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Update transcribe.py

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Alexander Kuznetsov 2024-11-01 20:33:52 +03:00 committed by GitHub
parent 80ddd07c28
commit 482a5b89d8
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1 changed files with 18 additions and 5 deletions
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whisper/transcribe.py
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@ -76,8 +76,8 @@ def transcribe(
compression_ratio_threshold: float compression_ratio_threshold: float
If the gzip compression ratio is above this value, treat as failed If the gzip compression ratio is above this value, treat as failed
compression_ratio_hallucination_threshold: float compression_ratio_halcination_threshold: float
If the gzip compression ratio is above this value after all attempts to decode, treat as a halucination and skip If the gzip compression ratio is above this value after all attempts to decode, treat as a hallucination and skip
logprob_threshold: float logprob_threshold: float
If the average log probability over sampled tokens is below this value, treat as failed If the average log probability over sampled tokens is below this value, treat as failed
@ -106,6 +106,11 @@ def transcribe(
"prompt-engineer" a context for transcription, e.g. custom vocabularies or proper nouns "prompt-engineer" a context for transcription, e.g. custom vocabularies or proper nouns
to make it more likely to predict those word correctly. to make it more likely to predict those word correctly.
carry_initial_prompt: bool
If carry_initial_prompt is True, `initial_prompt` is prepended to the prompt of each internal
`decode()` call. If there is not enough context space at the start of the prompt, it is
left-sliced to make space.
decode_options: dict decode_options: dict
Keyword arguments to construct `DecodingOptions` instances Keyword arguments to construct `DecodingOptions` instances
@ -221,8 +226,6 @@ def transcribe(
): ):
# Discard the segment # Discard the segment
continue # Skip to the next segment continue # Skip to the next segment
if not needs_fallback: if not needs_fallback:
break break
@ -240,9 +243,11 @@ def transcribe(
all_segments = [] all_segments = []
prompt_reset_since = 0 prompt_reset_since = 0
remaining_prompt_length = model.dims.n_text_ctx // 2 - 1
if initial_prompt is not None: if initial_prompt is not None:
initial_prompt_tokens = tokenizer.encode(" " + initial_prompt.strip()) initial_prompt_tokens = tokenizer.encode(" " + initial_prompt.strip())
all_tokens.extend(initial_prompt_tokens) all_tokens.extend(initial_prompt_tokens)
remaining_prompt_length -= len(initial_prompt_tokens)
else: else:
initial_prompt_tokens = [] initial_prompt_tokens = []
@ -288,7 +293,13 @@ def transcribe(
segment_duration = segment_size * HOP_LENGTH / SAMPLE_RATE segment_duration = segment_size * HOP_LENGTH / SAMPLE_RATE
mel_segment = pad_or_trim(mel_segment, N_FRAMES).to(model.device).to(dtype) mel_segment = pad_or_trim(mel_segment, N_FRAMES).to(model.device).to(dtype)
if carry_initial_prompt:
nignored = max(len(initial_prompt_tokens), prompt_reset_since)
remaining_prompt = all_tokens[nignored:][-remaining_prompt_length:]
decode_options["prompt"] = initial_prompt_tokens + remaining_prompt
else:
decode_options["prompt"] = all_tokens[prompt_reset_since:] decode_options["prompt"] = all_tokens[prompt_reset_since:]
result: DecodingResult = decode_with_fallback(mel_segment) result: DecodingResult = decode_with_fallback(mel_segment)
tokens = torch.tensor(result.tokens) tokens = torch.tensor(result.tokens)
@ -542,6 +553,8 @@ def cli():
parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations") parser.add_argument("--suppress_tokens", type=str, default="-1", help="comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations")
parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.") parser.add_argument("--initial_prompt", type=str, default=None, help="optional text to provide as a prompt for the first window.")
parser.add_argument("--carry_initial_prompt", type=str2bool, default=False, help="if True, prepend initial_prompt to every internal decode() call. May reduce the effectiveness of condition_on_previous_text")
parser.add_argument("--condition_on_previous_text", type=str2bool, default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop") parser.add_argument("--condition_on_previous_text", type=str2bool, default=True, help="if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop")
parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default") parser.add_argument("--fp16", type=str2bool, default=True, help="whether to perform inference in fp16; True by default")