linear_rna_tcg.yaml

# @package _global_
#
# to execute this experiment run:
# python train.py experiment=tcg

defaults:
  - override /model: linear_tcg
  - override /datamodule: rna_velocity #linear_unidentifiable_velocity
  - override /logger:
      - csv
      - wandb
  - override /trainer: gpu
name: "linear_rna_tcg_gfn"

seed: 0

datamodule:
  batch_size: 500

# best
model:
  env_batch_size: 1024
  eval_batch_size: 5000
  full_posterior_eval: False
  uniform_backwards: True
  debug_use_shd_energy: False
  analytic_use_simple_mse_energy: True
  loss_fn: "detailed_balance"
  alpha: 0
  temperature: 0.01
  temper_period: 5
  w_mse: 10 # 0 <= w_mse <= 1
  w_sparse: 20
  prior_lambda: 100
  beta: 0.01
  confidence: 0.0
  hidden_dim: 128
  embed_dim: 64 # used for transformer architecture
  gfn_freq: 1
  energy_freq: 1
  pretraining_epochs: 0
  lr: 1e-4
  hyper: "mlp"
  bias: True

trainer:
  max_epochs: 1000
  min_epochs: 1000
  check_val_every_n_epoch: 5

logger:
  wandb:
    tags: ["analytic", "rna", "full-graph", "gfn", "${name}", "v14"]