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Update subgen.py

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Cleaned up garbage collection so vram is released when the transcode queue is empty.
This commit is contained in:
McCloudS
2023-10-26 22:57:14 -06:00
committed by GitHub
parent 036dd9a7c2
commit 42bf55f203
1 changed files with 7 additions and 1 deletions
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8
subgen/subgen.py
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@@ -7,6 +7,7 @@ import sys
import time import time
import queue import queue
import logging import logging
import gc
from array import array from array import array
# List of packages to install # List of packages to install
@@ -66,7 +67,7 @@ if transcribe_device == "gpu":
jellyfin_userid = "" jellyfin_userid = ""
app = Flask(__name__) app = Flask(__name__)
model = stable_whisper.load_faster_whisper(whisper_model, download_root=model_location, device=transcribe_device, cpu_threads=whisper_threads, num_workers=concurrent_transcriptions) model = None
files_to_transcribe = [] files_to_transcribe = []
subextension = '.subgen.' + whisper_model + '.' + namesublang + '.srt' subextension = '.subgen.' + whisper_model + '.' + namesublang + '.srt'
print("Transcriptions are limited to running " + str(concurrent_transcriptions) + " at a time") print("Transcriptions are limited to running " + str(concurrent_transcriptions) + " at a time")
@@ -179,6 +180,7 @@ def gen_subtitles(video_file_path: str) -> None:
try: try:
print(f"Transcribing file: {video_file_path}") print(f"Transcribing file: {video_file_path}")
start_time = time.time() start_time = time.time()
model = stable_whisper.load_faster_whisper(whisper_model, download_root=model_location, device=transcribe_device, cpu_threads=whisper_threads, num_workers=concurrent_transcriptions)
result = model.transcribe_stable(video_file_path, task=transcribe_or_translate) result = model.transcribe_stable(video_file_path, task=transcribe_or_translate)
result.to_srt_vtt(video_file_path.rsplit('.', 1)[0] + subextension, word_level=word_level_highlight) result.to_srt_vtt(video_file_path.rsplit('.', 1)[0] + subextension, word_level=word_level_highlight)
elapsed_time = time.time() - start_time elapsed_time = time.time() - start_time
@@ -188,6 +190,10 @@ def gen_subtitles(video_file_path: str) -> None:
print(f"Error processing or transcribing {video_file_path}: {e}") print(f"Error processing or transcribing {video_file_path}: {e}")
finally: finally:
files_to_transcribe.remove(video_file_path) files_to_transcribe.remove(video_file_path)
if len(files_to_transcribe) == 0:
logging.debug("Queue is empty, clearing/releasing VRAM")
del model
gc.collect()
# Function to add a file for transcription # Function to add a file for transcription
def add_file_for_transcription(file_path, front=True): def add_file_for_transcription(file_path, front=True):