Update config.yaml

config.yaml

@@ -1,138 +1,138 @@
-location:
-  data_root_dir: C:\Users\Green\Desktop\lama-main/celeba-hq-dataset/
-  out_root_dir: F:\Result celeba/experiments/
-  tb_dir: F:\Result celeba/tb_logs/
-  pretrained_models: C:\Users\Green\Desktop\lama-main/
-data:
-  batch_size: 25
-  val_batch_size: 40
-  num_workers: 4
-  train:
-    indir: ${location.data_root_dir}/train_256
-    out_size: 256
-    mask_gen_kwargs:
-      irregular_proba: 1
-      irregular_kwargs:
-        max_angle: 4
-        max_len: 200
-        max_width: 100
-        max_times: 5
-        min_times: 1
-      box_proba: 1
-      box_kwargs:
-        margin: 10
-        bbox_min_size: 30
-        bbox_max_size: 150
-        max_times: 4
-        min_times: 1
-      segm_proba: 0
-    transform_variant: no_augs
-    dataloader_kwargs:
-      batch_size: ${data.batch_size}
-      shuffle: true
-      num_workers: ${data.num_workers}
-  val:
-    indir: ${location.data_root_dir}/val_256
-    img_suffix: .png
-    dataloader_kwargs:
-      batch_size: ${data.val_batch_size}
-      shuffle: false
-      num_workers: ${data.num_workers}
-  visual_test: null
-generator:
-  kind: Swin_UNET
-discriminator:
-  kind: pix2pixhd_nlayer
-  input_nc: 3
-  ndf: 64
-  n_layers: 4
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-visualizer:
-  kind: directory
-  outdir: F:\Result celeba\experiments\2022-06-12_14-48-59_train_lama-fourier-celeba.yaml_aaa\samples
-  key_order:
-  - image
-  - predicted_image
-  - discr_output_fake
-  - discr_output_real
-  - inpainted
-  - eye
-  - eye_pred
-  - hair
-  - hair_pred
-  - skin
-  - skin_pred
-  rescale_keys:
-  - discr_output_fake
-  - discr_output_real
-evaluator:
-  kind: default
-  inpainted_key: inpainted
-  integral_kind: ssim_fid100_f1
-trainer:
-  kwargs:
-    gpus: 1
-    accelerator: dp
-    max_epochs: 50
-    gradient_clip_val: 1
-    limit_train_batches: 25000
-    log_every_n_steps: 300
-    precision: 32
-    terminate_on_nan: false
-    check_val_every_n_epoch: 5
-    num_sanity_val_steps: 0
-    replace_sampler_ddp: false
-  checkpoint_kwargs:
-    verbose: true
-    save_top_k: 5
-    save_last: true
-    monitor: val_ssim_fid100_f1_total_mean
-    mode: max
-run_title: aaa
-training_model:
-  kind: default
-  visualize_each_iters: 100
-  concat_mask: true
-  store_discr_outputs_for_vis: true
-losses:
-  l1:
-    weight_missing: 0
-    weight_known: 10
-    weight_known_skin: 3
-    weight_known_eye: 3
-    weight_known_ear: 3
-    weight_known_lip: 3
-    weight_known_cloth: 3
-    weight_known_hair: 3
-  perceptual:
-    weight: 0
-  adversarial_component:
-    weight_skin: 0.1
-    weight_eye: 0.15
-    weight_ear: 0.15
-    weight_lip: 0.15
-    weight_cloth: 0.1
-    weight_hair: 0.1
-  adversarial:
-    kind: r1
-    weight: 10
-    gp_coef: 0.001
-    mask_as_fake_target: true
-    allow_scale_mask: true
-  feature_matching:
-    weight: 100
-    weight_skin: 10
-    weight_eye: 15
-    weight_ear: 15
-    weight_lip: 15
-    weight_cloth: 10
-    weight_hair: 10
-  resnet_pl:
-    weight: 30
