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147
ultralytics/nn/modules/__init__.py
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147
ultralytics/nn/modules/__init__.py
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# Ultralytics YOLO 🚀, AGPL-3.0 license
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"""
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Ultralytics modules.
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Example:
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Visualize a module with Netron.
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```python
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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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"""
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from .block import (
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C1,
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C2,
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C3,
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C3TR,
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DFL,
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SPP,
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SPPF,
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Bottleneck,
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BottleneckCSP,
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C2f,
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C2fAttn,
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ImagePoolingAttn,
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C3Ghost,
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C3x,
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GhostBottleneck,
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HGBlock,
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HGStem,
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Proto,
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RepC3,
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ResNetLayer,
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ContrastiveHead,
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BNContrastiveHead,
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RepNCSPELAN4,
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ADown,
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SPPELAN,
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CBFuse,
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CBLinear,
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Silence,
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PSA,
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C2fCIB,
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SCDown,
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RepVGGDW
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)
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from .conv import (
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CBAM,
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ChannelAttention,
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Concat,
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Conv,
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Conv2,
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ConvTranspose,
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DWConv,
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DWConvTranspose2d,
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Focus,
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GhostConv,
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LightConv,
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RepConv,
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SpatialAttention,
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)
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from .head import OBB, Classify, Detect, Pose, RTDETRDecoder, Segment, WorldDetect, v10Detect
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from .transformer import (
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AIFI,
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MLP,
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DeformableTransformerDecoder,
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DeformableTransformerDecoderLayer,
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LayerNorm2d,
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MLPBlock,
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MSDeformAttn,
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TransformerBlock,
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TransformerEncoderLayer,
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TransformerLayer,
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)
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__all__ = (
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"Conv",
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"Conv2",
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"LightConv",
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"RepConv",
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"DWConv",
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"DWConvTranspose2d",
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"ConvTranspose",
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"Focus",
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"GhostConv",
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"ChannelAttention",
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"SpatialAttention",
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"CBAM",
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"Concat",
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"TransformerLayer",
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"TransformerBlock",
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"MLPBlock",
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"LayerNorm2d",
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"DFL",
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"HGBlock",
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"HGStem",
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"SPP",
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"SPPF",
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"C1",
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"C2",
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"C3",
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"C2f",
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"C2fAttn",
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"C3x",
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"C3TR",
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"C3Ghost",
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"GhostBottleneck",
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"Bottleneck",
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"BottleneckCSP",
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"Proto",
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"Detect",
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"Segment",
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"Pose",
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"Classify",
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"TransformerEncoderLayer",
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"RepC3",
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"RTDETRDecoder",
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"AIFI",
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"DeformableTransformerDecoder",
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"DeformableTransformerDecoderLayer",
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"MSDeformAttn",
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"MLP",
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"ResNetLayer",
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"OBB",
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"WorldDetect",
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"ImagePoolingAttn",
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"ContrastiveHead",
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"BNContrastiveHead",
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"RepNCSPELAN4",
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"ADown",
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"SPPELAN",
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"CBFuse",
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"CBLinear",
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"Silence",
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"PSA",
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"C2fCIB",
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"SCDown",
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"RepVGGDW",
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"v10Detect"
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)
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