pytorch / pytorch/executorch

No module named 'tosa' using executorch==0.7

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module: arm need-user-input partner: arm
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Python
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Description

🐛 Describe the bug

I installed executorch==0.7 by pip install, and when I run example code in https://docs.pytorch.org/executorch/stable/getting-started.html ,

from executorch.backends.arm.ethosu_partitioner import EthosUPartitioner

it raised the bug:

File ***/envs/vela/lib/python3.12/site-packages/executorch/backends/arm/tosa_quant_utils.py:23
     21 from torch import Tensor
     22 from torch.fx import Node
---> 23 from tosa.RoundingMode import RoundingMode  # type: ignore
     26 q_ops = (
     27     exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
     28     exir_ops.edge.quantized_decomposed.quantize_per_channel.default,
     29 )
     30 dq_ops = (
     31     exir_ops.edge.quantized_decomposed.dequantize_per_tensor.default,
     32     exir_ops.edge.quantized_decomposed.dequantize_per_channel.default,
     33 )

ModuleNotFoundError: No module named 'tosa'

Versions

Versions of relevant libraries:
[pip3] executorch==0.7.0
[pip3] numpy==2.3.2
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-nccl-cu12==2.27.3
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] torch==2.8.0
[pip3] torchao==0.12.0
[pip3] triton==3.4.0
[conda] executorch 0.7.0 pypi_0 pypi
[conda] numpy 2.3.2 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.8.4.1 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.10.2.21 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.3.3.83 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.9.90 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.7.3.90 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.5.8.93 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.7.1 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.27.3 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.8.90 pypi_0 pypi
[conda] torch 2.8.0 pypi_0 pypi
[conda] torchao 0.12.0 pypi_0 pypi
[conda] triton 3.4.0 pypi_0 pypi

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the import in executorch/backends/arm/tosa_quant_utils.py and compare it with the installation instructions in the linked getting-started documentation. Verify how the tosa dependency is expected to be provided, then confirm that importing EthosUPartitioner after installing executorch==0.7 no longer raises ModuleNotFoundError.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
embedded-iot, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
35/100

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