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# Ultralytics YOLO 🚀, AGPL-3.0 license
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"""
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Ultralytics modules. Visualize with:
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from ultralytics.nn.modules import *
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import torch
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import os
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x = torch.ones(1, 128, 40, 40)
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m = Conv(128, 128)
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f = f'{m._get_name()}.onnx'
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torch.onnx.export(m, x, f)
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os.system(f'onnxsim {f} {f} && open {f}')
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"""
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from .block import (C1, C2, C3, C3TR, DFL, SPP, SPPF, Bottleneck, BottleneckCSP, C2f, C3Ghost, C3x, GhostBottleneck,
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HGBlock, HGStem, Proto, RepC3)
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from .conv import (CBAM, ChannelAttention, Concat, Conv, Conv2, ConvTranspose, DWConv, DWConvTranspose2d, Focus,
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GhostConv, LightConv, RepConv, SpatialAttention)
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from .head import Classify, Detect, Pose, RTDETRDecoder, Segment
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from .transformer import (AIFI, MLP, DeformableTransformerDecoder, DeformableTransformerDecoderLayer, LayerNorm2d,
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MLPBlock, MSDeformAttn, TransformerBlock, TransformerEncoderLayer, TransformerLayer)
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__all__ = [
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'Conv', 'Conv2', 'LightConv', 'RepConv', 'DWConv', 'DWConvTranspose2d', 'ConvTranspose', 'Focus', 'GhostConv',
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'ChannelAttention', 'SpatialAttention', 'CBAM', 'Concat', 'TransformerLayer', 'TransformerBlock', 'MLPBlock',
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'LayerNorm2d', 'DFL', 'HGBlock', 'HGStem', 'SPP', 'SPPF', 'C1', 'C2', 'C3', 'C2f', 'C3x', 'C3TR', 'C3Ghost',
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'GhostBottleneck', 'Bottleneck', 'BottleneckCSP', 'Proto', 'Detect', 'Segment', 'Pose', 'Classify',
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'TransformerEncoderLayer', 'RepC3', 'RTDETRDecoder', 'AIFI', 'DeformableTransformerDecoder',
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'DeformableTransformerDecoderLayer', 'MSDeformAttn', 'MLP']
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