benchmarks/rnnt/ootb/inference/pytorch/utils/download_utils.py [24:52]:
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def download_file(url, dest_folder, fname, overwrite=False):
    fpath = os.path.join(dest_folder, fname)
    if os.path.isfile(fpath):
        if overwrite:
            print("Overwriting existing file")
        else:
            print("File exists, skipping download.")
            return

    tmp_fpath = fpath + '.tmp'

    r = requests.get(url, stream=True)
    file_size = int(r.headers['Content-Length'])
    chunk_size = 1024 * 1024  # 1MB
    total_chunks = int(file_size / chunk_size)

    with open(tmp_fpath, 'wb') as fp:
        content_iterator = r.iter_content(chunk_size=chunk_size)
        chunks = tqdm.tqdm(content_iterator, total=total_chunks,
                           unit='MB', desc=fpath, leave=True)
        for chunk in chunks:
            fp.write(chunk)

    os.rename(tmp_fpath, fpath)


def md5_checksum(fpath, target_hash):
    file_hash = hashlib.md5()
    with open(fpath, "rb") as fp:
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benchmarks/rnnt/ootb/train/utils/download_utils.py [23:51]:
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def download_file(url, dest_folder, fname, overwrite=False):
    fpath = os.path.join(dest_folder, fname)
    if os.path.isfile(fpath):
        if overwrite:
            print("Overwriting existing file")
        else:
            print("File exists, skipping download.")
            return

    tmp_fpath = fpath + '.tmp'

    r = requests.get(url, stream=True)
    file_size = int(r.headers['Content-Length'])
    chunk_size = 1024 * 1024  # 1MB
    total_chunks = int(file_size / chunk_size)

    with open(tmp_fpath, 'wb') as fp:
        content_iterator = r.iter_content(chunk_size=chunk_size)
        chunks = tqdm.tqdm(content_iterator, total=total_chunks,
                           unit='MB', desc=fpath, leave=True)
        for chunk in chunks:
            fp.write(chunk)

    os.rename(tmp_fpath, fpath)


def md5_checksum(fpath, target_hash):
    file_hash = hashlib.md5()
    with open(fpath, "rb") as fp:
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