[https://nvbugs/5625972][fix] Patch llama4 export for bug in torch2.9 #8984
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tensorrt_llm/_torch/auto_deploy/export/library/polar.py(1 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py(0 hunks)
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- tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py
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tensorrt_llm/_torch/auto_deploy/export/library/polar.py
🪛 Ruff (0.14.3)
tensorrt_llm/_torch/auto_deploy/export/library/polar.py
16-16: Unused function argument: angle
(ARG001)
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| """Patch aten.polar for meta kernel issue""" | ||
|
|
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| # TODO(fridah): remove this patch once the issue introduced in https://github.com/pytorch/pytorch/pull/160894 is solved |
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Add the required NVIDIA Apache-2.0 header.
This file is missing the mandated NVIDIA Apache-2.0 copyright header for 2025. Please prepend the standard header before the module docstring. As per coding guidelines.
Apply this diff:
+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
"""Patch aten.polar for meta kernel issue"""📝 Committable suggestion
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Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| """Patch aten.polar for meta kernel issue""" | |
| # TODO(fridah): remove this patch once the issue introduced in https://github.com/pytorch/pytorch/pull/160894 is solved | |
| # Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
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| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """Patch aten.polar for meta kernel issue""" | |
| # TODO(fridah): remove this patch once the issue introduced in https://github.com/pytorch/pytorch/pull/160894 is solved |
🤖 Prompt for AI Agents
tensorrt_llm/_torch/auto_deploy/export/library/polar.py lines 1-3: this file is
missing the required NVIDIA Apache-2.0 copyright header for 2025; prepend the
standard NVIDIA Apache-2.0 header (including copyright line for 2025 and the
Apache-2.0 license notice) at the very top of the file before the existing
module docstring, ensuring the header text matches the project's standard header
format and retains the current docstring and TODO comment below it.
| def polar_custom_fake(abs: torch.Tensor, angle: torch.Tensor) -> torch.Tensor: | ||
| """Fake implementation for export.""" | ||
| out_dtype = torch.complex64 if abs.dtype == torch.float32 else torch.complex128 | ||
| return torch.empty_like(abs, dtype=out_dtype) |
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Fix fake kernel shape inference for broadcasting.
torch.empty_like(abs, ...) drops broadcasted dimensions, so when abs and angle have different but broadcastable shapes, the fake kernel reports the wrong output shape. That breaks export shape propagation. Compute the broadcasted shape explicitly before allocating the fake output.(docs.pytorch.org)
Apply this diff:
@polar_custom.register_fake
def polar_custom_fake(abs: torch.Tensor, angle: torch.Tensor) -> torch.Tensor:
"""Fake implementation for export."""
- out_dtype = torch.complex64 if abs.dtype == torch.float32 else torch.complex128
- return torch.empty_like(abs, dtype=out_dtype)
+ out_dtype = torch.complex64 if abs.dtype == torch.float32 else torch.complex128
+ broadcast_shape = torch.broadcast_shapes(abs.shape, angle.shape)
+ requires_grad = abs.requires_grad or angle.requires_grad
+ return torch.empty(
+ broadcast_shape,
+ dtype=out_dtype,
+ device=abs.device,
+ requires_grad=requires_grad,
+ )🧰 Tools
🪛 Ruff (0.14.3)
16-16: Unused function argument: angle
(ARG001)
🤖 Prompt for AI Agents
In tensorrt_llm/_torch/auto_deploy/export/library/polar.py around lines 16 to
19, the fake implementation uses torch.empty_like(abs, dtype=...) which loses
broadcasted dimensions when abs and angle have different but broadcastable
shapes; compute the explicit broadcasted shape (e.g., via
torch.broadcast_shapes(abs.shape, angle.shape) or torch.broadcast_tensors(abs,
angle)[0].shape) and allocate the fake output with that shape and correct dtype
so the exported kernel reports the correct broadcasted output shape.
…hape issue with aten.polar Signed-off-by: Fridah-nv <[email protected]>
753aef0 to
7151f3b
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patch torch.polar for llama4 for bug in torch2.9
closes #8924
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