cms/2023_10_12/config.yaml

backend: tensorflow

cache: caches/cms_gen

dataset:
  schema: cms
  target_particles: gen
  num_input_features: 42
#       NONE = 0,
#       TRACK = 1,
#       PS1 = 2,
#       PS2 = 3,
#       ECAL = 4,
#       HCAL = 5,
#       GSF = 6,
#       BREM = 7,
#       HFEM = 8,
#       HFHAD = 9,
#       SC = 10,
#       HO = 11,
  num_input_classes: 12
  #(none=0, ch.had=1, n.had=2, hfem=3, hfhad=4, gamma=5, e=6, mu=7)
  num_output_classes: 8
  padded_num_elem_size: 6400
  cls_weight_by_pt: no
  reg_weight_by_pt: no
  enable_tfds_caching: no

loss:
  classification_loss_coef: 100.0
  charge_loss_coef: 1.0
  pt_loss_coef: 1.0
  eta_loss_coef: 1.0
  sin_phi_loss_coef: 1.0
  cos_phi_loss_coef: 1.0
  energy_loss_coef: 1.0
  cls_loss:
    type: SigmoidFocalCrossEntropy
    from_logits: yes
    gamma: 2.0
  charge_loss:
    type: CategoricalCrossentropy
    from_logits: yes
  energy_loss:
    type: Huber
  pt_loss:
    type: Huber
  sin_phi_loss:
    type: Huber
    delta: 0.1
  cos_phi_loss:
    type: Huber
    delta: 0.1
  eta_loss:
    type: Huber
    delta: 0.1
  event_loss: none #none, sliced_wasserstein, gen_jet_logcosh, gen_jet_mse, hist_2d
  event_loss_coef: 1.0
  met_loss: none
  met_loss_coef: 1.0

tensorflow:
  eager: no

setup:
  train: yes
  weights:
  weights_config:
  lr: 0.00005
  num_epochs: 55
  dtype: float32
  trainable:
  lr_schedule: none  # cosinedecay, exponentialdecay, onecycle, none
  optimizer: adam  # adam, adamw, sgd
  horovod_enabled: no
  cls_output_as_logits: yes
  #if enabled, do not create LSH bins for small graphs (less than one bin size)
  #enabling results in some speedup for gun samples, but must be disabled for XLA
  small_graph_opt: yes
  use_normalizer: no

batching:
  # if enabled, use dynamic batching instead of the fixed-size batches configured in batch_per_gpu
  bucket_by_sequence_length: yes
  bucket_batch_sizes: auto
  batch_multiplier: 1

optimizer:
  adam:
    amsgrad: no
  adamw:
    amsgrad: yes
    weight_decay: 0.001
  sgd:
    nesterov: no
    momentum: 0.9

# LR Schedules
exponentialdecay:
  decay_steps: 2000
  decay_rate: 0.99
  staircase: yes
onecycle:
  mom_min: 0.85
  mom_max: 0.95
  warmup_ratio: 0.3
  div_factor: 25.0
  final_div: 100000.0

parameters:
  model: gnn_dense
  input_encoding: cms
  node_update_mode: additive
  do_node_encoding: yes
  node_encoding_hidden_dim: 512

  combined_graph_layer:
    bin_size: 640
    max_num_bins: 200
    distance_dim: 128
    layernorm: yes
    dropout: 0.0
    dist_activation: elu
    ffn_dist_num_layers: 2
    ffn_dist_hidden_dim: 128

    # GCN
    kernel:
      type: NodePairGaussianKernel
      dist_mult: 0.1
      clip_value_low: 0.0
      dist_norm: l2
    num_node_messages: 2
    node_message:
      type: GHConvDense
      output_dim: 512
      activation: elu
      #if this is enabled, it will break float16 training
      normalize_degrees: no
    activation: elu

  num_graph_layers_id: 3
  num_graph_layers_reg: 3
  output_decoding:
    activation: elu
    regression_use_classification: yes
    dropout: 0.1

    pt_as_correction: yes

    id_dim_decrease: yes
    charge_dim_decrease: yes
    pt_dim_decrease: yes
    eta_dim_decrease: yes
    phi_dim_decrease: yes
    energy_dim_decrease: yes

    id_hidden_dim: 512
    charge_hidden_dim: 256
    pt_hidden_dim: 512
    eta_hidden_dim: 256
    phi_hidden_dim: 256
    energy_hidden_dim: 512

    id_num_layers: 3
    charge_num_layers: 2
    pt_num_layers: 2
    eta_num_layers: 2
    phi_num_layers: 2
    energy_num_layers: 2
    layernorm: yes
    mask_reg_cls0: yes

  skip_connection: no
  debug: no

timing:
  num_ev: 100
  num_iter: 3

callbacks:
  checkpoint:
    monitor: "val_loss"
  plot_freq: 1
  tensorboard:
    dump_history: yes
    hist_freq: 1

hypertune:
  algorithm: hyperband  # random, bayesian, hyperband
  random:
    objective: val_loss
    max_trials: 100
  bayesian:
    objective: val_loss
    max_trials: 100
    num_initial_points: 2
  hyperband:
    objective: val_loss
    max_epochs: 10
    factor: 3
    iterations: 1
    executions_per_trial: 1

raytune:
  local_dir:  # Note: please specify an absolute path
  sched:  asha # asha, hyperband
  search_alg:  # bayes, bohb, hyperopt, nevergrad, scikit
  default_metric: "val_loss"
  default_mode: "min"
  # Tune schedule specific parameters
  asha:
    max_t: 200
    reduction_factor: 4
    brackets: 1
    grace_period: 10
  hyperband:
    max_t: 200
    reduction_factor: 4
  hyperopt:
    n_random_steps: 10
  nevergrad:
    n_random_steps: 10

train_test_datasets:
  multiparticlegun:
    batch_per_gpu: 1
    event_pad_size: -1
    datasets:
      - cms_pf_multi_particle_gun
  physical:
    batch_per_gpu: 1
    event_pad_size: -1
    datasets:
      - cms_pf_ttbar
      - cms_pf_ztt
      - cms_pf_qcd
      - cms_pf_qcd_high_pt
      - cms_pf_sms_t1tttt
  gun:
    batch_per_gpu: 50
    event_pad_size: -1
    datasets:
      - cms_pf_single_electron
      - cms_pf_single_gamma
      - cms_pf_single_neutron
      - cms_pf_single_pi0
      - cms_pf_single_pi
      - cms_pf_single_tau
      - cms_pf_single_mu
      - cms_pf_single_proton

evaluation_datasets:
  cms_pf_qcd_high_pt:
    batch_size: 5
    num_events: -1
  cms_pf_single_neutron:
    batch_size: 100
    num_events: -1

validation_dataset: cms_pf_qcd_high_pt
validation_batch_size: 5
validation_num_events: 500

evaluation_jet_algo: antikt_algorithm

datasets:
  cms_pf_ttbar:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_ztt:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_qcd:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_qcd_high_pt:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_electron:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_gamma:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_pi0:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_neutron:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_pi:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_tau:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_mu:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_single_proton:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_multi_particle_gun:
    version: 1.6.0
    data_dir:
    manual_dir:
  cms_pf_sms_t1tttt:
    version: 1.6.0
    data_dir:
    manual_dir: