| |
|
|
| import os |
| import re |
| from collections import defaultdict |
| from pathlib import Path |
| from typing import Dict, List, Tuple |
|
|
| from update_readme import generate_url, get_all_files |
|
|
|
|
| class Wheel: |
| def __init__(self, full_name: str, url: str): |
| """ |
| Args: |
| full_name: |
| Example: k2-1.24.3.dev20230720+cpu.torch1.10.0-cp36-cp36m-macosx_10_9_x86_64.whl |
| """ |
| self.full_name = full_name |
| |
| pattern = ( |
| r"k2-(\d)\.(\d)+((\.)(\d))?\.dev(\d{8})\+cpu\.torch(\d\.\d+\.\d)-cp(\d+)" |
| ) |
| m = re.search(pattern, full_name) |
|
|
| self.k2_major = int(m.group(1)) |
| self.k2_minor = int(m.group(2)) |
| self.k2_patch = int(m.group(5)) |
| self.k2_date = int(m.group(6)) |
| self.torch_version = m.group(7) |
| self.py_version = int(m.group(8)) |
| self.url = url |
|
|
| def __str__(self): |
| return self.url |
|
|
| def __repr__(self): |
| return self.url |
|
|
|
|
| def generate_index(filename: str, torch_versions) -> str: |
| b = [] |
| for i in torch_versions: |
| b.append(f" ./{i}.rst") |
| b = "\n".join(b) |
|
|
| s = f"""\ |
| Pre-compiled CPU wheels (macOS) |
| =============================== |
| |
| This page describes pre-compiled ``CPU`` wheels for `k2`_ on macOS. |
| |
| .. toctree:: |
| :maxdepth: 2 |
| |
| {b} |
| """ |
| with open(filename, "w") as f: |
| f.write(s) |
|
|
|
|
| def sort_by_wheel(x: Wheel): |
| return x.k2_major, x.k2_minor, x.k2_patch, x.k2_date, x.py_version |
|
|
|
|
| def sort_by_torch(x): |
| major, minor, patch = x.split(".") |
| return int(major), int(minor), int(patch) |
|
|
|
|
| def get_all_torch_versions(wheels: List[Wheel]) -> List[str]: |
| ans = set() |
| for w in wheels: |
| ans.add(w.torch_version) |
|
|
| |
| ans = list(ans) |
| ans.sort(reverse=True, key=sort_by_torch) |
| return ans |
|
|
|
|
| def get_doc_dir(): |
| k2_dir = os.getenv("K2_DIR") |
| if k2_dir is None: |
| raise ValueError("Please set the environment variable k2_dir") |
|
|
| cpu_dir = Path(k2_dir) / "docs/source/installation/pre-compiled-cpu-wheels-macos" |
|
|
| if not Path(cpu_dir).is_dir(): |
| raise ValueError(f"{cpu_dir} does not exist") |
|
|
| print(f"k2 doc cpu_dir: {cpu_dir}") |
| return cpu_dir |
|
|
|
|
| def remove_all_files(d: str): |
| files = get_all_files(d, "*.rst") |
| for f in files: |
| print(f"removing {f}") |
| os.remove(f) |
|
|
|
|
| def get_all_cpu_wheels(): |
| cpu = get_all_files("macos", suffix="*.whl") |
| cpu_wheels = generate_url(cpu) |
| return cpu_wheels |
|
|
|
|
| def generate_file(d: str, torch_version: str, wheels: List[Wheel]) -> str: |
| s = f"torch {torch_version}\n" |
| s += "=" * len(f"torch {torch_version}") |
| s += "\n" * 3 |
| wheels = filter(lambda w: w.torch_version == torch_version, wheels) |
| wheels = list(wheels) |
| wheels.sort(reverse=True, key=sort_by_wheel) |
| for w in wheels: |
| s += f"- `{w.full_name} <{w.url}>`_\n" |
|
|
| with open(f"{d}/{torch_version}.rst", "w") as f: |
| f.write(s) |
|
|
|
|
| def main(): |
| d = get_doc_dir() |
| remove_all_files(d) |
|
|
| urls = get_all_cpu_wheels() |
|
|
| wheels = [] |
| for url in urls: |
| full_name = url.rsplit("/", maxsplit=1)[1] |
| wheels.append(Wheel(full_name, url)) |
| torch_versions = get_all_torch_versions(wheels) |
|
|
| content = [] |
| for t in torch_versions: |
| s = generate_file(d, t, wheels) |
|
|
| generate_index(f"{d}/index.rst", torch_versions) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
