valentinsingularity commited on
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Delete saved_models/g_mc_point_xray_conv_absorption_L3_InputQ_n256_size1024.yaml

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saved_models/g_mc_point_xray_conv_absorption_L3_InputQ_n256_size1024.yaml DELETED
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- general:
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- name: g_mc_point_xray_conv_absorption_L3_InputQ_n256_size1024
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- root_dir: null
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-
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- dset:
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- cls: ReflectivityDataLoader
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- prior_sampler:
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- cls: SubpriorParametricSampler
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- kwargs:
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- param_ranges:
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- thicknesses: [1., 500.]
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- roughnesses: [0., 60.]
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- slds: [0., 150.]
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- islds: [0., 30.]
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- q_shift: [-0.002, 0.002]
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- r_scale: [0.9, 1.1]
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- bound_width_ranges:
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- thicknesses: [1.0e-2, 500.]
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- roughnesses: [1.0e-2, 60.]
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- slds: [ 1.0e-2, 5.]
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- islds: [1.0e-2, 5.]
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- q_shift: [1.0e-5, 0.004]
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- r_scale: [1.0e-3, 0.2]
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- shift_param_config:
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- q_shift: true
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- r_scale: true
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- model_name: model_with_absorption
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- max_num_layers: 3
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- max_total_thickness: 1500
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- constrained_roughness: true
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- constrained_isld: true
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- max_thickness_share: 0.5
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- max_sld_share: 0.2
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- logdist: false
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- scale_params_by_ranges: false
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- scaled_range: [-1., 1.]
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- device: 'cuda'
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-
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- q_generator:
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- cls: VariableQ
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- kwargs:
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- q_min_range: [0.001, 0.03]
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- q_max_range: [0.1, 0.5]
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- n_q_range: [256, 256]
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- device: 'cuda'
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-
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- intensity_noise:
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- cls: GaussianExpIntensityNoise
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- kwargs:
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- relative_errors: [0.01, 0.3]
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- add_to_context: true
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-
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- curves_scaler:
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- cls: LogAffineCurvesScaler
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- kwargs:
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- weight: 0.2
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- bias: 1.0
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- eps: 1.0e-10
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-
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- model:
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- network:
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- cls: NetworkWithPriors
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- pretrained_name: null
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- device: 'cuda'
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- kwargs:
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- embedding_net_type: 'conv'
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- embedding_net_kwargs:
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- in_channels: 2
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- hidden_channels: [32, 64, 128, 256, 512]
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- kernel_size: 3
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- dim_embedding: 512
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- dim_avpool: 8
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- use_batch_norm: true
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- activation: 'gelu'
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- pretrained_embedding_net: null
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- dim_out: 17
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- dim_conditioning_params: 0
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- layer_width: 1024
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- num_blocks: 8
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- repeats_per_block: 2
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- residual: true
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- use_batch_norm: true
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- use_layer_norm: false
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- mlp_activation: 'gelu'
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- dropout_rate: 0.0
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- tanh_output: false
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- conditioning: 'film'
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- concat_condition_first_layer: false
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-
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- training:
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- trainer_cls: PointEstimatorTrainer
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- num_iterations: 300000
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- batch_size: 4096
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- lr: 1.0e-3
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- grad_accumulation_steps: 1
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- clip_grad_norm_max: null
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- update_tqdm_freq: 1
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- optimizer: AdamW
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- trainer_kwargs:
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- train_with_q_input: true
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- condition_on_q_resolutions: false
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- rescale_loss_interval_width: true
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- use_l1_loss: true
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- optim_kwargs:
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- betas: [0.9, 0.999]
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- weight_decay: 0.0005
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- callbacks:
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- save_best_model:
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- enable: true
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- freq: 500
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- lr_scheduler:
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- cls: CosineAnnealingWithWarmup
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- kwargs:
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- min_lr: 1.0e-6
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- warmup_iters: 500
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- total_iters: 300000