Delete configs/e_mc_point_neutron_conv_standard_L5_InputQDq_n256_size1024.yaml

configs/e_mc_point_neutron_conv_standard_L5_InputQDq_n256_size1024.yaml

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-general:
-  name: e_mc_point_neutron_conv_standard_L5_InputQDq_n256_size1024
-  root_dir: null
-  
-dset:
-  cls: ReflectivityDataLoader
-  prior_sampler:
-    cls: SubpriorParametricSampler
-    kwargs:
-      param_ranges:
-        thicknesses: [1., 1500.]
-        roughnesses: [0., 60.]
-        slds: [-8., 16.]
-        r_scale: [0.9, 1.1]
-        log10_background: [-10.0, -4.0]
-      bound_width_ranges:
-        thicknesses: [1.0e-2, 1500.]
-        roughnesses: [1.0e-2, 60.]
-        slds: [1.0e-2, 5.]
-        r_scale: [1.0e-2, 0.2]
-        log10_background: [1.0e-2, 6.0]
-      shift_param_config:
-        r_scale: true
-        log10_background: true
-      model_name: standard_model
-      max_num_layers: 5
-      max_total_thickness: 1500
-      constrained_roughness: true
-      max_thickness_share: 0.5
-      logdist: false
-      scale_params_by_ranges: false
-      scaled_range: [-1., 1.]
-      device: 'cuda'
-
-  q_generator:
-    cls: VariableQ
-    kwargs:
-      q_min_range: [0.001, 0.02]
-      q_max_range: [0.05, 0.4]
-      n_q_range: [256, 256]
-      device: 'cuda'
-
-  intensity_noise:
-    cls: GaussianExpIntensityNoise
-    kwargs:
-      relative_errors: [0.01, 0.3]
-      add_to_context: true
-
-  smearing:
-    cls: Smearing
-    kwargs:
-      sigma_range: [0.01, 0.12]
-      gauss_num: 17
-      share_smeared: 1.0
-      
-  curves_scaler:
-    cls: LogAffineCurvesScaler
-    kwargs:
-      weight: 0.2
-      bias: 1.0
-      eps: 1.0e-10
-
-model:
-  network:
-    cls: NetworkWithPriors
-    pretrained_name: null
-    device: 'cuda'
-    kwargs:
-      embedding_net_type: 'conv'
-      embedding_net_kwargs:
-        in_channels: 2
-        hidden_channels: [32, 64, 128, 256, 512]
-        kernel_size: 3
-        dim_embedding: 512
-        dim_avpool: 8
-        use_batch_norm: true
-        use_se: false
-        activation: 'gelu'
-      pretrained_embedding_net: null
-      dim_out: 19
-      dim_conditioning_params: 1
-      layer_width: 1024
-      num_blocks: 8
-      repeats_per_block: 2
-      residual: true
-      use_batch_norm: true
-      use_layer_norm: false
-      mlp_activation: 'gelu'
-      dropout_rate: 0.0 
-      tanh_output: false
-      conditioning: 'film'
-      concat_condition_first_layer: false
-       
-training:
-  trainer_cls: PointEstimatorTrainer
-  num_iterations: 300000
-  batch_size: 2048
-  lr: 1.0e-3
-  grad_accumulation_steps: 1
-  clip_grad_norm_max: null
-  update_tqdm_freq: 1
-  optimizer: AdamW
-  trainer_kwargs:
-    train_with_q_input: true
-    condition_on_q_resolutions: true
-    rescale_loss_interval_width: true
-    use_l1_loss: true
-    optim_kwargs:
-      betas: [0.9, 0.999]
-      weight_decay: 0.0005
-  callbacks:
-    save_best_model:
-      enable: true
-      freq: 500
-    lr_scheduler:
-      cls: CosineAnnealingWithWarmup
-      kwargs:
-        min_lr: 1.0e-6
-        warmup_iters: 500
-        total_iters: 300000