Rename 2023-04-08T07-38-29-project.yaml to config.yaml

2023-04-08T07-38-29-project.yaml

@@ -1,39 +0,0 @@
-model:
-  learning_rate: 0.0003
-  target: celle_main.CELLE_trainer
-  params:
-    ckpt_path: logs/2023-03-04T12-17-47_HPA_celle_ESM2_1280/checkpoints/epoch=000020.ckpt
-    condition_model_path: logs/2022-11-07T17-17-51_OpenCell_nucleus_vqgan_finetune/checkpoints/epoch=000468.ckpt
-    condition_config_path: logs/2022-11-07T17-17-51_OpenCell_nucleus_vqgan_finetune/configs/2023-02-23T19-14-01-project.yaml
-    vqgan_model_path: logs/2023-02-13T11-37-10_OpenCell_threshold_vqgan_finetune/checkpoints/last.ckpt
-    vqgan_config_path: logs/2023-02-13T11-37-10_OpenCell_threshold_vqgan_finetune/configs/2023-02-13T11-37-10-project.yaml
-    image_key: threshold
-    num_images: 2
-    dim: 1280
-    num_text_tokens: 33
-    text_seq_len: 1000
-    depth: 25
-    heads: 16
-    dim_head: 64
-    attn_dropout: 0.1
-    ff_dropout: 0.1
-    attn_types: full
-    rotary_emb: true
-    fixed_embedding: true
-    monitor: val/loss_epoch
-    text_embedding: esm2
-    loss_img_weight: 1
-    loss_cond_weight: 1
-data:
-  target: celle_main.CellDataModule
-  params:
-    data_csv: /home/emaad/CELL-E_2/data/OpenCell/train_test_split_HPA_50.csv
-    dataset: OpenCell
-    sequence_mode: embedding
-    vocab: esm2
-    threshold: median
-    text_seq_len: 1000
-    crop_size: 256
-    resize: 600
-    batch_size: 1
-    num_workers: 8

config.yaml

@@ -0,0 +1,25 @@
+model:
+  learning_rate: 0.0003
+  target: celle_main.CELLE_trainer
+  params:
+    ckpt_path: model.ckpt
+    condition_model_path: 
+    condition_config_path: nucleus_vqgan.yaml
+    vqgan_model_path: 
+    vqgan_config_path: threshold_vqgan.yaml
+    image_key: threshold
+    num_images: 2
+    dim: 1280
+    num_text_tokens: 33
+    text_seq_len: 1000
+    depth: 25
+    heads: 16
+    dim_head: 64
+    attn_dropout: 0.1
+    ff_dropout: 0.1
+    attn_types: full
+    rotary_emb: true
+    fixed_embedding: true
+    text_embedding: esm2
+    loss_img_weight: 1
+    loss_cond_weight: 1