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Add Windows instructions

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powderluv
2022-10-30 22:25:42 -07:00
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@@ -21,9 +21,9 @@ High Performance Machine Learning and Data Analytics for CPUs, GPUs, Accelerator
This step sets up a new VirtualEnv for Python
```shell
python --version #Check you have 3.7->3.10 on Linux or 3.10 on macOS
python --version #Check you have 3.10 on Linux, macOS or Windows Powershell
python -m venv shark_venv
source shark_venv/bin/activate
source shark_venv/bin/activate # Use shark_venv/Scripts/activate on Windows
# If you are using conda create and activate a new conda env
@@ -38,9 +38,8 @@ python -m pip install --upgrade pip
This step pip installs SHARK and related packages on Linux Python 3.7, 3.8, 3.9, 3.10 and macOS Python 3.10
```shell
pip install nodai-shark -f https://nod-ai.github.io/SHARK/package-index/ -f https://llvm.github.io/torch-mlir/package-index/ -f https://github.com/nod-ai/shark-runtime/releases --extra-index-url https://download.pytorch.org/whl/nightly/cpu
pip install nodai-shark -f https://nod-ai.github.io/SHARK/package-index/ -f https://llvm.github.io/torch-mlir/package-index/ -f https://nod-ai.github.io/SHARK-Runtime/pip-release-links.html --extra-index-url https://download.pytorch.org/whl/nightly/cpu
```
If you are on an Intel macOS machine you need this [workaround](https://github.com/nod-ai/SHARK/issues/102) for an upstream issue.
### Run shark tank model tests.
```shell
@@ -77,12 +76,38 @@ git clone https://github.com/nod-ai/SHARK.git
```
## Setup your Python VirtualEnvironment and Dependencies
### Windows Users
```shell
# Setup venv and install necessary packages (torch-mlir, nodLabs/Shark, ...).
# Requires Python 3.10 and Powershell
./setup_venv.ps1
shark.venv/Scripts/activate
```
### Linux / macOS Users
```shell
# Setup venv and install necessary packages (torch-mlir, nodLabs/Shark, ...).
./setup_venv.sh
source shark.venv/bin/activate
```
For example if you want to use Python3.10 and with TF Import tools you can use the environment variables like:
### Run a demo script
```shell
python -m shark.examples.shark_inference.resnet50_script --device="cpu" # Use gpu | vulkan
# Or a pytest
pytest tank/test_models.py -k "MiniLM"
```
</details>
<details>
<summary>Development, Testing and Benchmarks</summary>
If you want to use Python3.10 and with TF Import tools you can use the environment variables like:
Set `USE_IREE=1` to use upstream IREE
```
# PYTHON=python3.10 VENV_DIR=0617_venv IMPORTER=1 ./setup_venv.sh
@@ -109,17 +134,6 @@ for Torch-MLIR.
```
Now the SHARK will use your locally build Torch-MLIR repo.
### Run a demo script
```shell
python -m shark.examples.shark_inference.resnet50_script --device="cpu" # Use gpu | vulkan
# Or a pytest
pytest tank/test_models.py -k "MiniLM"
```
</details>
<details>
<summary>Testing and Benchmarks</summary>
## Benchmarking Dispatches