Replace configs with minimal inference-only YAMLs (no training/validation)

knee/vsharp_adain_triang_32_16.yaml

@@ -1,197 +1,67 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: NONE
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 32
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: ADAIN
-  image_unet_adain_hidden_features:
-    - 32
-    - 16
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 32
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: ADAIN
+    image_unet_adain_hidden_features:
+        - 32
+        - 16
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

knee/vsharp_modconv_features_triang.yaml

@@ -1,195 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 32
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 32
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 80001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

knee/vsharp_modconv_features_triang_32_16.yaml

@@ -1,195 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 16
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 16
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 80001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

knee/vsharp_modconv_features_triang_32_16_mod_inp.yaml

@@ -1,195 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 16
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: true
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 16
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: true
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

knee/vsharp_modconv_features_triang_32_8.yaml

@@ -1,195 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 8
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 8
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 80001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

knee/vsharp_triang.yaml

@@ -1,195 +1,63 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: NONE
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 32
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 32
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-        random_flip_probability: 0.5
-        random_rotation_probability: 0.5
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 15000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 80001
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

prostate/vsharp_modconv_features_triang.yaml

@@ -1,193 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 32
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 32
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 30000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150000
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

prostate/vsharp_modconv_features_triang_32_16.yaml

@@ -1,193 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 16
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 16
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 30000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150000
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

prostate/vsharp_modconv_features_triang_32_8.yaml

@@ -1,193 +1,66 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: FEATURES
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 8
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    conv_modulation: FEATURES
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 8
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    modulation_at_input: false
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+    image_unet_norm_type: INSTANCE
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 30000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150000
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995

