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Runtime error
Ruslan Magana Vsevolodovna
commited on
Commit
•
4b68d40
1
Parent(s):
2cc68f0
fixing gpu
Browse files- app.py +15 -17
- requirements.txt +5 -3
app.py
CHANGED
@@ -3,15 +3,12 @@ from moviepy.editor import *
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from PIL import Image
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM,pipeline
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import gradio as gr
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import torch
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from huggingface_hub import snapshot_download
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from PIL import Image
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from min_dalle import MinDalle
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import
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from PIL import Image, ImageDraw, ImageFont
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import textwrap
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from mutagen.mp3 import MP3
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# to speech conversion
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from gtts import gTTS
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from pydub import AudioSegment
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from os import getcwd
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@@ -23,13 +20,14 @@ title = "Video Story Generator with Audio by using dalle-mini and distilbart and
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tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-6")
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model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-12-6")
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#device = "cuda:0" if torch.cuda.is_available() else "cpu"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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print(device)
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-
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-
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-
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def get_output_video(text):
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inputs = tokenizer(text,
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@@ -62,13 +60,12 @@ def get_output_video(text):
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model = MinDalle(
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is_mega=is_mega,
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models_root=models_root,
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is_reusable=
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is_verbose=True,
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#dtype=torch.float16,
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device='cpu' #'cuda'
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)
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image = model.generate_image(
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text,
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@@ -86,11 +83,12 @@ def get_output_video(text):
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is_mega= True,
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text=senten,
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seed=1,
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grid_size=1,
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top_k=
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image_path='generated',
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models_root='pretrained',
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fp16=256,)
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generated_images.append(image)
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# Step 4- Creation of the subtitles
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from PIL import Image
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM,pipeline
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import gradio as gr
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import torch, torch.backends.cudnn, torch.backends.cuda
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from min_dalle import MinDalle
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from huggingface_hub import snapshot_download
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from PIL import Image, ImageDraw, ImageFont
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import textwrap
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from mutagen.mp3 import MP3
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from gtts import gTTS
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from pydub import AudioSegment
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from os import getcwd
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tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-6")
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model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-12-6")
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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print(device)
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def log_gpu_memory():
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print(subprocess.check_output('nvidia-smi').decode('utf-8'))
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log_gpu_memory()
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def get_output_video(text):
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inputs = tokenizer(text,
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model = MinDalle(
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is_mega=is_mega,
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models_root=models_root,
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is_reusable=True,
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is_verbose=True,
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dtype=torch.float16 if fp16 else torch.float32 #param ["float32", "float16", "bfloat16"] #float32 is faster than float16 but uses more GPU memory.
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device='cuda' #'cpu'
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)
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log_gpu_memory()
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image = model.generate_image(
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text,
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is_mega= True,
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text=senten,
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seed=1,
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grid_size=1, #param {type:"integer"}
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top_k=128, #param {type:"integer"}
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image_path='generated',
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models_root='pretrained',
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fp16=256,)
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generated_images.append(image)
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# Step 4- Creation of the subtitles
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requirements.txt
CHANGED
@@ -1,7 +1,7 @@
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gradio
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min-dalle
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transformers
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torch
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requests
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moviepy
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huggingface_hub
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@@ -12,4 +12,6 @@ gTTS
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mutagen
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nltk
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accelerate
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nvidia-ml-py3
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min-dalle==0.4.6
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emoji==1.7.0
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gradio
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transformers
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requests
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moviepy
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huggingface_hub
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mutagen
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nltk
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accelerate
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nvidia-ml-py3
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--find-links https://download.pytorch.org/whl/torch_stable.html
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torch==1.12.1+cu116
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