wehub-resource-sync
52 lines
1.9 KiB
ReStructuredText
52 lines
1.9 KiB
ReStructuredText
.. Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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.. http://www.apache.org/licenses/LICENSE-2.0
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.. Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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.. _install-from-pypi:
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Install from PyPI
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=================
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For most Python users, the quickest way to get started is to install the Apache
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TVM wheel from PyPI:
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.. code-block:: bash
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pip install apache-tvm
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This installs the Python package, including modules such as ``tvm.tirx``, and
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is suitable for trying tutorials that do not require a custom build.
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CUDA environments
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-----------------
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Some CUDA workflows use NVIDIA's Python CUDA bindings for runtime compilation.
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Install the CUDA extra in the same environment as TVM when you need this path:
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.. code-block:: bash
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pip install "apache-tvm[cuda]"
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This extra installs Python-side CUDA bindings only. It does not make the PyPI
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wheel a CUDA-enabled TVM build, and it does not install NVIDIA drivers or a CUDA
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toolkit. If you need CUDA support in TVM itself, build TVM from source with
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``USE_CUDA=ON``.
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For more details on installing the TIRx compiler and optional kernel library,
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visit the :doc:`TIRx installation </tirx/install>` page. If you need to
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customize TVM's build configuration, visit the
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:ref:`install TVM from source <install-from-source>` page instead.
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