Failure when testing my own trained model

[firasguediri]

File "test.py", line 19, in
model = Pix2PixModel(opt)
File "/content/drive/My Drive/SPADE/SPADE/models/pix2pix_model.py", line 25, in init
self.netG, self.netD, self.netE = self.initialize_networks(opt)
File "/content/drive/My Drive/SPADE/SPADE/models/pix2pix_model.py", line 96, in initialize_networks
netG = util.load_network(netG, 'G', opt.which_epoch, opt)
File "/content/drive/My Drive/SPADE/SPADE/util/util.py", line 208, in load_network
net.load_state_dict(weights)
File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 1045, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for SPADEGenerator:
size mismatch for fc.weight: copying a param with shape torch.Size([768, 39, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 39, 3, 3]).
size mismatch for fc.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.conv_0.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.conv_0.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for head_0.conv_0.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.conv_0.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for head_0.conv_1.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.conv_1.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for head_0.conv_1.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.conv_1.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for head_0.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for head_0.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_0.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for head_0.norm_0.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for head_0.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for head_0.norm_1.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for head_0.norm_1.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.conv_0.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.conv_0.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for G_middle_0.conv_0.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.conv_0.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for G_middle_0.conv_1.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.conv_1.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for G_middle_0.conv_1.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.conv_1.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for G_middle_0.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_0.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_0.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_0.norm_0.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_0.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_0.norm_1.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_0.norm_1.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.conv_0.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.conv_0.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for G_middle_1.conv_0.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.conv_0.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for G_middle_1.conv_1.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.conv_1.weight_orig: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for G_middle_1.conv_1.weight_u: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.conv_1.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for G_middle_1.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_1.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_0.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_1.norm_0.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_1.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for G_middle_1.norm_1.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for G_middle_1.norm_1.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.conv_0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.conv_0.weight_orig: copying a param with shape torch.Size([384, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 1024, 3, 3]).
size mismatch for up_0.conv_0.weight_u: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.conv_0.weight_v: copying a param with shape torch.Size([6912]) from checkpoint, the shape in current model is torch.Size([9216]).
size mismatch for up_0.conv_1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.conv_1.weight_orig: copying a param with shape torch.Size([384, 384, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
size mismatch for up_0.conv_1.weight_u: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.conv_1.weight_v: copying a param with shape torch.Size([3456]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for up_0.conv_s.weight_orig: copying a param with shape torch.Size([384, 768, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 1024, 1, 1]).
size mismatch for up_0.conv_s.weight_u: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.conv_s.weight_v: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for up_0.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_0.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for up_0.norm_0.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_0.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.norm_1.mlp_beta.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_0.norm_1.mlp_beta.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_0.norm_s.param_free_norm.running_mean: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_s.param_free_norm.running_var: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_s.mlp_gamma.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for up_0.norm_s.mlp_gamma.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_0.norm_s.mlp_beta.weight: copying a param with shape torch.Size([768, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 128, 3, 3]).
size mismatch for up_0.norm_s.mlp_beta.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]).
size mismatch for up_1.conv_0.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.conv_0.weight_orig: copying a param with shape torch.Size([192, 384, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]).
size mismatch for up_1.conv_0.weight_u: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.conv_0.weight_v: copying a param with shape torch.Size([3456]) from checkpoint, the shape in current model is torch.Size([4608]).
size mismatch for up_1.conv_1.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.conv_1.weight_orig: copying a param with shape torch.Size([192, 192, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for up_1.conv_1.weight_u: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.conv_1.weight_v: copying a param with shape torch.Size([1728]) from checkpoint, the shape in current model is torch.Size([2304]).
size mismatch for up_1.conv_s.weight_orig: copying a param with shape torch.Size([192, 384, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 512, 1, 1]).
size mismatch for up_1.conv_s.weight_u: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.conv_s.weight_v: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_1.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_0.mlp_beta.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_1.norm_0.mlp_beta.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_1.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.norm_1.mlp_beta.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_1.norm_1.mlp_beta.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_1.norm_s.param_free_norm.running_mean: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_s.param_free_norm.running_var: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_s.mlp_gamma.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_1.norm_s.mlp_gamma.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_1.norm_s.mlp_beta.weight: copying a param with shape torch.Size([384, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 128, 3, 3]).
size mismatch for up_1.norm_s.mlp_beta.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for up_2.conv_0.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.conv_0.weight_orig: copying a param with shape torch.Size([96, 192, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]).
size mismatch for up_2.conv_0.weight_u: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.conv_0.weight_v: copying a param with shape torch.Size([1728]) from checkpoint, the shape in current model is torch.Size([2304]).
size mismatch for up_2.conv_1.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.conv_1.weight_orig: copying a param with shape torch.Size([96, 96, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_2.conv_1.weight_u: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.conv_1.weight_v: copying a param with shape torch.Size([864]) from checkpoint, the shape in current model is torch.Size([1152]).
size mismatch for up_2.conv_s.weight_orig: copying a param with shape torch.Size([96, 192, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]).
size mismatch for up_2.conv_s.weight_u: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.conv_s.weight_v: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_2.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_0.mlp_beta.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_2.norm_0.mlp_beta.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_2.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.norm_1.mlp_beta.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_2.norm_1.mlp_beta.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_2.norm_s.param_free_norm.running_mean: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_s.param_free_norm.running_var: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_s.mlp_gamma.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_2.norm_s.mlp_gamma.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_2.norm_s.mlp_beta.weight: copying a param with shape torch.Size([192, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for up_2.norm_s.mlp_beta.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for up_3.conv_0.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.conv_0.weight_orig: copying a param with shape torch.Size([48, 96, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]).
size mismatch for up_3.conv_0.weight_u: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.conv_0.weight_v: copying a param with shape torch.Size([864]) from checkpoint, the shape in current model is torch.Size([1152]).
size mismatch for up_3.conv_1.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.conv_1.weight_orig: copying a param with shape torch.Size([48, 48, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for up_3.conv_1.weight_u: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.conv_1.weight_v: copying a param with shape torch.Size([432]) from checkpoint, the shape in current model is torch.Size([576]).
size mismatch for up_3.conv_s.weight_orig: copying a param with shape torch.Size([48, 96, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]).
size mismatch for up_3.conv_s.weight_u: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.conv_s.weight_v: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_0.param_free_norm.running_mean: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_0.param_free_norm.running_var: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_0.mlp_gamma.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_3.norm_0.mlp_gamma.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_0.mlp_beta.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_3.norm_0.mlp_beta.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_1.param_free_norm.running_mean: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.norm_1.param_free_norm.running_var: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.norm_1.mlp_gamma.weight: copying a param with shape torch.Size([48, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]).
size mismatch for up_3.norm_1.mlp_gamma.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.norm_1.mlp_beta.weight: copying a param with shape torch.Size([48, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]).
size mismatch for up_3.norm_1.mlp_beta.bias: copying a param with shape torch.Size([48]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for up_3.norm_s.param_free_norm.running_mean: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_s.param_free_norm.running_var: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_s.mlp_gamma.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_3.norm_s.mlp_gamma.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for up_3.norm_s.mlp_beta.weight: copying a param with shape torch.Size([96, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for up_3.norm_s.mlp_beta.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for conv_img.weight: copying a param with shape torch.Size([3, 48, 3, 3]) from checkpoint, the shape in current model is torch.Size([3, 64, 3, 3]).

[jmssxgp]

me too

[mjehanzaib999]

any solution to this problem?

[mjehanzaib999]

so i found the problem, you may be using a different number of label_nc value in test, different from what you used in training part