tvm: Apache TVM 是一个开放源代码的机器学习编译器框架,用于 CPU,GPU 和机器学习加速器

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README

# TVM Documentation

This folder contains the source of TVM's documentation, hosted at https://tvm.apache.org/docs

## Build Locally

### With Docker (recommended)

1. Build TVM and the docs inside the [tlcpack/ci-gpu image](https://hub.docker.com/r/tlcpack/ci-gpu) using the [`ci.py`](../tests/scripts/ci.py) script.

```bash
 # If this runs into errors, try cleaning your 'build' directory
 python tests/scripts/ci.py docs

# See other doc building options
 python tests/scripts/ci.py docs --help
 ```

2. Serve the docs and visit http://localhost:8000 in your browser

```bash
 # Run an HTTP server you can visit to view the docs in your browser
 python tests/scripts/ci.py serve-docs
 ```

### Native

1. [Build TVM](https://tvm.apache.org/docs/install/from_source.html) first in the repo root folder, then make it importable:

```bash
 export TVM_HOME=/path-to-tvm
 export TVM_LIBRARY_PATH=$TVM_HOME/build
 pip install --target=$TVM_HOME/python $TVM_HOME/3rdparty/tvm-ffi
 export PYTHONPATH=$TVM_HOME/python:$PYTHONPATH
 ```

`docs/conf.py` unconditionally imports `tvm` at startup, so the build will
 fail immediately if TVM is not importable.

2. Install dependencies

```bash
 # Pillow on Ubuntu may require libjpeg-dev from apt
 ./docker/bash.sh ci_gpu -c \
 'python3 -m pip install --quiet sphinx-book-theme==1.1.4 && python3 -m pip freeze' > frozen-requirements.txt

pip install -r frozen-requirements.txt
 ```

3. Generate the docs

```bash
 # TVM_TUTORIAL_EXEC_PATTERN=none skips the tutorial execution to the build
 # work on most environments (e.g. MacOS).
 export TVM_TUTORIAL_EXEC_PATTERN=none

cd docs
 make html
 ```

4. Run an HTTP server and visit http://localhost:8000 in your browser

```bash
 cd _build/html && python3 -m http.server
 ```

## Only Execute Specified Tutorials

The document build process will execute all the tutorials in the sphinx gallery.
This will cause failure in some cases when certain machines do not have necessary
environment. You can set `TVM_TUTORIAL_EXEC_PATTERN` to only execute
the path that matches the regular expression pattern.

For example, to only build tutorials under `/get_started/tutorials`, run

```bash
python tests/scripts/ci.py docs --tutorial-pattern=/get_started/tutorials
```

To only build one specific file, do

```bash
# The slash \ is used to get . in regular expression
python tests/scripts/ci.py docs --tutorial-pattern=file_name\.py
```

## Helper Scripts

The following script mirrors the CI docs pipeline: it runs a sphinx pre-check
(when not running locally) and then performs a full `make htmldepoly` build,
including tutorial execution. You will need a GPU CI environment.

```bash
tests/scripts/task_python_docs.sh
```

To build docs locally without executing tutorials (fastest local iteration):

```bash
cd docs && TVM_TUTORIAL_EXEC_PATTERN=none make html
```

Note: the sphinx pre-check (warning validation) only runs in CI (`IS_LOCAL=0`).
`python tests/scripts/ci.py docs` always sets `IS_LOCAL=1` and skips the
pre-check regardless of other flags.

To run the full build including tutorial executions:

```bash
python tests/scripts/ci.py docs --full
```

## Define the Order of Tutorials

You can define the order of tutorials with `subsection_order` and
`within_subsection_order` in [`conf.py`](conf.py).
By default, the tutorials within one subsection are sorted by filename.

## Google Colab Integration

All the TVM tutorials can be opened and used interactively in Google Colab by
clicking the button at the top of the page. To do this, `sphinx-gallery` builds
`.ipynb` files from each tutorial, which are automatically deployed to the
[apache/tvm-site](https://github.com/apache/tvm-site/tree/asf-site) repo's
`asf-site` branch by [@tvm-bot](https://github.com/tvm-bot).

To make sure your tutorial runs correctly on Colab, any non-Python parts of
the tutorial (e.g. dependency installations) should be prefixed by an
[IPython magic command](https://ipython.readthedocs.io/en/stable/interactive/magics.html).
These will not be included in the built `HTML` file. For example, to install
Pytorch in your tutorial, add a ReStructured Text block like the following:

```python
######################################################################
# To run this tutorial, we must install PyTorch:
#
# .. code-block:: bash
#
# %%shell
# pip install torch
#
```

### Interactive Bash Scripts

In stock IPython, the `%%bash` magic command should be used to run shell
commands. However, this command does not give real-time output - the
tutorial's user will not see any output until the entire cell finishes
running. When running commands that take several minutes (e.g. installing
dependencies), this is annoying.

Luckily, Google Colab has the `%%shell` magic command that does the same
thing as `%%bash`, but gives output in real time. This command is specific
to Colab, and its [source code](https://github.com/googlecolab/colabtools)
is public. Thus, `%%shell` should be used instead of `%%bash` when writing
TVM tutorials.