# Energy Halting Experiment Config

# Model Architecture
model: ctm
d_model: 512
d_input: 128
heads: 4
iterations: 50
dropout: 0.0
backbone_type: resnet18-4
positional_embedding_type: none

# CTM Specifics
synapse_depth: 4
n_synch_out: 512
n_synch_action: 512
neuron_select_type: random-pairing
n_random_pairing_self: 0
memory_length: 25
deep_memory: true
memory_hidden_dims: 4
do_normalisation: false

# Energy Head
energy_head:
  enabled: true
  d_hidden: 64

# Training
batch_size: 32
batch_size_test: 32
lr: 1.0e-3
training_iterations: 100001
warmup_steps: 5000
use_scheduler: true
scheduler_type: cosine
weight_decay: 0.0
gradient_clipping: -1
do_compile: false
num_workers_train: 4

# Loss
loss:
  type: energy_contrastive
  margin: 5.0
  energy_scale: 0.5

# Inference
inference:
  energy_threshold: 0.5
  delta_threshold: 0.01

# Housekeeping
dataset: cifar10
data_root: data/
save_every: 1000
track_every: 1000
seed: 412
log_dir: logs/energy_experiment
device: [-1] # Auto-detect