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| from dataclasses import dataclass, fields | |
| import gradio as gr | |
| class WhisperGradioComponents: | |
| model_size: gr.Dropdown | |
| lang: gr.Dropdown | |
| is_translate: gr.Checkbox | |
| beam_size: gr.Number | |
| log_prob_threshold: gr.Number | |
| no_speech_threshold: gr.Number | |
| compute_type: gr.Dropdown | |
| best_of: gr.Number | |
| patience: gr.Number | |
| """ | |
| A data class to pass Gradio components to the function before Gradio pre-processing. | |
| See this documentation for more information about Gradio pre-processing: https://www.gradio.app/docs/components | |
| Attributes | |
| ---------- | |
| model_size: gr.Dropdown | |
| Whisper model size. | |
| lang: gr.Dropdown | |
| Source language of the file to transcribe. | |
| is_translate: gr.Checkbox | |
| Boolean value that determines whether to translate to English. | |
| It's Whisper's feature to translate speech from another language directly into English end-to-end. | |
| beam_size: gr.Number | |
| Int value that is used for decoding option. | |
| log_prob_threshold: gr.Number | |
| If the average log probability over sampled tokens is below this value, treat as failed. | |
| no_speech_threshold: gr.Number | |
| If the no_speech probability is higher than this value AND | |
| the average log probability over sampled tokens is below `log_prob_threshold`, | |
| consider the segment as silent. | |
| compute_type: gr.Dropdown | |
| compute type for transcription. | |
| see more info : https://opennmt.net/CTranslate2/quantization.html | |
| best_of: gr.Number | |
| Number of candidates when sampling with non-zero temperature. | |
| patience: gr.Number | |
| Beam search patience factor. | |
| """ | |
| def to_list(self) -> list: | |
| """ | |
| Converts the data class attributes into a list, to pass parameters to a function before Gradio pre-processing. | |
| Returns | |
| ---------- | |
| A list of Gradio components | |
| """ | |
| return [getattr(self, f.name) for f in fields(self)] | |
| def to_values(*params): | |
| """ | |
| Convert a tuple of parameters into a WhisperValues data class, to use parameters in a function after Gradio pre-processing. | |
| Parameters | |
| ---------- | |
| *params: tuple | |
| This is provided in a tuple because Gradio does not support **kwargs arbitrary. | |
| Reference : https://discuss.huggingface.co/t/passing-an-additional-argument-to-a-function/25140/2 | |
| Returns | |
| ---------- | |
| A WhisperValues data class | |
| """ | |
| return WhisperValues(*params) | |
| class WhisperValues: | |
| model_size: str | |
| lang: str | |
| is_translate: bool | |
| beam_size: int | |
| log_prob_threshold: float | |
| no_speech_threshold: float | |
| compute_type: str | |
| best_of: int | |
| patience: float | |
| """ | |
| A data class to use Whisper parameters in the function after Gradio pre-processing. | |
| See this documentation for more information about Gradio pre-processing: : https://www.gradio.app/docs/components | |
| """ | |