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project : # Project name
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name : AWS_Dataset
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+ seed : 42
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exp_tag : 1 # Experiment tag
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# Main output directory.
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output : outputs/${project.name}/${exp_tag}
@@ -27,8 +28,8 @@ hydra: # Hydra config
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output_subdir : hydra # Default is .hydra which causes files not being uploaded in W&B.
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data : # Input directory for training and validation data
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- input_dir : /lustre/rranade/modulus_dev/data /volume_data/
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- input_dir_val : /lustre/rranade/modulus_dev/data/volume_data_val /
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+ input_dir : /home/aistudio/modulus/examples/cfd/external_aerodynamics/domino/outputs /volume_data/
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+ input_dir_val : /home/aistudio/modulus/examples/cfd/external_aerodynamics/domino/outputs/volume_data /
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bounding_box : # Bounding box dimensions for computational domain
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min : [-3.5, -2.25 , -0.32]
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max : [8.5 , 2.25 , 3.00]
@@ -55,12 +56,12 @@ variables:
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model :
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model_type : combined # train which model? surface, volume, combined
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loss_function : " mse" # mse or rmse
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- interp_res : [128, 64, 48 ] # resolution of latent space
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+ interp_res : [64, 32, 24 ] # resolution of latent space
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use_sdf_in_basis_func : true # SDF in basis function network
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positional_encoding : false # calculate positional encoding?
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- volume_points_sample : 8192 # Number of points to sample in volume per epoch
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- surface_points_sample : 8192 # Number of points to sample on surface per epoch
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- geom_points_sample : 200_000 # Number of points to sample on STL per epoch
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+ volume_points_sample : 1024 # Number of points to sample in volume per epoch
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+ surface_points_sample : 1024 # Number of points to sample on surface per epoch
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+ geom_points_sample : 2_000 # Number of points to sample on STL per epoch
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surface_neighbors : true # Pre-compute surface neighborhood from input data
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num_surface_neighbors : 7 # How many neighbors?
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use_surface_normals : true # Use surface normals and surface areas for surface computation?
@@ -95,11 +96,10 @@ model:
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scaling_params : [30.0, 1.226] # [inlet_velocity, air_density]
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train : # Training configurable parameters
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- epochs : 500
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+ epochs : 50
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checkpoint_interval : 1
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dataloader :
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batch_size : 1
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- pin_memory : true
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sampler :
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shuffle : true
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drop_last : false
@@ -108,15 +108,14 @@ train: # Training configurable parameters
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val : # Validation configurable parameters
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dataloader :
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batch_size : 1
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- pin_memory : true
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sampler :
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shuffle : true
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drop_last : false
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eval : # Testing configurable parameters
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- test_path : /lustre/rranade/benchmarking/drivaer_aws_surface_test_new/
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- save_path : /lustre/rranade/ domino/mesh_predictions_surf_final1/
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- checkpoint_name : DoMINO.0.50.pt
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+ test_path : /home/aistudio/modulus/examples/cfd/external_aerodynamics/domino/drivaer_data_full_new
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+ save_path : /home/aistudio/modulus/examples/cfd/external_aerodynamics/ domino/outputs /mesh_predictions_surf_final1/
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+ checkpoint_name : /home/aistudio/xiaoyewww/PaddleScience/examples/domino/outputs/AWS_Dataset/1/models/ DoMINO.0.30.pdparams
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data_processor : # Data processor configurable parameters
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kind : drivaer_aws # must be either drivesim or drivaer_aws
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