From 0c6c2a36fe32d3a1938d2e2ecea51581b01889d5 Mon Sep 17 00:00:00 2001 From: jmisilo Date: Sun, 30 Oct 2022 21:32:23 +0100 Subject: [PATCH 1/6] Implement changing temperature when making predictions --- src/evaluate.py | 10 +++++++++- src/model/loops.py | 4 ++-- src/model/model.py | 4 +++- src/predict.py | 10 +++++++++- 4 files changed, 23 insertions(+), 5 deletions(-) diff --git a/src/evaluate.py b/src/evaluate.py index ba1032f..7ef16cd 100644 --- a/src/evaluate.py +++ b/src/evaluate.py @@ -44,6 +44,14 @@ help='Path to the results folder' ) +parser.add_argument( + '-T', + '--temperature', + type=float, + default=1.0, + help='Temperature for sampling' +) + args = parser.parse_args() ckp_path = os.path.join(config.weights_dir, args.checkpoint_name) @@ -93,4 +101,4 @@ if not os.path.exists(save_path): os.mkdir(save_path) - evaluate_dataset(model, test_dataset, args.img_path, save_path) \ No newline at end of file + evaluate_dataset(model, test_dataset, args.img_path, save_path, args.temperature) \ No newline at end of file diff --git a/src/model/loops.py b/src/model/loops.py index 5278979..31f45ef 100644 --- a/src/model/loops.py +++ b/src/model/loops.py @@ -130,7 +130,7 @@ def test_step(model, dataset, img_path, num_examples=4): return Image.open(buf) -def evaluate_dataset(model, dataset, img_path, save_path): +def evaluate_dataset(model, dataset, img_path, save_path, temperature=1.0): ''' Evaluate model on dataset. @@ -147,7 +147,7 @@ def evaluate_dataset(model, dataset, img_path, save_path): img = Image.open(os.path.join(img_path, img_name)) with torch.no_grad(): - caption, _ = model(img) + caption, _ = model(img, temperature) plt.imshow(img) plt.title(caption) diff --git a/src/model/model.py b/src/model/model.py index e1b1fc0..6a87b34 100644 --- a/src/model/model.py +++ b/src/model/model.py @@ -146,7 +146,7 @@ def freeze_layers(self): for p in [*list(self.ie.parameters()), *list(self.td.parameters())[14:-14]]: # freeze everything, except 1st and last transformer layer in Decoder p.requires_grad = False - def forward(self, img): + def forward(self, img, temperature=1.0): ''' Caption generation for a single image. @@ -188,6 +188,8 @@ def forward(self, img): emb += pos_emb pred = self.td(emb) + pred = torch.softmax(pred / temperature, dim=-1) + _, pred = torch.max(pred, dim=1) last_token = pred[-1].item() diff --git a/src/predict.py b/src/predict.py index 1c5b427..9f6e426 100644 --- a/src/predict.py +++ b/src/predict.py @@ -43,6 +43,14 @@ help='Path to the results folder' ) +parser.add_argument( + '-T', + '--temperature', + type=float, + default=1.0, + help='Temperature for sampling' +) + args = parser.parse_args() # set seed @@ -87,7 +95,7 @@ model.eval() with torch.no_grad(): - caption, _ = model(img) + caption, _ = model(img, args.temperature) plt.imshow(img) plt.title(caption) From a91f62af3557f01b52190d736a6f116a903a145c Mon Sep 17 00:00:00 2001 From: jmisilo Date: Sun, 30 Oct 2022 22:34:59 +0100 Subject: [PATCH 2/6] Prevent temperature from being negative --- src/model/model.