Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
The histogram of a tensor is computed using torch.histc(). It returns a histogram represented as a tensor. It takes four parameters: input, bins, min and max. It sorts the elements into equal width bins between min and max. It ignores the elements smaller than the min and greater than the max.StepsImport the required library. In all the following Python examples, the required Python libraries are torch and Matplotlib. Make sure you have already installed them.Create a tensor and print it.Compute torch.histc(input, bins=100, min=0, max=100). It returns a tensor of histogram values. Set bins, min, and max to appropriate values according ... Read More
RGB images have three channels, Red, Green, and Blue. We need to compute the mean of the image pixel values across these image channels. For this purpose, we use the method torch.mean(). But the input parameter to this method is a PyTorch tensor. So, we first convert the image to the PyTorch tensor and then apply this method. It returns the mean value of all the elements in the tensor. To find the mean across the image channels, we set the parameter dim = [1, 2].StepsImport the required library. In all the following Python examples, the required Python libraries are ... Read More
PyTorch provides a method torch.kthvalue() to find the k-th element of a tensor. It returns the value of the k-th element of tensor sorted in ascending order, and the index of the element in the original tensor.torch.topk() method is used to find the top "k" elements. It returns the top "k" or largest "k" elements in the tensor.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed it.Create a PyTorch tensor and print it.Compute torch.kthvalue(input, k). It returns two tensors. Assign these two tensors to two new variables ... Read More
A PyTorch tensor is like a numpy array. The only difference is that a tensor utilizes the GPUs to accelerate numeric computations. The mean of a tensor is computed using the torch.mean() method. It returns the mean value of all the elements in the input tensor. We can also compute the mean row-wise and column-wise, providing suitable axis or dim.The standard deviation of a tensor is computed using torch.std(). It returns the standard deviation of all the elements in the tensor. Like mean, we can also compute the standard deviation, row or column-wise.StepsImport the required library. In all the following ... Read More
To perform element-wise division on two tensors in PyTorch, we can use the torch.div() method. It divides each element of the first input tensor by the corresponding element of the second tensor. We can also divide a tensor by a scalar. A tensor can be divided by a tensor with same or different dimension. The dimension of the final tensor will be same as the dimension of the higher-dimensional tensor. If we divide a 1D tensor by a 2D tensor, then the final tensor will a 2D tensor.StepsImport the required library. In all the following Python examples, the required Python ... Read More
torch.mul() method is used to perform element-wise multiplication on tensors in PyTorch. It multiplies the corresponding elements of the tensors. We can multiply two or more tensors. We can also multiply scalar and tensors. Tensors with same or different dimensions can also be multiplied. The dimension of the final tensor will be same as the dimension of higher-dimensional tensor. Element-wise multiplication on tensors are also known as Hadamard product.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed it.Define two or more PyTorch tensors and print them. If ... Read More
To perform element-wise subtraction on tensors, we can use the torch.sub() method of PyTorch. The corresponding elements of the tensors are subtracted. We can subtract a scalar or tensor from another tensor. We can subtract a tensor from a tensor with same or different dimension. The dimension of the final tensor will be same as the dimension of the higher-dimensional tensor.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed it.Define two or more PyTorch tensors and print them. If you want to subtract a scalar quantity, define ... Read More
We can use torch.add() to perform element-wise addition on tensors in PyTorch. It adds the corresponding elements of the tensors. We can add a scalar or tensor to another tensor. We can add tensors with same or different dimensions. The dimension of the final tensor will be same as the dimension of the higher dimension tensor.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed it.Define two or more PyTorch tensors and print them. If you want to add a scalar quantity, define it.Add two or more tensors ... Read More
To resize a PyTorch tensor, we use the .view() method. We can increase or decrease the dimension of the tensor, but we have to make sure that the total number of elements in a tensor must match before and after the resize.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed it.Create a PyTorch tensor and print it.Resize the above-created tensor using .view() and assign the value to a variable. .view() does not resize the original tensor; it only gives a view with the new size, as its ... Read More
We access the size (or shape) of a tensor and the number of elements in the tensor as the metadata of the tensor. To access the size of a tensor, we use the .size() method and the shape of a tensor is accessed using .shape.Both .size() and .shape produce the same result. We use the torch.numel() function to find the total number of elements in the tensor.StepsImport the required library. Here, the required library is torch. Make sure that you have installed torch.Define a PyTorch tensor.Find the metadata of the tensor. Use .size() and .shape to access the size and ... Read More