-    weights_path: C:\Users\Green\Desktop\lama-main
+location:
+  data_root_dir: ${location.data_root_dir}
+  out_root_dir: ${location.data_root_dir}
+  tb_dir: ${location.data_root_dir}
+  pretrained_models: ${location.data_root_dir}
+data:
+  batch_size: 25
+  val_batch_size: 40
+  num_workers: 4
+  train:
+    indir: ${location.data_root_dir}/train_256
+    out_size: 256
+    mask_gen_kwargs:
+      irregular_proba: 1
+      irregular_kwargs:
+        max_angle: 4
+        max_len: 200
+        max_width: 100
+        max_times: 5
+        min_times: 1
+      box_proba: 1
+      box_kwargs:
+        margin: 10
+        bbox_min_size: 30
+        bbox_max_size: 150
+        max_times: 4
+        min_times: 1
+      segm_proba: 0
+    transform_variant: no_augs
+    dataloader_kwargs:
+      batch_size: ${data.batch_size}
+      shuffle: true
+      num_workers: ${data.num_workers}
+  val:
+    indir: ${location.data_root_dir}/val_256
+    img_suffix: .png
+    dataloader_kwargs:
+      batch_size: ${data.val_batch_size}
+      shuffle: false
+      num_workers: ${data.num_workers}
+  visual_test: null
+generator:
+  kind: Swin_UNET
+discriminator:
+  kind: pix2pixhd_nlayer
+  input_nc: 3
+  ndf: 64
+  n_layers: 4
+optimizers:
+  generator:
+    kind: adam
+    lr: 0.001
+  discriminator:
+    kind: adam
+    lr: 0.0001
+visualizer:
+  kind: directory
+  outdir: ${location.data_root_dir}/samples
+  key_order:
+  - image
+  - predicted_image
+  - discr_output_fake
+  - discr_output_real
+  - inpainted
+  - eye
+  - eye_pred
+  - hair
+  - hair_pred
+  - skin
+  - skin_pred
+  rescale_keys:
+  - discr_output_fake
+  - discr_output_real
+evaluator:
+  kind: default
+  inpainted_key: inpainted
+  integral_kind: ssim_fid100_f1
+trainer:
+  kwargs:
+    gpus: 1
+    accelerator: dp
+    max_epochs: 50
+    gradient_clip_val: 1
+    limit_train_batches: 25000
+    log_every_n_steps: 300
+    precision: 32
+    terminate_on_nan: false
+    check_val_every_n_epoch: 5
+    num_sanity_val_steps: 0
+    replace_sampler_ddp: false
+  checkpoint_kwargs:
+    verbose: true
+    save_top_k: 5
+    save_last: true
+    monitor: val_ssim_fid100_f1_total_mean
+    mode: max
+run_title: aaa
+training_model:
+  kind: default
+  visualize_each_iters: 100
+  concat_mask: true
+  store_discr_outputs_for_vis: true
+losses:
+  l1:
+    weight_missing: 0
+    weight_known: 10
+    weight_known_skin: 3
+    weight_known_eye: 3
+    weight_known_ear: 3
+    weight_known_lip: 3
+    weight_known_cloth: 3
+    weight_known_hair: 3
+  perceptual:
+    weight: 0
+  adversarial_component:
+    weight_skin: 0.1
+    weight_eye: 0.15
+    weight_ear: 0.15
+    weight_lip: 0.15
+    weight_cloth: 0.1
+    weight_hair: 0.1
+  adversarial:
+    kind: r1
+    weight: 10
+    gp_coef: 0.001
+    mask_as_fake_target: true
+    allow_scale_mask: true
+  feature_matching:
+    weight: 100
+    weight_skin: 10
+    weight_eye: 15
+    weight_ear: 15
+    weight_lip: 15
+    weight_cloth: 10
+    weight_hair: 10
+  resnet_pl:
+    weight: 30
+    weights_path: ${location.data_root_dir}/lama-main