| from transformers import PretrainedConfig | |
| class GPUNetConfig(PretrainedConfig): | |
| model_type = "GPUNet" | |
| def __init__( | |
| self, | |
| in_channels=1, | |
| n_classes=3, | |
| depth=3, | |
| wf=6, | |
| padding=True, | |
| batch_norm=False, | |
| up_mode="sinc", | |
| dropout=True, | |
| Relu="Relu", | |
| out_act="None", | |
| **kwargs): | |
| self.in_channels = in_channels | |
| self.n_classes = n_classes | |
| self.depth = depth | |
| self.wf = wf | |
| self.padding = padding | |
| self.batch_norm = batch_norm | |
| self.up_mode = up_mode | |
| self.dropout = dropout | |
| self.Relu = Relu | |
| self.out_act = out_act | |
| super().__init__(**kwargs) | |
| class GPReconResNetConfig(PretrainedConfig): | |
| model_type = "GPReconResNet" | |
| def __init__( | |
| self, | |
| in_channels=1, | |
| n_classes=3, | |
| res_blocks=14, | |
| starting_nfeatures=64, | |
| updown_blocks=2, | |
| is_relu_leaky=True, | |
| do_batchnorm=False, | |
| res_drop_prob=0.5, | |
| out_act="None", | |
| forwardV=0, | |
| upinterp_algo='sinc', | |
| post_interp_convtrans=False, | |
| is3D=False, | |
| **kwargs): | |
| self.in_channels = in_channels | |
| self.n_classes = n_classes | |
| self.res_blocks = res_blocks | |
| self.starting_nfeatures = starting_nfeatures | |
| self.updown_blocks = updown_blocks | |
| self.is_relu_leaky = is_relu_leaky | |
| self.do_batchnorm = do_batchnorm | |
| self.res_drop_prob = res_drop_prob | |
| self.out_act = out_act | |
| self.forwardV = forwardV | |
| self.upinterp_algo = upinterp_algo | |
| self.post_interp_convtrans = post_interp_convtrans | |
| self.is3D = is3D | |
| super().__init__(**kwargs) | |
| class GPShuffleUNetConfig(PretrainedConfig): | |
| model_type = "GPShuffleUNet" | |
| def __init__( | |
| self, | |
| d=2, | |
| in_ch=1, | |
| num_features=64, | |
| n_levels=3, | |
| out_ch=3, | |
| kernel_size=3, | |
| stride=1, | |
| dropout=True, | |
| out_act="None", | |
| **kwargs): | |
| self.d = d | |
| self.in_ch = in_ch | |
| self.num_features = num_features | |
| self.n_levels = n_levels | |
| self.out_ch = out_ch | |
| self.kernel_size = kernel_size | |
| self.stride = stride | |
| self.dropout = dropout | |
| self.out_act = out_act | |
| super().__init__(**kwargs) |