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config.json

@@ -1,5 +1,5 @@
 {
-  "save_path": "saved_standard_challenging_context32_nocond_cont_cont_all_cont",
+  "save_path": "saved_standard_challenging_context32_nocond_cont_cont_all_cont_eval",
   "model": {
     "base_learning_rate": 8e-05,
     "target": "latent_diffusion.ldm.models.diffusion.ddpm.LatentDiffusion",
@@ -28,7 +28,7 @@
             64,
             48
           ],
-          "in_channels": 166,
+          "in_channels": 8,
           "out_channels": 4,
           "model_channels": 192,
           "attention_resolutions": [
@@ -48,6 +48,18 @@
           "transformer_depth": 1
         }
       },
+      "temporal_encoder_config": {
+        "target": "latent_diffusion.ldm.modules.encoders.temporal_encoder.TemporalEncoder",
+        "params": {
+          "input_channels": 6,
+          "hidden_size": 1024,
+          "num_layers": 1,
+          "dropout": 0.1,
+          "output_channels": 4,
+          "output_height": 48,
+          "output_width": 64
+        }
+      },
       "first_stage_config": {
         "target": "latent_diffusion.ldm.models.autoencoder.AutoencoderKL",
         "params": {
@@ -81,8 +93,8 @@
   "data": {
     "target": "data.data_processing.datasets.DataModule",
     "params": {
-      "batch_size": 256,
-      "num_workers": 16,
+      "batch_size": 8,
+      "num_workers": 1,
       "wrap": false,
       "shuffle": true,
       "drop_last": true,
@@ -92,7 +104,7 @@
       "train": {
         "target": "data.data_processing.datasets.ActionsData",
         "params": {
-          "data_csv_path": "train_dataset/train_dataset.target_frames.csv",
+          "data_csv_path": "desktop_sequences_filtered_with_desktop_1.5k.challenging.train.target_frames.csv",
           "normalization": "standard",
           "context_length": 32
         }
@@ -106,7 +118,7 @@
       "limit_val_batches": 0,
       "accelerator": "gpu",
       "gpus": 1,
-      "accumulate_grad_batches": 1,
+      "accumulate_grad_batches": 999999,
       "gradient_clip_val": 1,
       "checkpoint_callback": true
     }