svlqd
3d48f473b0
- found problems with mps - integrated jinja2 templates for rendering (.tex?) - raw ui & bad structure
65 lines
1.7 KiB
Python
65 lines
1.7 KiB
Python
# from logging import Logger
|
|
import time
|
|
import torch
|
|
import gc
|
|
from transformers import WhisperForConditionalGeneration, WhisperProcessor
|
|
|
|
from transcription.engines.base_engine import BaseEngine
|
|
|
|
class WhisperEngine(BaseEngine):
|
|
def loadModel(self) -> None:
|
|
self.processor = WhisperProcessor.from_pretrained(self.modelName)
|
|
self.model = WhisperForConditionalGeneration.from_pretrained(
|
|
self.modelName,
|
|
torch_dtype = self.dType # check twice
|
|
).to(self.device) # ??? recheck
|
|
|
|
def unloadModel(self) -> None:
|
|
self.model = None
|
|
self.processor = None
|
|
|
|
# TODO: MPS?
|
|
if self.device == "cuda":
|
|
torch.cuda.empty_cache()
|
|
|
|
def transcribeBatch(
|
|
self,
|
|
batch,
|
|
) -> str:
|
|
assert self.processor is not None
|
|
assert self.model is not None
|
|
|
|
inputs = self.processor(
|
|
batch,
|
|
sampling_rate=16000,
|
|
return_tensors="pt",
|
|
padding=True,
|
|
)
|
|
|
|
input_features = inputs.input_features.to(self.device).to(self.dType)
|
|
|
|
with torch.no_grad():
|
|
predicted_ids = self.model.generate(
|
|
input_features,
|
|
language=self.language,
|
|
task="transcribe",
|
|
temperature=0.0,
|
|
)
|
|
|
|
batchText = self.processor.batch_decode(
|
|
predicted_ids,
|
|
skip_special_tokens=True,
|
|
)
|
|
|
|
inputs = None
|
|
input_features = None
|
|
predicted_ids = None
|
|
gc.collect()
|
|
|
|
# maybe do here something with MPS?
|
|
if self.device.startswith("cuda"):
|
|
torch.cuda.empty_cache()
|
|
torch.cuda.ipc_collect()
|
|
|
|
return " ".join(batchText)
|
|
|