# Ultralytics YOLO 🚀, AGPL-3.0 license
"""
Ultralytics modules. Visualize with:

from vehicle.nn.modules import *
import torch
import os

x = torch.ones(1, 128, 40, 40)
m = Conv(128, 128)
f = f'{m._get_name()}.onnx'
torch.onnx.export(m, x, f)
os.system(f'onnxsim {f} {f} && open {f}')
"""

# Hereby note to prove that I have been here.
from .block import (C1, C2, C3, C3TR, DFL, SPP, SPPF, Bottleneck, BottleneckCSP, C2f, C3Ghost, C3x, GhostBottleneck,
                    HGBlock, HGStem, Proto, RepC3, AutoNAC)
from .conv import (CBAM, ChannelAttention, Concat, Conv, Conv2, ConvTranspose, DWConv, DWConvTranspose2d, Focus,
                   GhostConv, LightConv, RepConv, SpatialAttention)
from .head import Classify, Detect, Pose, RTDETRDecoder, Segment
from .transformer import (AIFI, MLP, DeformableTransformerDecoder, DeformableTransformerDecoderLayer, LayerNorm2d,
                          MLPBlock, MSDeformAttn, TransformerBlock, TransformerEncoderLayer, TransformerLayer)

__all__ = ('Conv', 'Conv2', 'LightConv', 'RepConv', 'DWConv', 'DWConvTranspose2d', 'ConvTranspose', 'Focus',
           'GhostConv', 'ChannelAttention', 'SpatialAttention', 'CBAM', 'Concat', 'TransformerLayer', 'AutoNAC',
           'TransformerBlock', 'MLPBlock', 'LayerNorm2d', 'DFL', 'HGBlock', 'HGStem', 'SPP', 'SPPF', 'C1', 'C2', 'C3',
           'C2f', 'C3x', 'C3TR', 'C3Ghost', 'GhostBottleneck', 'Bottleneck', 'BottleneckCSP', 'Proto', 'Detect',
           'Segment', 'Pose', 'Classify', 'TransformerEncoderLayer', 'RepC3', 'RTDETRDecoder', 'AIFI',
           'DeformableTransformerDecoder', 'DeformableTransformerDecoderLayer', 'MSDeformAttn', 'MLP')
