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Updated installation instructions and fixed wheel file installation commands #3335

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Sep 11, 2024
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Updated installation instructions and fixed wheel file installation commands #3335

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df7f979
Updated wheel install instructions to make them more generic across r…
quic-bharathr Sep 9, 2024
cabb446
Fixed wheel file installation instructions
quic-bharathr Sep 10, 2024
c1784fa
Updated install instructions: torch GPU to cuda 2.1 and onnx to 1.16
quic-bharathr Sep 10, 2024
922f6e0
Added pytorch variant cuda versions
quic-bharathr Sep 11, 2024
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36 changes: 18 additions & 18 deletions Docs/install/index.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -47,10 +47,10 @@ The AIMET PyTorch GPU PyPI packages are available for environments that meet the

* 64-bit Intel x86-compatible processor
* Linux Ubuntu 22.04 LTS [Python 3.10] or Ubuntu 20.04 LTS [Python 3.8]
* Cuda 12.0
* CUDA 12.0
* Torch 2.2.2

**Pip install:**
**Pip install**

.. code-block::

Expand All @@ -61,45 +61,45 @@ The AIMET PyTorch GPU PyPI packages are available for environments that meet the
Release Packages
~~~~~~~~~~~~~~~~

For other aimet variants, install the latest version from the .whl files hosted at https://github.com/quic/aimet/releases
For other AIMET variants, install the *latest* version from the .whl files hosted at https://github.com/quic/aimet/releases

**PyTorch**

.. parsed-literal::

# Pytorch 2.1 with CUDA 12.x
python3 -m pip install |download_url|\ |version|/aimet_torch-\ |version|.cu121\ |whl_suffix|

# Pytorch 2.1 CPU only
python3 -m pip install |download_url|\ |version|/aimet_torch-\ |version|.cpu\ |whl_suffix|

# Pytorch 1.13 with CUDA 11.x
python3 -m pip install |download_url|\ |version|/aimet_torch-\ |version|\ |whl_suffix|
# Pytorch 1.13 CPU only
python3 -m pip install |download_url|\ |version|/aimet_torch-\ |version|\ |whl_suffix|
python3 -m pip install |download_url|\ |version|/aimet_torch-\ |version|.cu117\ |whl_suffix|


**TensorFlow**

.. parsed-literal::

# Tensorflow 2.10 GPU with CUDA 11.x
python3 -m pip install |download_url|\ |version|/aimet_tensorflow-\ |version|\ |whl_suffix|
python3 -m pip install |download_url|\ |version|/aimet_tensorflow-\ |version|.cu118\ |whl_suffix|

# Tensorflow 2.10 CPU only
python3 -m pip install |download_url|\ |version|/aimet_tensorflow-\ |version|\ |whl_suffix|
python3 -m pip install |download_url|\ |version|/aimet_tensorflow-\ |version|.cpu\ |whl_suffix|


**Onnx**

.. parsed-literal::

# ONNX 1.14 GPU
python3 -m pip install |download_url|\ |version|/aimet_onnx-\ |version|\ |whl_suffix|
# ONNX 1.14 CPU
python3 -m pip install |download_url|\ |version|/aimet_onnx-\ |version|\ |whl_suffix|
# ONNX 1.16 GPU with CUDA 11.x
python3 -m pip install |download_url|\ |version|/aimet_onnx-\ |version|.cu117\ |whl_suffix|

For previous AIMET releases, browse packages at https://github.com/quic/aimet/releases. Each release includes multiple python packages of the following format:

.. parsed-literal::
# ONNX 1.16 CPU
python3 -m pip install |download_url|\ |version|/aimet_onnx-\ |version|.cpu\ |whl_suffix|

# VARIANT in {torch_gpu, torch_cpu, tf_gpu, tf_cpu, onnx_gpu, onnx_cpu}
# PACKAGE_PREFIX in {aimet_torch, aimet_tensorflow, aimet_onnx}
<PACKAGE_PREFIX>-<VARIANT>_<VERSION>\ |whl_suffix|

For older versions, please browse the releases at https://github.com/quic/aimet/releases and follow the documentation corresponding to that release to select and install the appropriate package.

.. |whl_suffix| replace:: -cp310-cp310-manylinux_2_34_x86_64.whl
.. |download_url| replace:: \https://github.com/quic/aimet/releases/download/
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74 changes: 25 additions & 49 deletions Docs/install/install_docker.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,6 @@ Set the `<variant_string>` to ONE of the following depending on your desired var
#. For the PyTorch 2.1 GPU variant, use `torch-gpu`
#. For the PyTorch 2.1 CPU variant, use `torch-cpu`
#. For the PyTorch 1.13 GPU variant, use `torch-gpu-pt113`
#. For the PyTorch 1.13 CPU variant, use `torch-cpu-pt113`
#. For the TensorFlow GPU variant, use `tf-gpu`
#. For the TensorFlow CPU variant, use `tf-cpu`
#. For the ONNX GPU variant, use `onnx-gpu`
