Bugfix/esd eval framework

mu/algorithms/esd/.gitignore

@@ -0,0 +1 @@
+src/*

mu/algorithms/esd/__init__.py

@@ -2,10 +2,12 @@
 from .model import ESDModel
 from .sampler import ESDSampler
 from .trainer import ESDTrainer
+from .evalutator import ESDEvaluator
 
 __all__ = [
     'ESDAlgorithm',
     'ESDModel',
     'ESDSampler',
     'ESDTrainer',
+    'ESDEvaluator'
 ]

mu/algorithms/esd/configs/evaluation_config.yaml

@@ -0,0 +1,20 @@
+model_config: "mu/algorithms/esd/configs/generate_sd.yaml"
+ckpt_path: "outputs/esd/finetuned_models/esd_Abstractionism_model.pth"
+theme: "Abstractionism"
+cfg_text: 9.0
+seed: 188
+task: "class"
+ddim_steps: 100
+image_height: 512
+image_width: 512
+ddim_eta: 0.0
+sampler_output_dir: "outputs/eval_results/mu_results/esd/"
+seed_list: ["188"]
+# classification_model: "vit_large_patch16_224.augreg_in21k"
+classification_model: "vit_large_patch16_224"
+classification_ckpt: "outputs/esd/finetuned_models/esd_Abstractionism_model.pth"
+eval_output_dir: "outputs/eval_results/mu_results/esd/"
+reference_dir: "/home/ubuntu/Projects/msu_unlearningalgorithm/data/quick-canvas-dataset/sample/"
+forget_theme: "Abstractionism"
+fid_output_path: "outputs/eval_results/mu_results/esd/"
+multiprocessing: "False"

mu/algorithms/esd/configs/generate_sd.yaml

@@ -0,0 +1,70 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: stable_diffusion.ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: stable_diffusion.ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: stable_diffusion.ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_heads: 8
+        use_spatial_transformer: True
+        transformer_depth: 1
+        context_dim: 768
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: stable_diffusion.ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: stable_diffusion.ldm.modules.encoders.modules.FrozenCLIPEmbedder

mu/algorithms/esd/configs/train_config.yaml

@@ -9,10 +9,12 @@ ddim_steps: 50  # Optional: DDIM steps of inference
 
 # Model configuration
 model_config_path: "mu/algorithms/esd/configs/model_config.yaml"
-ckpt_path: "models/compvis/style50/compvis.ckpt"  # Checkpoint path for Stable Diffusion
+ckpt_path: "/home/ubuntu/Projects/UnlearnCanvas/UnlearnCanvas/machine_unlearning/models/compvis/style50/compvis.ckpt"  # Checkpoint path for Stable Diffusion
 
 # Dataset directories
-raw_dataset_dir: "data/quick-canvas-dataset/sample"
+# raw_dataset_dir: "data/quick-canvas-dataset/sample"
+
+raw_dataset_dir: "/home/ubuntu/Projects/msu_unlearningalgorithm/data/quick-canvas-dataset/sample"
 processed_dataset_dir: "mu/algorithms/esd/data"
 dataset_type: "unlearncanvas"  # Choices: ['unlearncanvas', 'i2p']
 template: "style"  # Choices: ['object', 'style', 'i2p']

mu/algorithms/esd/environment.yaml

@@ -45,7 +45,7 @@ dependencies:
     - h5py # This is for ICL_Inpainting
     - xtcocotools # This is for ICL_Inpainting
     - natsort # This is for ICL_Inpainting
-    - timm==0.3.2 # This is for ICL_Inpainting
+    - timm==0.6.7 # This is for ICL_Inpainting
     - git+https://github.com/cocodataset/panopticapi.git # This is for ICL_Inpainting
     - fairscale # This is for ICL_Inpainting
     - git+https://github.com/facebookresearch/detectron2.git # This is for ICL_Inpainting