Remove torchvision import
Browse files
app.py
CHANGED
@@ -4,8 +4,6 @@ os.system('pip install git+https://github.com/huggingface/transformers.git --upg
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import gradio as gr
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from transformers import ViTFeatureExtractor, ViTModel
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import torch
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import torch.nn as nn
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import torchvision
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import matplotlib.pyplot as plt
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torch.hub.download_url_to_file('http://images.cocodataset.org/val2017/000000039769.jpg', 'cats.jpg')
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@@ -25,10 +23,10 @@ def get_attention_maps(pixel_values, attentions, nh):
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th_attn[head] = th_attn[head][idx2[head]]
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th_attn = th_attn.reshape(nh, w_featmap, h_featmap).float()
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# interpolate
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th_attn = nn.functional.interpolate(th_attn.unsqueeze(0), scale_factor=model.config.patch_size, mode="nearest")[0].cpu().numpy()
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attentions = attentions.reshape(nh, w_featmap, h_featmap)
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attentions = nn.functional.interpolate(attentions.unsqueeze(0), scale_factor=model.config.patch_size, mode="nearest")[0].cpu()
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attentions = attentions.detach().numpy()
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# save attentions heatmaps and return list of filenames
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import gradio as gr
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from transformers import ViTFeatureExtractor, ViTModel
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import torch
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import matplotlib.pyplot as plt
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torch.hub.download_url_to_file('http://images.cocodataset.org/val2017/000000039769.jpg', 'cats.jpg')
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th_attn[head] = th_attn[head][idx2[head]]
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th_attn = th_attn.reshape(nh, w_featmap, h_featmap).float()
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# interpolate
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th_attn = torch.nn.functional.interpolate(th_attn.unsqueeze(0), scale_factor=model.config.patch_size, mode="nearest")[0].cpu().numpy()
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attentions = attentions.reshape(nh, w_featmap, h_featmap)
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attentions = torch.nn.functional.interpolate(attentions.unsqueeze(0), scale_factor=model.config.patch_size, mode="nearest")[0].cpu()
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attentions = attentions.detach().numpy()
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# save attentions heatmaps and return list of filenames
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