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/src/model/model.py b/src/model/model.py index 6a87b34..b60c59a 100644 --- a/src/model/model.py +++ b/src/model/model.py @@ -157,7 +157,10 @@ def forward(self, img, temperature=1.0): caption: generated caption [str] tokens: generated tokens [torch.Tensor] ''' - # only one image at a time + + if temperature <= 0.0: + temperature = 1.0 + print('Temperature must be positive. Setting it to 1.0') with torch.no_grad(): img_embedded = self.ie(img) From 25c5b1ccfbc95834e40a7fdadef47911c32bfc3e Mon Sep 17 00:00:00 2001 From: jmisilo Date: Mon, 31 Oct 2022 18:33:53 +0100 Subject: [PATCH 3/6] Save loss history in checkpoints --- src/training.py | 13 ++++++++++--- src/utils/load_ckp.py | 2 +- 2 files changed, 11 insertions(+), 4 deletions(-) diff --git a/src/training.py b/src/training.py index 1787bef..9486633 100644 --- a/src/training.py +++ b/src/training.py @@ -87,7 +87,11 @@ scaler = torch.cuda.amp.GradScaler() ckp_path = os.path.join(config.weights_dir, args.checkpoint_name) - start_epoch = load_ckp(ckp_path, model, optimizer, scheduler, scaler, device) if os.path.isfile(ckp_path) else 0 + start_epoch, total_train_loss, total_valid_loss = ( + load_ckp(ckp_path, model, optimizer, scheduler, scaler, device) + if os.path.isfile(ckp_path) else + 0, [], [] + ) # build train model process with experiment tracking from wandb wandb.init(project='clipXgpt2 captioner', config=config.__dict__) @@ -107,6 +111,9 @@ 'examples': wandb.Image(test_results) }) + total_train_loss.append(train_loss) + total_valid_loss.append(valid_loss) + if not os.path.exists(config.weights_dir): os.makedirs(config.weights_dir) @@ -114,12 +121,12 @@ torch.save( { 'epoch': epoch, - 'train_loss': train_loss, - 'valid_loss': valid_loss, 'model1_state_dict': model.state_dict(), 'optimizer_state_dict': optimizer.state_dict(), 'scheduler_state_dict': scheduler.state_dict(), 'scaler_state_dict': scaler.state_dict(), + 'tloss': total_train_loss, + 'vloss': total_valid_loss }, os.path.join(config.weights_dir, f'epoch_{epoch}.pt') ) \ No newline at end of file diff --git a/src/utils/load_ckp.py b/src/utils/load_ckp.py index 05116bf..2e7be76 100644 --- a/src/utils/load_ckp.py +++ b/src/utils/load_ckp.py @@ -22,7 +22,7 @@ def load_ckp(checkpoint_fpath, model, optimizer=None, scheduler=None, scaler=Non if scaler is not None: scaler.load_state_dict(checkpoint['scaler_state_dict']) - return checkpoint['epoch'] + return checkpoint['epoch'], checkpoint['tloss'], checkpoint['vloss'] def download_weights(checkpoint_fpath): ''' From e7519d4cede29075106b582a27fa3b3e4dc5358c Mon Sep 17 00:00:00 2001 From: jmisilo Date: Mon, 31 Oct 2022 18:44:08 +0100 Subject: [PATCH 4/6] Change one key in checkpoint --- src/training.py | 2 +- src/utils/load_ckp.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/training.py b/src/training.py index 9486633..d6d1555 100644 --- a/src/training.py +++ b/src/training.py @@ -121,7 +121,7 @@ torch.save( { 'epoch': epoch, - 'model1_state_dict': model.state_dict(), + 'model_state_dict': model.state_dict(), 'optimizer_state_dict': optimizer.state_dict(), 'scheduler_state_dict': scheduler.state_dict(), 'scaler_state_dict': scaler.state_dict(), diff --git a/src/utils/load_ckp.py b/src/utils/load_ckp.py index 2e7be76..de80b84 100644 --- a/src/utils/load_ckp.py +++ b/src/utils/load_ckp.py @@ -12,7 +12,7 @@ def load_ckp(checkpoint_fpath, model, optimizer=None, scheduler=None, scaler=Non checkpoint = torch.load(checkpoint_fpath, map_location=device) - model.load_state_dict(checkpoint['model1_state_dict']) + model.load_state_dict(checkpoint['model_state_dict']) if optimizer is not None: optimizer.load_state_dict(checkpoint['optimizer_state_dict']) From 39b7346133518b08ceedae54315bfd9ae712c37b Mon Sep 17 00:00:00 2001 From: jmisilo Date: Sun, 6 Nov 2022 12:46:25 +0100 