train_config_cocostuff.yml

output_root: '../'
pytorch_data_dir: 'pytorch_data_dir'
experiment_name: "cocostuff_EAGLE"
log_dir: "cocostuff27"
dataset_name: "cocostuff27"
azureml_logging: True
submitting_to_aml: False

# wandb params
project_name: "EAGLE" 
entity: "your_ID"

# Loader params
num_workers: 6
max_steps: 10000
batch_size: 32
step_schedulers: 200
dir_dataset_name: ~
dir_dataset_n_classes: 5

has_labels: False
crop_type: 'five'
crop_ratio: .5
res: 224
loader_crop_type: "center"

# lr
lr_linear: 1e-3  
lr_cluster: 5e-3 
lr_cluster_eigen: 5e-5

# eigen
eigen_cluster: 4
eigen_cluster_out: 32

# Model Params
use_head: True
extra_clusters: 5
use_true_labels: False
use_recalibrator: False
model_type: "vit_small"
arch: "dino"
use_fit_model: False
dino_feat_type: "KK"
projection_type: "nonlinear"
dino_patch_size: 8
granularity: 1
continuous: True
dim: 512 
dropout: True
zero_clamp: True
recluster_threshold: 0.85
lr: 5e-4
pretrained_weights: ~
stabalize: True
stop_at_zero: True
shift_value: 3.5
shift_bias: 0

# Feature Contrastive params
pointwise: True
feature_samples: 11
neg_samples: 5
aug_alignment_weight: 0.0

correspondence_weight: 1.0

local_pos_weight: 0.85
local_pos_aug_weight: 0.85
global_loss_weight: 0.7
contrastive_temp: 0.07
momentum_limit: 0.9
centroid_mode: "prototype"

neg_inter_weight: 0.63
pos_inter_weight: 0.25
pos_intra_weight: 1

rec_weight: 0.0
repulsion_weight: 0.0

# CRF Params
crf_weight: 0.0
alpha: .5
beta: .15
gamma: .05
w1: 10.0
w2: 3.0
shift: 0.00
crf_samples: 1000
color_space: "rgb"

reset_probe_steps: ~

n_images: 4
scalar_log_freq: 10
checkpoint_freq: 100
val_freq: 100
hist_freq: 100


hydra:
  run:
    dir: "."
  output_subdir: ~
  #job_logging: "disabled"
  #hydra_logging: "disabled"