Neat configs

README.md

@@ -209,8 +209,7 @@ On the host machine:
     bash fetch_data/celebahq_gen_masks.sh
 
     # Run training
-    # You can change bs with data.batch_size=10
-    python bin/train.py -cn ablv2_work_no_segmpl_csdilirpl_celeba_csdilirpl1_new location=celeba
+    python bin/train.py -cn lama-fourier-celeba data.batch_size=10
 
     # Infer model on thick/thin/medium masks in 256 and run evaluation 
     # like this:

bin/predict.py

@@ -47,6 +47,7 @@ def main(predict_config: OmegaConf):
             train_config = OmegaConf.create(yaml.safe_load(f))
 
         train_config.training_model.predict_only = True
+        train_config.visualizer.kind = 'noop'
 
         out_ext = predict_config.get('out_ext', '.png')
 

configs/training/ablv2_work.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 30
     weights_path: ${env:TORCH_HOME}
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final

configs/training/ablv2_work_ffc075.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 30
     weights_path: ${env:TORCH_HOME}
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: ffc_resnet_075
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final

configs/training/ablv2_work_md.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 30
     weights_path: ${env:TORCH_HOME}
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_multidilated_catin_4dil_9b
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final_benchmark

configs/training/ablv2_work_no_fm.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 30
     weights_path: ${env:TORCH_HOME}
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: mlp-mow-final
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final

configs/training/ablv2_work_no_segmpl.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 0
 #    weights_path: ${env:TORCH_HOME}
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final

configs/training/ablv2_work_no_segmpl_csdilirpl.yaml

@@ -24,30 +24,12 @@ losses:
     weight: 1
     segmentation: false
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final_benchmark

configs/training/ablv2_work_no_segmpl_csdilirpl_celeba_csdilirpl1_new.yaml

@@ -1,41 +1,5 @@
 run_title: ''
 
-visualizer:
-  kind: directory
-  outdir: ./visualizer-output/celeba/train_ablv2_work_no_segmpl_csdilirpl_celeba_csdilirpl1_new/samples
-  key_order:
-  - image
-  - predicted_image
-  - discr_output_fake
-  - discr_output_real
-  - inpainted
-  rescale_keys:
-  - discr_output_fake
-  - discr_output_real
-trainer:
-  kwargs:
-    gpus: -1
-    accelerator: ddp
-    max_epochs: 40
-    gradient_clip_val: 1
-    log_gpu_memory: None
-    limit_train_batches: 25000
-    val_check_interval: 2600
-    log_every_n_steps: 250
-    precision: 32
-    terminate_on_nan: false
-    check_val_every_n_epoch: 1
-    num_sanity_val_steps: 8
-    replace_sampler_ddp: false
-    benchmark: true
-    resume_from_checkpoint: /group-volume/User-Driven-Content-Generation/e.logacheva/CelebA-HQ-inpainting/experiments/e.logacheva_2021-10-12_21-37-20_train_ablv2_work_no_segmpl_csdilirpl_celeba_csdilirpl1_new/models/last.ckpt
-  checkpoint_kwargs:
-    verbose: true
-    save_top_k: 5
-    save_last: true
-    period: 1
-    monitor: val_ssim_fid100_f1_total_mean
-    mode: max
 training_model:
   kind: default
   visualize_each_iters: 1000
@@ -58,18 +22,14 @@ losses:
   segm_pl:
     weight: 1
     imagenet_weights: true
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
 
 defaults:
   - location: celeba
   - data: abl-04-256-mh-dist-celeba
-  - evaluator: default_inpainted
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
+  - visualizer: directory
+  - evaluator: default_inpainted
+  - trainer: any_gpu_large_ssim_ddp_final_celeba
   - hydra: overrides

configs/training/ablv2_work_no_segmpl_csirpl.yaml

@@ -25,30 +25,12 @@ losses:
     arch_encoder: 'resnet50'
     segmentation: false
 
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
-
-visualizer:  # override only keys, the rest parameters are kept from defaults/visualizer
-  key_order:
-    - image
-    - predicted_image
-    - discr_output_fake
-    - discr_output_real
-    - inpainted
-  rescale_keys:
-    - discr_output_fake
-    - discr_output_real
-
 defaults:
   - location: docker
   - data: abl-04-256-mh-dist
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
   - visualizer: directory
   - evaluator: default_inpainted
   - trainer: any_gpu_large_ssim_ddp_final

configs/training/ablv2_work_no_segmpl_csirpl_celeba_csirpl03_new.yaml

@@ -1,39 +1,5 @@
 run_title: ''
 
-visualizer:
-  kind: directory
-  outdir: ./visualizer-output/celeba/train_ablv2_work_no_segmpl_csirpl_celeba_csirpl03_new/samples
-  key_order:
-  - image
-  - predicted_image
-  - discr_output_fake
-  - discr_output_real
-  - inpainted
-  rescale_keys:
-  - discr_output_fake
-  - discr_output_real
-trainer:
-  kwargs:
-    gpus: -1
-    accelerator: ddp
-    max_epochs: 40
-    gradient_clip_val: 1
-    log_gpu_memory: None
-    limit_train_batches: 25000
-    val_check_interval: 2600
-    log_every_n_steps: 250
-    precision: 32
-    terminate_on_nan: false
-    check_val_every_n_epoch: 1
-    num_sanity_val_steps: 8
-    replace_sampler_ddp: false
-  checkpoint_kwargs:
-    verbose: true
-    save_top_k: 5
-    save_last: true
-    period: 1
-    monitor: val_ssim_fid100_f1_total_mean
-    mode: max
 training_model:
   kind: default
   visualize_each_iters: 1000
@@ -57,18 +23,14 @@ losses:
     weight: 0.3
     arch_encoder: resnet50
     imagenet_weights: true
-optimizers:
-  generator:
-    kind: adam
-    lr: 0.001
-  discriminator:
-    kind: adam
-    lr: 0.0001
 
 defaults:
   - location: celeba
   - data: abl-04-256-mh-dist-celeba
-  - evaluator: default_inpainted
   - generator: pix2pixhd_global_sigmoid
   - discriminator: pix2pixhd_nlayer
+  - optimizers: default_optimizers
+  - visualizer: directory
+  - evaluator: default_inpainted
+  - trainer: any_gpu_large_ssim_ddp_final_celeba
   - hydra: overrides