Subject: [PATCH 5/6] Delete old examples --- examples/23012796.jpg | Bin 29580 -> 0 bytes examples/3787801.jpg | Bin 42551 -> 0 bytes examples/7757242158.jpg | Bin 38286 -> 0 bytes 3 files changed, 0 insertions(+), 0 deletions(-) delete mode 100644 examples/23012796.jpg delete mode 100644 examples/3787801.jpg delete mode 100644 examples/7757242158.jpg diff --git a/examples/23012796.jpg b/examples/23012796.jpg deleted file mode 100644 index 8c114267c1e32d8ac2dffb96a6da8299494e051a..0000000000000000000000000000000000000000 GIT binary patch literal 0 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a frozen CLIP, a fully trained Mapping Module (6x Transformer Encoder Layers) and with partially frozen GPT-2 (the first and last 14 layers were trained). -The training process was carried out using the [Kaggle](https://www.kaggle.com/) P100 GPU. Training time is about 2 x 11h (106 epochs) with a linearly changing learning rate (from 0 to 0.0001908) and batch size 64. Originally, the Model was supposed to be trained longer - which results in a non-standard LR. *I also tried a longer training session (150 epochs), but overtraining was noticeable.* +The training process was carried out using the [Kaggle](https://www.kaggle.com/) P100 GPU. Training time - about 3 x 11h (150 epochs) with a linear learning rate warmup (max LR `3e-3`) and batch size 64. -### Example results - -![Example1](./examples/23012796.jpg) +#### Loss and Learning Rate during training -![Example2](./examples/3787801.jpg) +![LOSSxLR](./examples/loss_lr.jpg) -![Example3](./examples/7757242158.jpg) +### Example results -As I said, the goal was to test the Model's ability to recognize the situation. In the next phase of the experiments, I will try to improve the Model process and parameters to achieve better captions with the same dataset. +![Example1](./examples/23012796.jpg) +![Example2](./examples/36979.jpg) +![Example3](./examples/89407459.jpg) ### Usage @@ -36,7 +36,10 @@ Create environment and install requirements: ```bash python -m venv venv +# for windows .\venv\Scripts\activate +# for linux/mac +source venv/bin/activate pip install -r requirements.txt ``` diff --git a/src/training.py b/src/training.py index d6d1555..1ccbe51 100644 --- a/src/training.py +++ b/src/training.py @@ -90,7 +90,7 @@ start_epoch, total_train_loss, total_valid_loss = ( load_ckp(ckp_path, model, optimizer, scheduler, scaler, device) if os.path.isfile(ckp_path) else - 0, [], [] + (0, [], []) ) # build train model process with experiment tracking from wandb diff --git a/src/utils/config.py b/src/utils/config.py index e3e5a17..1225945 100644 --- a/src/utils/config.py +++ b/src/utils/config.py @@ -15,8 +15,8 @@ class Config: num_workers: int = 2 train_size: int = 0.84 val_size: int = 0.13 - epochs: int = 200 - lr: int = 6e-3 + epochs: int = 150 + lr: int = 3e-3 k: float = 0.33 batch_size_exp: int = 6 ep_len: int = 4 diff --git a/src/utils/load_ckp.py b/src/utils/load_ckp.py index de80b84..1e5a2bf 100644 --- a/src/utils/load_ckp.py +++ b/src/utils/load_ckp.py @@ -29,4 +29,4 @@ def download_weights(checkpoint_fpath): Downloads weights from Google Drive. ''' - gdown.download('https://drive.google.com/uc?id=1lEufQVOETFEIhPdFDYaez31uroq_5Lby', checkpoint_fpath, quiet=False) \ No newline at end of file + gdown.download('https://drive.google.com/uc?id=10ieSMMJzE9EeiPIF3CMzeT4timiQTjHV', checkpoint_fpath, quiet=False) \ No newline at end of file