Expand Down Expand Up @@ -121,73 +120,50 @@ Install AIMET packages
From PyPI
=========

Aimet Torch GPU can install from pypi through the following method:
The default AIMET Torch GPU variant may be installed from PyPI as follows:
- Go to https://pypi.org/project/aimet-torch
- Browse the Requirements section of each Release to identify the version you wish to install. Following are some tips:
- For Pytorch 2.2.2 GPU with CUDA 12.1, use aimet-torch>=1.32.2
- For Pytorch 2.1.2 GPU with CUDA 12.1, use aimet-torch==1.32.1.post1
- For PyTorch 1.13 GPU with CUDA 11.7, use aimet-torch==1.31.2
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Couldn't we just tell them to pip install aimet-torch and rely on pip's dependency resolution for aligning the torch/aimet-torch versions?


Go to https://pypi.org/project/aimet-torch to identify a version you wish to install

- For PyTorch 1.13 GPU you should use aimet-torch==1.31.1
- For Pytorch 2.1.2 GPU you should use aimet-torch >= 1.32.0
Run the following commands to install the package (prepend with "sudo" and/or package version as needed):

.. code-block:: bash

sudo apt-get install liblapacke -y
pip install aimet-torch

apt-get install liblapacke -y
python3 -m pip install aimet-torch

From Release Package
====================

Alternatively, we host .whl packages for each release at https://github.com/quic/aimet/releases. Identify the release tag
of the package you wish to install, then follow the instructions below to install AIMET from the .whl file.

Set the <variant_string> to ONE of the following depending on your desired variant
We also host python wheel packages for different variants which may be installed as follows:
- Go to https://github.com/quic/aimet/releases
- Identify the release tag of the package that you wish to install
- Identify the .whl file corresponding to the package variant that you wish to install
- Follow the instructions below to install AIMET from the .whl file

#. For the PyTorch 2.1 GPU variant, use "torch_gpu"
#. For the PyTorch 2.1 CPU variant, use "torch_cpu"
#. For the PyTorch 1.13 GPU variant, use "torch_gpu-pt113"
#. For the PyTorch 1.13 CPU variant, use "torch_cpu-pt113"
#. For the TensorFlow GPU variant, use "tf_gpu"
#. For the TensorFlow CPU variant, use "tf_cpu"
#. For the ONNX GPU variant, use "onnx_gpu"
#. For the ONNX CPU variant, use "onnx_cpu"
Set the package details as follows:

.. code-block:: bash

export AIMET_VARIANT=<variant_string>

Replace <release_tag> in the steps below with the appropriate tag:

.. code-block:: bash

export release_tag=<release_tag>

Set the package download URL as follows:

.. code-block:: bash
# Set the release tag ex. "1.34.0"
export release_tag="<version release tag>"

# Construct the download root URL
export download_url="https://github.com/quic/aimet/releases/download/${release_tag}"

Set the common suffix for the package files as follows:

.. code-block:: bash

export wheel_file_suffix="cp310-cp310-linux_x86_64.whl"

Install the AIMET packages in the order specified below:
# Set the wheel file name with extension
# ex. "aimet_torch-1.34.0.cu121-cp310-cp310-manylinux_2_34_x86_64.whl"
export wheel_file_name="<wheel file name>"

**NOTE:**
#. Please pre-pend the "apt-get install" and "pip3 install" commands with "sudo -H" as appropriate.
#. These instructions assume that pip packages will be installed in the path: /usr/local/lib/python3.10/dist-packages. If that is not the case, please modify it accordingly.
#. Python dependencies will automatically get installed.
Install the selected AIMET package as specified below:
**NOTE:** Python dependencies will automatically get installed.

.. code-block:: bash

# Install ONE of the following depending on the variant
python3 -m pip install ${download_url}/aimet_torch-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix} -f https://download.pytorch.org/whl/torch_stable.html
# OR
python3 -m pip install ${download_url}/aimet_tensorflow-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix}
# OR
python3 -m pip install ${download_url}/aimet_onnx-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix}
python3 -m pip install ${download_url}/${wheel_file_name}


Environment setup
~~~~~~~~~~~~~~~~~
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70 changes: 23 additions & 47 deletions Docs/install/install_host.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -100,73 +100,49 @@ Install AIMET packages
From PyPI
=========

