fix(docs): note numpy version requirements in readme
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README.md
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README.md
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@ -99,7 +99,7 @@ Every time you start using ONNX web, activate the virtual environment:
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```shell
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```shell
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# on linux:
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# on linux:
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> ./onnx_env/bin/activate
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> source ./onnx_env/bin/activate
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# on windows:
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# on windows:
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> .\onnx_env\Scripts\Activate.bat
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> .\onnx_env\Scripts\Activate.bat
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@ -116,7 +116,8 @@ Update pip itself:
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Install the following packages for AI:
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Install the following packages for AI:
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```shell
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```shell
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> pip install diffusers transformers ftfy numpy spacy scipy
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> pip install numpy>=1.20,<1.24 # version is important, 1.24 removed the deprecated np.float symbol
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> pip install accelerate diffusers transformers ftfy spacy scipy
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> pip install onnx onnxruntime torch
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> pip install onnx onnxruntime torch
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> pip install onnxruntime-directml --force-reinstall # TODO: is this one necessary?
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> pip install onnxruntime-directml --force-reinstall # TODO: is this one necessary?
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```
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```
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@ -133,8 +134,11 @@ _Or_ install all of these packages at once using [the `requirements.txt` file](.
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> pip install -r requirements.txt
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> pip install -r requirements.txt
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```
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```
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At the moment, none of these packages seem to need specific versions. There is a warning about an incompatibility in
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At the moment, only `numpy` seems to need a specific version. If you see an error about `np.float`, make sure you are
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Protobuf, and some of the gist guides recommend `diffusers=0.3.0`, but I had trouble with old versions of `diffusers`
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not using `numpy>=1.24`. [This SO question](https://stackoverflow.com/questions/74844262/how-to-solve-error-numpy-has-no-attribute-float-in-python)
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has more details.
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I got a warning about an incompatibility in `protobuf` when installing the `onnxruntime-directml` package, but have not seen any issues. Some of the gist guides recommend `diffusers=0.3.0`, but I had trouble with old versions of `diffusers`
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before 0.6.0 or so. If I can determine a good set of working versions, I will pin them in `requirements.txt`.
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before 0.6.0 or so. If I can determine a good set of working versions, I will pin them in `requirements.txt`.
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### Install ORT Nightly package
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### Install ORT Nightly package
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@ -145,7 +149,6 @@ Downloads can be found at https://aiinfra.visualstudio.com/PublicPackages/_artif
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Python 3.10, download the `cp310` package. For Python 3.9, download the `cp39` package, and so on.
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Python 3.10, download the `cp310` package. For Python 3.9, download the `cp39` package, and so on.
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```shell
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```shell
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> wget https://aiinfra.pkgs.visualstudio.com/PublicPackages/_apis/packaging/feeds/7982ae20-ed19-4a35-a362-a96ac99897b7/pypi/packages/ort-nightly-directml/versions/1.14.dev20221214001/ort_nightly_directml-1.14.0.dev20221214001-cp310-cp310-win_amd64.whl/content
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> pip install ~/Downloads/ort_nightly_directml-1.14.0.dev20221214001-cp310-cp310-win_amd64.whl --force-reinstall
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> pip install ~/Downloads/ort_nightly_directml-1.14.0.dev20221214001-cp310-cp310-win_amd64.whl --force-reinstall
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```
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```
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@ -174,7 +177,9 @@ Download the conversion script from the `huggingface/diffusers` repository to th
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Run the conversion script with your desired model(s):
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Run the conversion script with your desired model(s):
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```shell
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```shell
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> python convert_stable_diffusion_checkpoint_to_onnx.py --model_path="runwayml/stable-diffusion-v1-5" --output_path="./stable-diffusion-onnx-v1-5"
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> python convert_stable_diffusion_checkpoint_to_onnx.py \
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--model_path="runwayml/stable-diffusion-v1-5" \
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--output_path="./models/stable-diffusion-onnx-v1-5"
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```
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```
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This will take a little while to convert each model. Stable diffusion v1.4 is about 6GB, v1.5 is at least 10GB or so.
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This will take a little while to convert each model. Stable diffusion v1.4 is about 6GB, v1.5 is at least 10GB or so.
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