def get_from_cache(url, cache_dir=None):
    """
    Given a URL, look for the corresponding dataset in the local cache.
    If it's not there, download it. Then return the path to the cached file.
    """
    if cache_dir is None:
        cache_dir = PYTORCH_FAIRSEQ_CACHE
    if isinstance(cache_dir, Path):
        cache_dir = str(cache_dir)

    if not os.path.exists(cache_dir):
        os.makedirs(cache_dir)

    # Get eTag to add to filename, if it exists.
    if url.startswith("s3://"):
        etag = s3_etag(url)
    else:
        try:
            import requests

            response = request_wrap_timeout(
                partial(requests.head, url, allow_redirects=True), url
            )
            if response.status_code != 200:
                etag = None
            else:
                etag = response.headers.get("ETag")
        except RuntimeError:
            etag = None

    filename = url_to_filename(url, etag)

    # get cache path to put the file
    cache_path = os.path.join(cache_dir, filename)

    # If we don't have a connection (etag is None) and can't identify the file
    # try to get the last downloaded one
    if not os.path.exists(cache_path) and etag is None:
        matching_files = fnmatch.filter(os.listdir(cache_dir), filename + ".*")
        matching_files = list(filter(lambda s: not s.endswith(".json"), matching_files))
        if matching_files:
            cache_path = os.path.join(cache_dir, matching_files[-1])

    if not os.path.exists(cache_path):
        # Download to temporary file, then copy to cache dir once finished.
        # Otherwise you get corrupt cache entries if the download gets interrupted.
        with tempfile.NamedTemporaryFile() as temp_file:
            logger.info("%s not found in cache, downloading to %s", url, temp_file.name)

            # GET file object
            if url.startswith("s3://"):
                s3_get(url, temp_file)
            else:
                http_get(url, temp_file)

            # we are copying the file before closing it, so flush to avoid truncation
            temp_file.flush()
            # shutil.copyfileobj() starts at the current position, so go to the start
            temp_file.seek(0)

            logger.info("copying %s to cache at %s", temp_file.name, cache_path)
            with open(cache_path, "wb") as cache_file:
                shutil.copyfileobj(temp_file, cache_file)

            logger.info("creating metadata file for %s", cache_path)
            meta = {"url": url, "etag": etag}
            meta_path = cache_path + ".json"
            with open(meta_path, "w") as meta_file:
                output_string = json.dumps(meta)
                meta_file.write(output_string)

            logger.info("removing temp file %s", temp_file.name)

    return cache_path
Given a URL, look for the corresponding dataset in the local cache.
If it's not there, download it. Then return the path to the cached file.
fairseq/file_utils.py