Delete clipseg/experiments/phrasecut.yaml

clipseg/experiments/phrasecut.yaml

@@ -1,80 +0,0 @@
-configuration:
-  batch_size: 64
-  optimizer: torch.optim.AdamW
-
-  lr: 0.001
-
-  trainer: experiment_setup.train_loop
-  scorer: experiment_setup.score
-  model: models.clipseg.CLIPDensePredT
-
-  lr_scheduler: cosine
-  T_max: 20000
-  eta_min: 0.0001
-
-  max_iterations: 20000
-  val_interval: null
-
-  # dataset
-  dataset: datasets.phrasecut.PhraseCut   # <-----------------
-  split_mode: pascal_test
-  split: train
-  mask: text_and_crop_blur_highlight352
-  image_size: 352
-  normalize: True
-  pre_crop_image_size: [sample, 1, 1.5]
-  aug: 1new
-
-  # general
-  mix: False # <-----------------
-  prompt: shuffle+
-  norm_cond: True
-  mix_text_min: 0.0
-  
-  # model
-  out: 1
-  extract_layers: [3, 7, 9]
-  reduce_dim: 64
-  depth: 3
-  fix_shift: False
-
-  loss: torch.nn.functional.binary_cross_entropy_with_logits
-  amp: True
-
-test_configuration_common:
-  normalize: True
-  image_size: 352
-  batch_size: 32
-  # max_iterations: 5
-  # max_iterations: 150
-  
-test_configuration: 
-
-  -
-    name: pc  # old: phrasecut
-    metric: metrics.FixedIntervalMetrics
-    test_dataset: phrasecut
-    split: test
-    mask: text
-    label_support: True
-    sigmoid: True
-
-
-columns: [i, name, pc_miou_0.3, pc_fgiou_0.3, pc_fgiou_0.5, pc_ap, duration, date]
-
-
-individual_configurations:
-
-# important ones
-
-
-- {name: rd64-uni, version: 'ViT-B/16', reduce_dim: 64, with_visual: True, negative_prob: 0.2, mix: True, mix_text_max: 0.5}
-
-# this was accedentally trained using old mask
-- {name: rd128-vit16-phrasecut, version: 'ViT-B/16', reduce_dim: 128, mask: text_and_blur3_highlight01}
-- {name: rd64-uni-novis, version: 'ViT-B/16', reduce_dim: 64, with_visual: False, negative_prob: 0.2, mix: False}
-# this was accedentally trained using old mask
-- {name: baseline3-vit16-phrasecut, model: models.clipseg.CLIPDenseBaseline, version: 'ViT-B/16', reduce_dim: 64, reduce2_dim: 64, mask: text_and_blur3_highlight01}
-
-- {name: vit64-uni, version: 'ViT-B/16', model: models.vitseg.VITDensePredT, reduce_dim: 64, with_visual: True, only_visual: True, negative_prob: 0.2, mask: crop_blur_highlight352, lr: 0.0003}
-- {name: vit64-uni-novis, version: 'ViT-B/16', model: models.vitseg.VITDensePredT, with_visual: False, reduce_dim: 64, lr: 0.0001}