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junrushao merged 1 commit into from
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[DOCS] Fix installation from source link some text #9238

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30 changes: 15 additions & 15 deletions docs/install/from_source.rst
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Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

- On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
- On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
- On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
- On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
- On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
sudo apt-get update
sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

brew install gcc git cmake
brew install llvm
brew install python@3.8
brew install gcc git cmake
brew install llvm
brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

.. code:: bash
.. code:: bash

brew install openblas gfortran

pip install pybind11 cython pythran
export OPENBLAS=/opt/homebrew/opt/openblas/lib/
pip install pybind11 cython pythran

export OPENBLAS=/opt/homebrew/opt/openblas/lib/

pip install scipy --no-use-pep517

pip install xgboost

Install Contrib Libraries
Expand Down
14 changes: 6 additions & 8 deletions docs/install/index.rst
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
:maxdepth: 2
Expand Down
18 changes: 2 additions & 16 deletions docs/install/tlcpack.rst
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.
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var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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 Merged

junrushao
merged 1 commit into

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Oct 11, 2021
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[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

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var __re = new RegExp('^' + ".*" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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 Merged

junrushao
merged 1 commit into

from

Oct 11, 2021
 Merged


[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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 Merged

junrushao
merged 1 commit into

from

Oct 11, 2021
 Merged


[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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junrushao
merged 1 commit into

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[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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 Merged

junrushao
merged 1 commit into

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Oct 11, 2021
 Merged


[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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 Merged

junrushao
merged 1 commit into

from

Oct 11, 2021
 Merged


[DOCS] Fix installation from source link some text
#9238
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30 changes: 15 additions & 15 deletions
docs/install/from_source.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
Expand Down

14 changes: 6 additions & 8 deletions
docs/install/index.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,17 +20,15 @@
Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
Expand Down

18 changes: 2 additions & 16 deletions
docs/install/tlcpack.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -20,19 +20,5 @@
TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
[DOCS] Fix installation from source link some text by tqchen · Pull Request #9238 · apache/tvm · GitHub
Skip to content
[DOCS] Fix installation from source link some text#9238

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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 Merged

junrushao
merged 1 commit into

from

Oct 11, 2021
 Merged


[DOCS] Fix installation from source link some text
#9238
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Original file line numberDiff line numberDiff line change
Expand Up@@ -52,8 +52,8 @@ Build the Shared Library
Our goal is to build the shared libraries:

 - On Linux the target library are `libtvm.so` and `libtvm_runtime.so`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`
 - On macOS the target library are `libtvm.dylib` and `libtvm_runtime.dylib`
 - On Windows the target library are `libtvm.dll` and `libtvm_runtime.dll`

It is also possible to :ref:`build the runtime <deploy-and-integration>` library only.

Expand All@@ -74,14 +74,14 @@ linux operating systems, execute (in a terminal):
 sudo apt-get update
 sudo apt-get install -y python3 python3-dev python3-setuptools gcc libtinfo-dev zlib1g-dev build-essential cmake libedit-dev libxml2-dev

Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Use Homebrew to install the required dependencies for macOS running either the Intel or M1 processors. You must follow the post-installation steps specified by
Homebrew to ensure the dependencies are correctly installed and configured:

.. code:: bash
.. code:: bash

 brew install gcc git cmake
 brew install llvm
 brew install python@3.8
 brew install gcc git cmake
 brew install llvm
 brew install python@3.8


We use cmake to build the library.
Expand DownExpand Up@@ -303,20 +303,20 @@ like ``virtualenv``.

 pip3 install --user tornado psutil xgboost cloudpickle

Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
Note on M1 macs, you may have trouble installing xgboost / scipy. scipy and xgboost requires some additional dependencies to be installed,
including openblas and its dependencies. Use the following commands to install scipy and xgboost with the required dependencies and
configuration. A workaround for this is to do the following commands:

 .. code:: bash
 .. code:: bash

 brew install openblas gfortran

 pip install pybind11 cython pythran 
 export OPENBLAS=/opt/homebrew/opt/openblas/lib/
 pip install pybind11 cython pythran 

 export OPENBLAS=/opt/homebrew/opt/openblas/lib/

 pip install scipy --no-use-pep517

 pip install xgboost

Install Contrib Libraries
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docs/install/index.rst

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Installing TVM
==============

TVM is still pre-1.0 release software, meaning that it is under active
development and is changing quickly. Because of this, it is best to
:ref:`install TVM from source <install_from_source>` to guarantee you
have the latest features and bug fixes. If you are interested in deploying to
mobile or embedded devices, you do not need to install the entire TVM stack on
your device. Instead, you only need the runtime and can install using the
Checkout to :ref:`install TVM from source <install-from-source>`. Installing
from source gives you the maximum flexibility to configure the build effectively from the official source releases.
If you are interested in deploying to mobile or embedded devices, you do not need to
install the entire TVM stack on your device. Instead, you only need the runtime and can install using the
:ref:`deployment and integration guide <deploy-and-integration>`.

If you would like to quickly try out TVM or run some demo and tutorials, you
can :ref:`install from Docker <docker-images>`, or install using the
third-party :doc:`TLCPack Python and Conda packages <tlcpack>`
can checkout :ref:`install from Docker <docker-images>`. You can also
tryout pre-built from third-party :doc:`TLCPack Python and Conda packages <tlcpack>`.

.. toctree::
 :maxdepth: 2
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docs/install/tlcpack.rst

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TLCPack
=======

The Tensor Learning Compiler binary Package (TLCPack) community builds and
maintains third-party packaging based on Apache TVM. TLCPack is a community
maintained release that does not contain any additional source code from the
TVM source repository. It takes source code from Apache TVM and builds Pip and
Conda binary packages with different build configurations, for both the stable
release and the nightly release. Please note that additional licensing
conditions may apply (for example, the CUDA EULA is enforced for the CUDA
enabled package) when you use the binary builds.

TLCPack is not part of Apache and is run by thirdparty community volunteers.
Please refer to the official Apache TVM website for Apache source releases.

Licenses for TVM and its dependencies can be found in the github repository.

More information on installing with TLCPack can be found on the `TLCPack site
<https://tlcpack.ai>`_.
TLCPack is a third-party conda and pip packaging based on TVM.
Checkout more information on `TLCPack site <https://tlcpack.ai>`_.