add memory usage
Browse files- requirements.txt +2 -1
- visualizer_drag_gradio.py +21 -0
requirements.txt
CHANGED
@@ -4,4 +4,5 @@ Ninja
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gradio
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huggingface_hub
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hf_transfer
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-
Pillow==9.5.0
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gradio
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huggingface_hub
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hf_transfer
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Pillow==9.5.0
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psutil
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visualizer_drag_gradio.py
CHANGED
@@ -7,6 +7,8 @@ from functools import partial
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from pathlib import Path
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import time
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import gradio as gr
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import numpy as np
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import torch
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@@ -160,6 +162,24 @@ def preprocess_mask_info(global_state, image):
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return global_state
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# filter large models running on SPACES
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allowed_checkpoints = [] # all checkpoints
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if IS_SPACE:
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@@ -557,6 +577,7 @@ with gr.Blocks() as app:
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step_idx = 0
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last_time = time.time()
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while True:
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# add a TIMEOUT break
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print(f'Running time: {time.time() - last_time}')
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if IS_SPACE and time.time() - last_time > TIMEOUT:
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from pathlib import Path
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import time
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import psutil
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import gradio as gr
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import numpy as np
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import torch
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return global_state
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def print_memory_usage():
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# Print system memory usage
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print(f"System memory usage: {psutil.virtual_memory().percent}%")
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# Print GPU memory usage
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if torch.cuda.is_available():
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device = torch.device("cuda")
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print(f"GPU memory usage: {torch.cuda.memory_allocated() / 1e9} GB")
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print(
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f"Max GPU memory usage: {torch.cuda.max_memory_allocated() / 1e9} GB")
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device_properties = torch.cuda.get_device_properties(device)
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available_memory = device_properties.total_memory - \
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torch.cuda.max_memory_allocated()
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print(f"Available GPU memory: {available_memory / 1e9} GB")
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else:
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print("No GPU available")
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# filter large models running on SPACES
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allowed_checkpoints = [] # all checkpoints
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if IS_SPACE:
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step_idx = 0
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last_time = time.time()
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while True:
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print_memory_usage()
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# add a TIMEOUT break
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print(f'Running time: {time.time() - last_time}')
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if IS_SPACE and time.time() - last_time > TIMEOUT:
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