mirror of https://github.com/hpcaitech/ColossalAI
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
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import torch
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import transformers
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from ..registry import ModelAttribute, model_zoo
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# ===============================
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# Register single-image SAM
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# ===============================
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# define data gen function
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def data_gen():
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# Generated from following code snippet
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#
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# from PIL import Image
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# import requests
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# from transformers import SamModel, SamProcessor
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#
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# model = SamModel.from_pretrained("facebook/sam-vit-base")
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# processor = SamProcessor.from_pretrained("facebook/sam-vit-base")
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#
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# img_url = "https://huggingface.co/ybelkada/segment-anything/resolve/main/assets/car.png"
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# raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB")
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# input_points = [[[450, 600]]] # 2D localization of a window
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# inputs = processor(raw_image, input_points=input_points, return_tensors="pt")
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pixel_values = torch.rand(1, 3, 1024, 1024, dtype=torch.float32)
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original_sizes = torch.tensor([[1764, 2646]], dtype=torch.int64)
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reshaped_input_sizes = torch.tensor([[683, 1024]], dtype=torch.int64)
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input_points = torch.tensor([[[[174.1497, 232.3129]]]], dtype=torch.float64)
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return dict(pixel_values=pixel_values,
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original_sizes=original_sizes,
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reshaped_input_sizes=reshaped_input_sizes,
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input_points=input_points)
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# define output transform function
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output_transform_fn = lambda x: x
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# define loss funciton
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loss_fn = lambda x: x.iou_scores.mean()
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config = transformers.SamConfig()
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config.vision_config.num_hidden_layers = 2
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# register the BERT variants
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model_zoo.register(name='transformers_sam',
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model_fn=lambda: transformers.SamModel(config),
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data_gen_fn=data_gen,
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output_transform_fn=output_transform_fn,
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loss_fn=loss_fn,
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model_attribute=ModelAttribute(has_control_flow=True))
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