f32[]" = add.sum();  add = None
  
          _autograd_grad = torch._functorch.eager_transforms._autograd_grad((output,), [diff_args], create_graph = True);  diff_args = None
          grad_input: "f32[3, 3, 3]" = _autograd_grad[0];  _autograd_grad = None
  
          grad_input_1: "f32[3, 3, 3]" = torch._C._functorch._unwrap_for_grad(grad_input, 1);  grad_input = None
          output_1: "f32[]" = torch._C._functorch._unwrap_for_grad(output, 1);  output = output_1 = None
  
          _grad_decrement_nesting = torch._C._functorch._grad_decrement_nesting();  _grad_decrement_nesting = None
          _saved_tensors_hooks_enable = torch._C._autograd._saved_tensors_hooks_enable();  _saved_tensors_hooks_enable = None
          return (grad_input_1,)
 : To accept the new output, re-run test with envvar EXPECTTEST_ACCEPT=1 (we recommend staging/committing your changes before doing this)

To execute this test, run the following from the base repo dir:
    python test/dynamo/test_higher_order_ops.py FuncTorchHigherOrderOpTestsWithCompiledAutograd.test_grad_freevar_python_scalar

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

RAW_BUFFERClick to expand / collapse

Platforms: linux, slow

This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.

Over the past 6 hours, it has been determined flaky in 9 workflow(s) with 18 failures and 9 successes.

Debugging instructions (after clicking on the recent samples link): DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs. To find relevant log snippets:

Click on the workflow logs linked above
Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
Grep for test_grad_freevar_python_scalar
There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.

<details><summary>Sample error message</summary>

Traceback (most recent call last):
  File "/var/lib/jenkins/workspace/test/dynamo/test_higher_order_ops.py", line 4645, in test_grad_freevar_python_scalar
    self.assertExpectedInline(
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3386, in assertExpectedInline
    return super().assertExpectedInline(actual if isinstance(actual, str) else str(actual), expect, skip + 1)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 413, in assertExpectedInline
    assert_expected_inline(
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 378, in assert_expected_inline
    assert_eq(expect, actual, msg=help_text)
  File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/expecttest/__init__.py", line 450, in assertMultiLineEqualMaybeCppStack
    self.assertMultiLineEqual(expect, actual, *args, **kwargs)
  File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 1226, in assertMultiLineEqual
    self.fail(self._formatMessage(msg, standardMsg))
  File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/case.py", line 675, in fail
    raise self.failureException(msg)
AssertionError: 'clas[1105 chars]= sin + 3;  sin = None\n        output: "f32[][736 chars],)\n' != 'clas[1105 chars]= sin.add(3);  sin = None\n        output: "f3[739 chars],)\n'
  class GraphModule(torch.nn.Module):
      def forward(self, L_x_: "f32[3, 3, 3]"):
          l_x_ = L_x_
  
          _saved_tensors_hooks_disable = torch._C._autograd._saved_tensors_hooks_disable("torch.func.{grad, vjp, jacrev, hessian} don't yet support saved tensor hooks. Please open an issue with your use case.");  _saved_tensors_hooks_disable = None
          _grad_increment_nesting = torch._C._functorch._grad_increment_nesting();  _grad_increment_nesting = None
  
          diff_args: "f32[3, 3, 3]" = torch._C._functorch._wrap_for_grad(l_x_, 1);  l_x_ = None
  
          set_inplace_requires_grad_allowed = torch._C._functorch.set_inplace_requires_grad_allowed(True);  set_inplace_requires_grad_allowed = None
  
          _set_tensor_requires_grad: "f32[3, 3, 3]" = torch._functorch.eager_transforms._set_tensor_requires_grad(diff_args);  _set_tensor_requires_grad = None
  
          set_inplace_requires_grad_allowed_1 = torch._C._functorch.set_inplace_requires_grad_allowed(False);  set_inplace_requires_grad_allowed_1 = None
  
          sin: "f32[3, 3, 3]" = diff_args.sin()
-         add: "f32[3, 3, 3]" = sin + 3;  sin = None
?                                  ^^^
+         add: "f32[3, 3, 3]" = sin.add(3);  sin = None
?                                  ^^^^^ +
          output: "f32[]" = add.sum();  add = None
  
          _autograd_grad = torch._functorch.eager_transforms._autograd_grad((output,), [diff_args], create_graph = True);  diff_args = None
          grad_input: "f32[3, 3, 3]" = _autograd_grad[0];  _autograd_grad = None
  
          grad_input_1: "f32[3, 3, 3]" = torch._C._functorch._unwrap_for_grad(grad_input, 1);  grad_input = None
          output_1: "f32[]" = torch._C._functorch._unwrap_for_grad(output, 1);  output = output_1 = None
  
          _grad_decrement_nesting = torch._C._functorch._grad_decrement_nesting();  _grad_decrement_nesting = None
          _saved_tensors_hooks_enable = torch._C._autograd._saved_tensors_hooks_enable();  _saved_tensors_hooks_enable = None
          return (grad_input_1,)
 : To accept the new output, re-run test with envvar EXPECTTEST_ACCEPT=1 (we recommend staging/committing your changes before doing this)

To execute this test, run the following from the base repo dir:
    python test/dynamo/test_higher_order_ops.py FuncTorchHigherOrderOpTestsWithCompiledAutograd.test_grad_freevar_python_scalar

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

</details>

Test file path: inductor/test_compiled_autograd.py

For all disabled tests (by GitHub issue), see https://hud.pytorch.org/disabled.

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @kadeng @muchulee8 @amjames @chauhang @aakhundov @coconutruben @jataylo

extent analysis

TL;DR

The most likely fix is to update the test case to use the correct method for adding a scalar to a tensor, which is sin.add(3) instead of sin + 3.

Guidance

Review the test case test_grad_freevar_python_scalar in test_higher_order_ops.py to ensure that the correct method is used for adding a scalar to a tensor.
Verify that the test case is failing due to the incorrect method usage by checking the error message and the expected output.
Update the test case to use sin.add(3) instead of sin + 3 to fix the issue.
Re-run the test with the updated code to verify that the issue is resolved.

Example

# Incorrect code
add: "f32[3, 3, 3]" = sin + 3;  sin = None

# Corrected code
add: "f32[3, 3, 3]" = sin.add(3);  sin = None

Notes

The issue seems to be specific to the test_grad_freevar_python_scalar test case, and updating the method usage should resolve the issue. However, it's always a good practice to review the entire test suite to ensure that similar issues are not present in other test cases.

Recommendation

Apply the workaround by updating the test case to use the correct method for adding a scalar to a tensor, which is sin.add(3) instead of sin + 3. This should resolve the issue and allow the test case to pass.

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pytorch - 💡(How to fix) Fix DISABLED test_grad_freevar_python_scalar (main.FuncTorchHigherOrderOpTestsWithCompiledAutograd) [2 comments, 1 participants]

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pytorch - 💡(How to fix) Fix DISABLED test_grad_freevar_python_scalar (main.FuncTorchHigherOrderOpTestsWithCompiledAutograd) [2 comments, 1 participants]