Aimet Torch GPU can install from pypi through the following method:
The default AIMET Torch GPU variant may be installed from PyPI as follows:
- Go to https://pypi.org/project/aimet-torch
- Browse the Requirements section of each Release to identify the version you wish to install. Following are some tips:
- For Pytorch 2.2.2 GPU with CUDA 12.1, use aimet-torch>=1.32.2
- For Pytorch 2.1.2 GPU with CUDA 12.1, use aimet-torch==1.32.1.post1
- For PyTorch 1.13 GPU with CUDA 11.7, use aimet-torch==1.31.2

Go to https://pypi.org/project/aimet-torch to identify a version you wish to install

- For PyTorch 1.13 GPU you should use aimet-torch==1.31.1
- For Pytorch 2.1.2 GPU you should use aimet-torch >= 1.32.0
Run the following commands to install the package (prepend with "sudo" and/or package version as needed):

.. code-block:: bash

sudo apt-get install liblapacke -y
pip install aimet-torch

apt-get install liblapacke -y
python3 -m pip install aimet-torch

From Release Package
====================

Alternatively, we host .whl packages for each release at https://github.com/quic/aimet/releases. Identify the release tag
of the package you wish to install, then follow the instructions below to install AIMET from the .whl file.

Set the <variant_string> to ONE of the following depending on your desired variant

#. For the PyTorch 2.1 GPU variant, use "torch_gpu"
#. For the PyTorch 2.1 CPU variant, use "torch_cpu"
#. For the PyTorch 1.13 GPU variant, use "torch_gpu_pt113"
#. For the PyTorch 1.13 CPU variant, use "torch_cpu_pt113"
#. For the TensorFlow GPU variant, use "tf_gpu"
#. For the TensorFlow CPU variant, use "tf_cpu"
#. For the ONNX GPU variant, use "onnx_gpu"
#. For the ONNX CPU variant, use "onnx_cpu"
We also host python wheel packages for different variants which may be installed as follows:
- Go to https://github.com/quic/aimet/releases
- Identify the release tag of the package that you wish to install
- Identify the .whl file corresponding to the package variant that you wish to install
- Follow the instructions below to install AIMET from the .whl file

.. code-block:: bash

export AIMET_VARIANT=<variant_string>

Replace <release_tag> in the steps below with the appropriate tag:
Set the package details as follows:

.. code-block:: bash

export release_tag=<release_tag>

Set the package download URL as follows:

.. code-block:: bash
# Set the release tag ex. "1.34.0"
export release_tag="<version release tag>"

# Construct the download root URL
export download_url="https://github.com/quic/aimet/releases/download/${release_tag}"

Set the common suffix for the package files as follows:

**NOTE:** Set wheel_file_suffix to cp310-cp310-linux_x86_64.whl OR cp38-cp38-linux_x86_64.whl OR cp36-cp36m-linux_x86_64 OR cp37-cp37m-linux_x86_64 OR py3-none-any as appropriate depending on the actual wheel filename(s) on the https://github.com/quic/aimet/releases.

.. code-block:: bash

export wheel_file_suffix="cp310-cp310-linux_x86_64.whl"

Install the AIMET packages in the order specified below:
# Set the wheel file name with extension
# ex. "aimet_torch-1.33.0.cu121-cp310-cp310-manylinux_2_34_x86_64.whl"
export wheel_file_name="<wheel file name>"

Install the selected AIMET package as specified below:
**NOTE:** Python dependencies will automatically get installed.

.. code-block:: bash

# Install ONE of the following depending on the variant
python3 -m pip install ${download_url}/aimet_torch-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix} -f https://download.pytorch.org/whl/torch_stable.html
# OR
python3 -m pip install ${download_url}/aimet_tensorflow-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix}
# OR
python3 -m pip install ${download_url}/aimet_onnx-${AIMET_VARIANT}_${release_tag}-${wheel_file_suffix}

python3 -m pip install ${download_url}/${wheel_file_name}

Install common debian packages
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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