prostate/vsharp_triang.yaml

@@ -1,193 +1,63 @@
 model:
-  model_name: vsharp.vsharp.VSharpNet
-  num_steps: 12
-  num_steps_dc_gd: 10
-  image_init: SENSE
-  no_parameter_sharing: true
-  auxiliary_steps: -1
-  image_model_architecture: UNET
-  initializer_channels:
-    - 32
-    - 32
-    - 64
-    - 64
-  initializer_dilations:
-    - 1
-    - 1
-    - 2
-    - 4
-  initializer_multiscale: 1
-  initializer_activation: PRELU
-  conv_modulation: NONE
-  aux_in_features: 2
-  log_aux: true
-  fc_hidden_features:
-    - 32
-    - 32
-  fc_groups: 1
-  fc_activation: SOFTPLUS
-  num_weights: null
-  modulation_at_input: false
-  image_resnet_hidden_channels: 128
-  image_resnet_num_blocks: 15
-  image_resnet_batchnorm: true
-  image_resnet_scale: 0.1
-  image_unet_num_filters: 32
-  image_unet_num_pool_layers: 4
-  image_unet_dropout: 0.0
-  image_unet_norm_type: INSTANCE
-  image_unet_adain_hidden_features: null
-  image_didn_hidden_channels: 16
-  image_didn_num_dubs: 6
-  image_didn_num_convs_recon: 9
-  image_conv_hidden_channels: 64
-  image_conv_n_convs: 15
-  image_conv_activation: ActivationType.RELU
-  image_conv_batchnorm: false
-additional_models:
-  sensitivity_model:
-    model_name: unet.unet_2d.UnetModel2d
-    in_channels: 2
-    out_channels: 2
-    num_filters: 16
-    num_pool_layers: 4
-    dropout_probability: 0.0
-    modulation: NONE
-    aux_in_features: null
-    fc_hidden_features: null
+    model_name: vsharp.vsharp.VSharpNet
+    num_steps: 12
+    num_steps_dc_gd: 10
+    image_init: SENSE
+    no_parameter_sharing: true
+    auxiliary_steps: -1
+    image_model_architecture: UNET
+    initializer_channels:
+        - 32
+        - 32
+        - 64
+        - 64
+    initializer_dilations:
+        - 1
+        - 1
+        - 2
+        - 4
+    initializer_multiscale: 1
+    initializer_activation: PRELU
+    aux_in_features: 2
+    log_aux: true
+    fc_hidden_features:
+        - 32
+        - 32
     fc_groups: 1
-    fc_activation: SIGMOID
-    num_weights: null
-    conv_out_bias: false
+    fc_activation: SOFTPLUS
+    image_unet_num_filters: 32
+    image_unet_num_pool_layers: 4
+    image_unet_dropout: 0.0
+additional_models:
+    sensitivity_model:
+        model_name: unet.unet_2d.UnetModel2d
+        in_channels: 2
+        out_channels: 2
+        num_filters: 16
+        num_pool_layers: 4
+        dropout_probability: 0.0
+        conv_out_bias: false
 physics:
-  forward_operator: fft2
-  backward_operator: ifft2
-  use_noise_matrix: false
-  noise_matrix_scaling: 1.0
-training:
-  datasets:
-    - name: FastMRI
-      transforms:
-        crop: reconstruction_size
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        image_center_crop: false
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-            - 16
-          center_fractions:
-            - 0.08
-            - 0.02
-          range_mode: LINEAR
-        scale_percentile: 0.995
-        use_seed: false
-        delete_kspace: false
-  model_checkpoint: null
-  optimizer: Adam
-  lr: 0.002
-  weight_decay: 0.0
-  batch_size: 1
-  lr_step_size: 30000
-  lr_gamma: 0.8
-  lr_warmup_iter: 1000
-  swa_start_iter: null
-  num_iterations: 150000
-  validation_steps: 4000
-  gradient_steps: 1
-  gradient_clipping: 0.0
-  gradient_debug: false
-  loss:
-    crop: header
-    losses:
-      - function: l1_loss
-        multiplier: 1.0
-      - function: ssim_loss
-        multiplier: 1.0
-      - function: hfen_l2_norm_loss
-        multiplier: 1.0
-      - function: hfen_l1_norm_loss
-        multiplier: 1.0
-      - function: kspace_nmae_loss
-        multiplier: 1.0
-      - function: kspace_nmse_loss
-        multiplier: 1.0
-  checkpointer:
-    checkpoint_steps: 4000
-  metrics: []
-  regularizers: []
-validation:
-  datasets:
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 4
-          center_fractions:
-            - 0.08
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 4x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 8
-          center_fractions:
-            - 0.04
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 8x
-    - name: FastMRI
-      transforms:
-        estimate_sensitivity_maps: true
-        scaling_key: masked_kspace
-        masking:
-          name: FastMRIEquispaced
-          accelerations:
-            - 16
-          center_fractions:
-            - 0.02
-        scale_percentile: 0.995
-        use_seed: true
-      text_description: 16x
-  batch_size: 20
-  metrics:
-    - fastmri_psnr
-    - fastmri_ssim
-    - fastmri_nmse
-  regularizers: []
-  crop: header
+    forward_operator: fft2
+    backward_operator: ifft2
 inference:
-  dataset:
-    name: FastMRI
-    transforms:
-      masking:
-        name: FastMRIEquispaced
-        accelerations:
-          - 4.0
-        center_fractions:
-          - 0.08
-        mode: STATIC
-      cropping:
-        crop: null
-      sensitivity_map_estimation:
-        estimate_sensitivity_maps: true
-      normalization:
-        scaling_key: masked_kspace
-        scale_percentile: 0.995
-      use_seed: true
-    text_description: inference-4x
-  batch_size: 1
-  crop: header
-logging:
-  log_as_image: null
-  tensorboard:
-    num_images: 4
+    batch_size: 1
+    crop: header
+    dataset:
+        name: FastMRI
+        transforms:
+            use_seed: true
+            delete_kspace: false
+            masking:
+                name: FastMRIEquispaced
+                accelerations:
+                    - 4.0
+                center_fractions:
+                    - 0.08
+            cropping:
+                image_center_crop: false
+            sensitivity_map_estimation:
+                estimate_sensitivity_maps: true
+            normalization:
+                scaling_key: masked_kspace
+                scale_percentile: 0.995