Create config.py

config.py

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+import torch
+
+debug = True
+image_path = ""
+captions_path = ""
+
+dataset_root = "/data/comps"
+train_json = "/data/comps/train.json"
+val_json = "/data/comps/val.json"
+
+
+batch_size = 200
+num_workers = 5
+head_lr = 1e-3
+image_encoder_lr = 1e-4
+text_encoder_lr = 1e-5
+weight_decay = 1e-3
+patience = 2
+factor = 0.8
+epochs = 350
+
+gpu = 1
+device = torch.device(f"cuda:{gpu}" if torch.cuda.is_available() else "cpu")
+
+model_name = 'efficientnet_b2'
+image_embedding = 1408
+
+# model_name = 'resnet50'
+# image_embedding = 1000
+
+text_encoder_model = "neuralspace-reverie/indic-transformers-bn-bert" 
+text_tokenizer = "neuralspace-reverie/indic-transformers-bn-bert"
+max_length = 100
+
+model_tag = f"{model_name}_{text_encoder_model.replace('/', '_')}_aug"
+log_tag = model_tag
+
+pretrained = True # for both image encoder and text encoder
+trainable = True # for both image encoder and text encoder
+temperature = 1.0
+
+# image size
+size = 224
+
+# proj. head
+num_projection_layers = 1
+projection_dim = 256 
+dropout = 0.1