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2 changes: 1 addition & 1 deletion examples/windows/accuracy_benchmark/requirements.txt
Original file line number Diff line number Diff line change
Expand Up @@ -8,4 +8,4 @@ peft>=0.5.0
rwkv>=0.7.3
tiktoken==0.7.0
tqdm==4.66.5
transformers==4.49.0
transformers==4.57.3
4 changes: 2 additions & 2 deletions examples/windows/onnx_ptq/genai_llm/requirements.txt
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@@ -1,4 +1,4 @@
datasets>=2.14.5
onnx==1.18.0
torch==2.6.0
transformers==4.49.0
torch==2.9.0
transformers==4.57.3
31 changes: 31 additions & 0 deletions examples/windows/onnx_ptq/whisper/README.md
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Expand Up @@ -41,6 +41,37 @@ pip install -r requirements.txt

```

### Optional: Installing latest PyTorch and TorchAudio versions (2.8+)

For users who need the latest versions of PyTorch and TorchAudio (version >=2.8), follow these additional steps:

1. **Install PyTorch and TorchAudio with CUDA support:**

```bash

pip install --upgrade torch torchaudio --index-url https://download.pytorch.org/whl/cu128

```

1. **Install torchcodec:**

```bash

pip install torchcodec

```

1. **Set up FFMPEG dependencies:**
- Download FFMPEG from: <https://www.gyan.dev/ffmpeg/builds/packages/ffmpeg-7.1.1-full_build-shared.7z>
- Extract the archive
- Copy all DLL files from the `bin` folder of the extracted FFMPEG directory and paste them into the torchcodec package folder (typically located at `<Python_Root_Folder>/Lib/site-packages/torchcodec`)

1. **Copy PyTorch DLL files:**
- Navigate to the `lib` folder in the torch package directory
- Copy all DLL files from this folder and paste them into the torchcodec package folder

After completing these steps, torchaudio will be ready for use.

## Inference script

The script `whisper_optimum_ort_inference.py` is for Optimum-ORT based inference of an ONNX Whisper model. It takes an audio file (.wav) as input and transcribes its content in english. This script also supports Word Error Rate (WER) accuracy measurement.
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4 changes: 2 additions & 2 deletions examples/windows/onnx_ptq/whisper/requirements.txt
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Expand Up @@ -4,10 +4,10 @@ datasets==2.19.0
evaluate
jiwer
librosa
onnx==1.17.0
onnx==1.18.0
onnxruntime-gpu==1.20.1
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Can we use onnx 1.19 and ort 1.23?

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I don't think there should be an issue upgrading onnx to 1.19 but i need to test the scripts for onnxruntime-gpu. Will update in comment, if it works.

optimum==1.23.3
soundfile
torch==2.7.0+cu128
torchaudio==2.7.0+cu128
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Can we update this torch dependencies to 2.9 as well?

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@hthadicherla hthadicherla Dec 8, 2025

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The reason why we kept these torch dependencies to 2.7, is because torchaudio >= 2.8 requires ffmpeg binaries which cannot be installed by pip and needs to be installed manually. Since torchaudio == 2.7 requires torch ==2.7 we cannot upgrade torch as well

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I have written steps to upgrade torch dependencies in the README though.

transformers==4.48.0
transformers==4.57.3