38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
import logging
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import time
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import numpy as np
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import habana_frameworks.torch.core as ht
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import torch
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from PIL import Image
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import clip
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from clip.utils import get_device_initial
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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def run_model(model_name, device):
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model, transform = clip.load(model_name, device=get_device_initial(device), jit=False)
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image = transform(Image.open("CLIP.png")).unsqueeze(0).to(device)
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text = clip.tokenize(["a diagram", "a dog", "a cat"]).to(device)
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with torch.no_grad():
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logits_per_image, _ = model(image, text)
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probs = logits_per_image.softmax(dim=-1).cpu().numpy()
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return probs
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if __name__ == "__main__":
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logger.info("Running on HPU")
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start_time = time.time()
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run_model("RN50", "hpu")
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end_time = time.time()
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logger.info(f"HPU execution time: {end_time - start_time:.4f} seconds")
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logger.info("Running on CPU")
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start_time = time.time()
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run_model("RN50", "cpu")
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end_time = time.time()
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logger.info(f"CPU execution time: {end_time - start_time:.4f} seconds")
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