From a5aa846b94df887a9ddd3c385e69835507ea8643 Mon Sep 17 00:00:00 2001 From: rohitgr7 Date: Thu, 7 Apr 2022 15:33:38 +0530 Subject: [PATCH 1/2] Bump version of black to 22.3.0 --- .pre-commit-config.yaml | 2 +- .../01-introduction-to-pytorch/Introduction_to_PyTorch.py | 2 +- .../Initialization_and_Optimization.py | 4 ++-- .../Deep_Energy_Models.py | 2 +- course_UvA-DL/11-vision-transformer/Vision_Transformer.py | 2 +- 5 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 24af5442d..3aa0c433e 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -41,7 +41,7 @@ repos: - id: isort - repo: https://github.com/psf/black - rev: 21.12b0 + rev: 22.3.0 hooks: - id: black name: Format code diff --git a/course_UvA-DL/01-introduction-to-pytorch/Introduction_to_PyTorch.py b/course_UvA-DL/01-introduction-to-pytorch/Introduction_to_PyTorch.py index 201b03444..f58d93057 100644 --- a/course_UvA-DL/01-introduction-to-pytorch/Introduction_to_PyTorch.py +++ b/course_UvA-DL/01-introduction-to-pytorch/Introduction_to_PyTorch.py @@ -314,7 +314,7 @@ # %% a = x + 2 -b = a ** 2 +b = a**2 c = b + 3 y = c.mean() print("Y", y) diff --git a/course_UvA-DL/03-initialization-and-optimization/Initialization_and_Optimization.py b/course_UvA-DL/03-initialization-and-optimization/Initialization_and_Optimization.py index 9ab3fcd68..fdf27edbc 100644 --- a/course_UvA-DL/03-initialization-and-optimization/Initialization_and_Optimization.py +++ b/course_UvA-DL/03-initialization-and-optimization/Initialization_and_Optimization.py @@ -1042,8 +1042,8 @@ def train_curve(optimizer_func, curve_func=pathological_curve_loss, num_updates= # %% def bivar_gaussian(w1, w2, x_mean=0.0, y_mean=0.0, x_sig=1.0, y_sig=1.0): norm = 1 / (2 * np.pi * x_sig * y_sig) - x_exp = (-1 * (w1 - x_mean) ** 2) / (2 * x_sig ** 2) - y_exp = (-1 * (w2 - y_mean) ** 2) / (2 * y_sig ** 2) + x_exp = (-1 * (w1 - x_mean) ** 2) / (2 * x_sig**2) + y_exp = (-1 * (w2 - y_mean) ** 2) / (2 * y_sig**2) return norm * torch.exp(x_exp + y_exp) diff --git a/course_UvA-DL/07-deep-energy-based-generative-models/Deep_Energy_Models.py b/course_UvA-DL/07-deep-energy-based-generative-models/Deep_Energy_Models.py index 537238ce2..2d29e6dfb 100644 --- a/course_UvA-DL/07-deep-energy-based-generative-models/Deep_Energy_Models.py +++ b/course_UvA-DL/07-deep-energy-based-generative-models/Deep_Energy_Models.py @@ -497,7 +497,7 @@ def training_step(self, batch, batch_idx): real_out, fake_out = self.cnn(inp_imgs).chunk(2, dim=0) # Calculate losses - reg_loss = self.hparams.alpha * (real_out ** 2 + fake_out ** 2).mean() + reg_loss = self.hparams.alpha * (real_out**2 + fake_out**2).mean() cdiv_loss = fake_out.mean() - real_out.mean() loss = reg_loss + cdiv_loss diff --git a/course_UvA-DL/11-vision-transformer/Vision_Transformer.py b/course_UvA-DL/11-vision-transformer/Vision_Transformer.py index 2da68ee66..53072d601 100644 --- a/course_UvA-DL/11-vision-transformer/Vision_Transformer.py +++ b/course_UvA-DL/11-vision-transformer/Vision_Transformer.py @@ -287,7 +287,7 @@ def __init__( self.patch_size = patch_size # Layers/Networks - self.input_layer = nn.Linear(num_channels * (patch_size ** 2), embed_dim) + self.input_layer = nn.Linear(num_channels * (patch_size**2), embed_dim) self.transformer = nn.Sequential( *(AttentionBlock(embed_dim, hidden_dim, num_heads, dropout=dropout) for _ in range(num_layers)) ) From 54c4ff1ad4497e89acbf3c6e1431166aeeb2ae94 Mon Sep 17 00:00:00 2001 From: rohitgr7 Date: Thu, 7 Apr 2022 15:45:23 +0530 Subject: [PATCH 2/2] fix example --- course_UvA-DL/11-vision-transformer/Vision_Transformer.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/course_UvA-DL/11-vision-transformer/Vision_Transformer.py b/course_UvA-DL/11-vision-transformer/Vision_Transformer.py index 53072d601..0d14a2e64 100644 --- a/course_UvA-DL/11-vision-transformer/Vision_Transformer.py +++ b/course_UvA-DL/11-vision-transformer/Vision_Transformer.py @@ -403,8 +403,8 @@ def train_model(**kwargs): model = ViT.load_from_checkpoint(trainer.checkpoint_callback.best_model_path) # Test best model on validation and test set - val_result = trainer.test(model, test_dataloaders=val_loader, verbose=False) - test_result = trainer.test(model, test_dataloaders=test_loader, verbose=False) + val_result = trainer.test(model, dataloaders=val_loader, verbose=False) + test_result = trainer.test(model, dataloaders=test_loader, verbose=False) result = {"test": test_result[0]["test_acc"], "val": val_result[0]["test_acc"]} return model, result