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import os |
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import re |
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from collections import defaultdict |
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from pathlib import Path |
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from typing import Dict, List, Tuple |
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from update_readme import generate_url, get_all_files |
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class Wheel: |
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def __init__(self, full_name: str, url: str): |
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""" |
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Args: |
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full_name: |
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Example: k2-1.23.4.dev20230223+cpu.torch1.10.0-cp36-cp36m-linux_x86_64.whl |
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""" |
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self.full_name = full_name |
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pattern = ( |
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r"k2-(\d)\.(\d)+((\.)(\d))?\.dev(\d{8})\+cpu\.torch(\d\.\d+\.\d)-cp(\d+)" |
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) |
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m = re.search(pattern, full_name) |
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self.k2_major = int(m.group(1)) |
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self.k2_minor = int(m.group(2)) |
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self.k2_patch = int(m.group(5)) |
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self.k2_date = int(m.group(6)) |
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self.torch_version = m.group(7) |
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self.py_version = int(m.group(8)) |
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self.url = url |
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def __str__(self): |
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return self.url |
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def __repr__(self): |
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return self.url |
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def generate_index(filename: str, torch_versions) -> str: |
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b = [] |
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for i in torch_versions: |
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b.append(f" ./{i}.rst") |
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b = "\n".join(b) |
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s = f"""\ |
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Pre-compiled CPU wheels (Linux) |
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=============================== |
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This page describes pre-compiled ``CPU`` wheels for `k2`_ on Linux. |
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.. toctree:: |
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:maxdepth: 2 |
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{b} |
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""" |
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with open(filename, "w") as f: |
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f.write(s) |
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def sort_by_wheel(x: Wheel): |
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return x.k2_major, x.k2_minor, x.k2_patch, x.k2_date, x.py_version |
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def sort_by_torch(x): |
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major, minor, patch = x.split(".") |
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return int(major), int(minor), int(patch) |
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def get_all_torch_versions(wheels: List[Wheel]) -> List[str]: |
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ans = set() |
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for w in wheels: |
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ans.add(w.torch_version) |
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ans = list(ans) |
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ans.sort(reverse=True, key=sort_by_torch) |
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return ans |
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def get_doc_dir(): |
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k2_dir = os.getenv("K2_DIR") |
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if k2_dir is None: |
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raise ValueError("Please set the environment variable k2_dir") |
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cpu_dir = Path(k2_dir) / "docs/source/installation/pre-compiled-cpu-wheels" |
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if not Path(cpu_dir).is_dir(): |
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raise ValueError(f"{cpu_dir} does not exist") |
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print(f"k2 doc cpu_dir: {cpu_dir}") |
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return cpu_dir |
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def remove_all_files(d: str): |
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files = get_all_files(d, "*.rst") |
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for f in files: |
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print(f"removing {f}") |
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os.remove(f) |
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def get_all_cpu_wheels(): |
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cpu = get_all_files("cpu", suffix="*.whl") |
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cpu_wheels = generate_url(cpu) |
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return cpu_wheels |
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def generate_file(d: str, torch_version: str, wheels: List[Wheel]) -> str: |
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s = f"troch {torch_version}\n" |
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s += "=" * len(f"torch {torch_version}") |
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s += "\n" * 3 |
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wheels = filter(lambda w: w.torch_version == torch_version, wheels) |
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wheels = list(wheels) |
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wheels.sort(reverse=True, key=sort_by_wheel) |
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for w in wheels: |
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s += f"- `{w.full_name} <{w.url}>`_\n" |
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with open(f"{d}/{torch_version}.rst", "w") as f: |
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f.write(s) |
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def main(): |
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d = get_doc_dir() |
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remove_all_files(d) |
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urls = get_all_cpu_wheels() |
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wheels = [] |
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for url in urls: |
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full_name = url.rsplit("/", maxsplit=1)[1] |
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wheels.append(Wheel(full_name, url)) |
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torch_versions = get_all_torch_versions(wheels) |
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content = [] |
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for t in torch_versions: |
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s = generate_file(d, t, wheels) |
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generate_index(f"{d}/index.rst", torch_versions) |
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if __name__ == "__main__": |
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main() |
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