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Shahid Akhtar Khan has Published 216 Articles
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
2K+ Views
We can apply a 2D transposed convolution operation over an input image composed of several input planes using the torch.nn.ConvTranspose2d() module. This module can be seen as the gradient of Conv2d with respect to its input.The input to a 2D transpose convolution layer must be of size [N, C, H, ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
7K+ Views
We can apply a 2D convolution operation over an input image composed of several input planes using the torch.nn.Conv2d() module. It is implemented as a layer in a convolutional neural network (CNN). The input to a 2D convolution layer must be of size [N, C, H, W] where N is ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
985 Views
A temporal data can be represented as a 1D tensor, and spatial data as 2D tensor while a volumetric data can be represented as a 3D tensor. The Upsample class provided by torch.nn module supports these types of data to be upsampled. But these data must be in the form ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
926 Views
The saturation of an image refers to the intensity of a color. The higher the saturation of a color, the more vivid it is. The lower the saturation of a color, the closer it is to gray.To adjust the saturation of an image, we apply adjust_saturation(). It's one of the ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
714 Views
We can apply a linear transformation to the input data using the torch.nn.Linear() module. It supports input data of type TensorFloat32. This is applied as a layer in the deep neural networks to perform linear transformation. The linear transform used −y = x * W ^ T + bHere x ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
5K+ Views
A tensor can be flattened into a one-dimensional tensor by reshaping it using the method torch.flatten(). This method supports both real and complex-valued input tensors. It takes a torch tensor as its input and returns a torch tensor flattened into one dimension.It takes two optional parameters, start_dim and end_dim. If ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
9K+ Views
To compute the cross entropy loss between the input and target (predicted and actual) values, we apply the function CrossEntropyLoss(). It is accessed from the torch.nn module. It creates a criterion that measures the cross entropy loss. It is a type of loss function provided by the torch.nn module.The loss ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
5K+ Views
Mean squared error is computed as the mean of the squared differences between the input and target (predicted and actual) values. To compute the mean squared error in PyTorch, we apply the MSELoss() function provided by the torch.nn module. It creates a criterion that measures the mean squared error. It ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
2K+ Views
A vector in PyTorch is a 1D tensor. To compute pairwise distance between two vectors, we can use the PairwiseDistance() function. It uses p-norm to compute the pairwise distance. PairwiseDistance is basically a class provided by the torch.nn module.The size of both the vectors must be same.Pairwise distance can be computed ... Read More
![Shahid Akhtar Khan](https://www.tutorialspoint.com/assets/profiles/394091/profile/60_2508042-1636180991.jpg)
Shahid Akhtar Khan
1K+ Views
The hue of an image refers to the three primary colors (red, blue, and yellow) and the three secondary colors (orange, green, and violet). To adjust the hue of an image, we apply adjust_hue(). It's one of the functional transforms provided by the torchvision.transforms module.adjust_hue() transformation accepts both PIL and ... Read More