onxx export
import torchfrom mmpose.models.necks import ChannelMappermodel = ChannelMapper( in_channels=[256, 256], kernel_size=1, out_channels=384, act_cfg=None, norm_cfg=dict(type='BN'), num_outs=3)# Create dummy input tensor with appropriate shapeinputs = (torch.randn(1, 256, 32, 32), torch.randn(1, 256, 16, 16))dummy_input = (inputs,) # Wrap the inputs in an extra tuple# Test the mode..
2024.11.28