Fixed installation docs for 1.34 release (#3667)

* Fixed wheel file naming mechanism in installation (#3292) * Updated versioning and naming of wheel files in conf.py and install RST file * Updated installation instructions and fixed wheel file installation commands (#3335) * Updated docker and host wheel install instructions to make them more generic across releases * Updated install instructions: torch GPU to cuda 2.1 and onnx to 1.16 * Added pytorch variant cuda versions Signed-off-by: Bharath Ramaswamy <quic_bharathr@quicinc.com> Signed-off-by: Joel Polizzi <quic_jpolizzi@quicinc.com> Co-authored-by: Joel Polizzi <quic_jpolizzi@quicinc.com> Co-authored-by: Bharath Ramaswamy <quic_bharathr@quicinc.com> Signed-off-by: Bharath Ramaswamy <quic_bharathr@quicinc.com>
quic · Sep 13, 2024 · 89184ab · 89184ab
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diff --git a/Docs/conf.py b/Docs/conf.py
@@ -173,6 +173,7 @@ def setup(app):
 .. |author| replace:: {author}
 .. |project| replace:: {project}
 .. |default-quantsim-config-file| replace:: aimet_common/quantsim_config/default_config.json
+.. |version| replace:: {version}
 """.format(project=project, author=author, version=version)
 
 # -- Options for LaTeX output ------------------------------------------------

diff --git a/Docs/install/index.rst b/Docs/install/index.rst
@@ -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::
 
@@ -61,48 +61,47 @@ 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-torch_gpu\_\ |version|\ |whl_suffix|
-    # Pytorch 1.13 CPU only
-    python3 -m pip install |download_url|\ |version|/aimet_torch-torch_cpu\_\ |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-tf_gpu\_\ |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-tf_cpu\_\ |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-onnx_gpu\_\ |version|\ |whl_suffix|
-    # ONNX 1.14 CPU
-    python3 -m pip install |download_url|\ |version|/aimet_onnx-onnx_cpu\_\ |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.
 
-.. |version| replace:: 1.31.0
-.. |whl_suffix| replace:: -cp38-cp38-linux_x86_64.whl
+.. |whl_suffix| replace:: -cp310-cp310-manylinux_2_34_x86_64.whl
 .. |download_url| replace:: \https://github.com/quic/aimet/releases/download/
 
 System Requirements

diff --git a/Docs/install/install_docker.rst b/Docs/install/install_docker.rst
@@ -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`
@@ -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
 
-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
 ~~~~~~~~~~~~~~~~~

diff --git a/Docs/install/install_host.rst b/Docs/install/install_host.rst
@@ -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
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~