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handle printing even if sys.stdout.buffer is not available (#887)
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@ -1,8 +1,7 @@
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import argparse
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import os
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import sys
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import warnings
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from typing import List, Optional, Tuple, Union, TYPE_CHECKING
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from typing import Optional, Tuple, Union, TYPE_CHECKING
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import numpy as np
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import torch
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@ -11,7 +10,7 @@ import tqdm
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from .audio import SAMPLE_RATE, N_FRAMES, HOP_LENGTH, pad_or_trim, log_mel_spectrogram
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from .decoding import DecodingOptions, DecodingResult
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from .tokenizer import LANGUAGES, TO_LANGUAGE_CODE, get_tokenizer
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from .utils import exact_div, format_timestamp, optional_int, optional_float, str2bool, get_writer
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from .utils import exact_div, format_timestamp, make_safe, optional_int, optional_float, str2bool, get_writer
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if TYPE_CHECKING:
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from .model import Whisper
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@ -166,11 +165,7 @@ def transcribe(
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}
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)
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if verbose:
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line = f"[{format_timestamp(start)} --> {format_timestamp(end)}] {text}\n"
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# compared to just `print(line)`, this replaces any character not representable using
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# the system default encoding with an '?', avoiding UnicodeEncodeError.
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sys.stdout.buffer.write(line.encode(sys.getdefaultencoding(), errors="replace"))
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sys.stdout.flush()
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print(make_safe(f"[{format_timestamp(start)} --> {format_timestamp(end)}] {text}"))
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# show the progress bar when verbose is False (otherwise the transcribed text will be printed)
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num_frames = mel.shape[-1]
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@ -1,8 +1,21 @@
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import json
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import os
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import sys
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import zlib
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from typing import Callable, TextIO
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system_encoding = sys.getdefaultencoding()
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if system_encoding != "utf-8":
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def make_safe(string):
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# replaces any character not representable using the system default encoding with an '?',
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# avoiding UnicodeEncodeError (https://github.com/openai/whisper/discussions/729).
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return string.encode(system_encoding, errors="replace").decode(system_encoding)
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else:
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def make_safe(string):
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# utf-8 can encode any Unicode code point, so no need to do the round-trip encoding
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return string
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def exact_div(x, y):
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assert x % y == 0
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