direct-e2e-ads-recon / vsharp_ads_2d_frame.yaml
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One inference YAML per model; other accels commented under masking
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# Inference-only config (active: 4x).
# Other validation rates are commented under inference.dataset.transforms.masking.
# Pair with checkpoint vsharp_ads_2d_frame.pt (same stem as the training YAML).
model:
model_name: vsharp.vsharp.VSharpNet3D
num_steps: 8
num_steps_dc_gd: 8
image_init: SENSE
no_parameter_sharing: true
auxiliary_steps: -1
initializer_channels:
- 32
- 32
- 64
- 64
initializer_dilations:
- 1
- 1
- 2
- 4
initializer_multiscale: 1
initializer_activation: PRELU
unet_num_filters: 16
unet_num_pool_layers: 4
unet_dropout: 0.0
unet_norm: false
additional_models:
sampling_model:
model_name: adaptive.policy.StraightThroughPolicy
sampling_dimension: TWO_D
st_slope: 10.0
st_clamp: false
use_softplus: true
slope: 10.0
fix_sign_leakage: true
kspace_shape:
- 512
- 246
num_layers: 1
kspace_sampler: false
sampler_detach_mask: false
sampler_chans: 16
sampler_num_pool_layers: 3
sampler_fc_size: 128
sampler_drop_prob: 0.0
sampler_num_fc_layers: 3
sampler_activation: LEAKY_RELU
sampling_type: DYNAMIC_2D
num_time_steps: 12
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
physics:
forward_operator: fft2
backward_operator: ifft2
inference:
batch_size: 1
crop: header
dataset:
name: CMRxRecon
transforms:
use_seed: true
delete_kspace: false
masking:
name: Gaussian2D
accelerations:
- 4.0327
center_fractions:
- 0.04
# --- 6x: uncomment these; comment out the active lists above ---
# accelerations: [6]
# center_fractions: [0.04]
# --- 8x: uncomment these; comment out the active lists above ---
# accelerations: [8.2]
# center_fractions: [0.04]
cropping:
image_center_crop: false
sensitivity_map_estimation:
estimate_sensitivity_maps: true
normalization:
scaling_key: acs_kspace
scale_percentile: 0.995
use_acs_as_mask: true
delete_acs_mask: false
augmentation:
pad:
- 512
- 246
kspace_context: time