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Articles by Shahid Akhtar Khan
Page 16 of 17
How to find element-wise remainder in PyTorch?
Element-wise remainder when a tensor is divided by other tensor is computed using the torch.remainder() method. We can also apply torch.fmod() to find the remainder.The difference between these two methods is that in torch.remainder(), when the sign of result is different than the sign of divisor, then the divisor is added to the result; whereas in torch.fmod(), it is not added.Syntaxtorch.remainder(input, other) torch.fmod(input, other)ParametersInput – It is a PyTorch tensor or scalar, the dividend.Other – It is also a PyTorch tensor or scalar, the divisor.OutputIt returns a tensor of element-wise remainder values.StepsImport the torch library.Define tensors, the dividend and the ...
Read MoreHow to perform in-place operations in PyTorch?
In-place operations directly change the content of a tensor without making a copy of it. Since it does not create a copy of the input, it reduces the memory usage when dealing with high-dimensional data. An in-place operation helps to utilize less GPU memory.In PyTorch, in-place operations are always post-fixed with a "_", like add_(), mul_(), etc.StepsTo perform an in-place operation, one could follow the steps given below −Import the required library. The required library is torch.Define/create tensors on which in-place operation is to be performed.Perform both normal and in-place operations to see the clear difference between them.Display the tensors ...
Read MoreHow to compute the sine of elements of a tensor in PyTorch?
To compute the sine of elements of a tensor, we use the torch.sin() method. It returns a new tensor with the sine values of the elements of the original input tensor. It takes a tensor as the input parameter and outputs a 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 tensor and print it.Compute torch.sin(input). It takes input, a tensor as input parameter, and returns a new tensor with the sine values of elements of the input.Print the tensor with the sine values of ...
Read MoreHow to compare two tensors in PyTorch?
To compare two tensors element-wise in PyTorch, we use the torch.eq() method. It compares the corresponding elements and returns "True" if the two elements are same, else it returns "False". We can compare two tensors with same or different dimensions, but the size of both the tensors must match at non-singleton dimension.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.eq(input1, input2). It returns a tensor of "True" and/or "False". It compares the tensor element-wise, and returns True if the corresponding ...
Read MoreHow to sort the elements of a tensor in PyTorch?
To sort the elements of a tensor in PyTorch, we can use the torch.sort() method. This method returns two tensors. The first tensor is a tensor with sorted values of the elements and the second tensor is a tensor of indices of elements in the original tensor. We can compute the 2D tensors, row-wise and column-wise.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.To sort the elements of the above-created tensor, compute torch.sort(input, dim). Assign this value to a new ...
Read MoreHow to compute the Logarithm of elements of a tensor in PyTorch?
To compute the logarithm of elements of a tensor in PyTorch, we use the torch.log() method. It returns a new tensor with the natural logarithm values of the elements of the original input tensor. It takes a tensor as the input parameter and outputs a 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 tensor and print it.Compute torch.log(input). It takes input, a tensor, as the input parameter and returns a new tensor with the natural logarithm values of elements of the input.Print the tensor ...
Read MoreHow to get the data type of a tensor in PyTorch?
A PyTorch tensor is homogenous, i.e., all the elements of a tensor are of the same data type. We can access the data type of a tensor using the ".dtype" attribute of the tensor. It returns the data type of 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 tensor and print it.Compute T.dtype. Here T is the tensor of which we want to get the data type.Print the data type of the tensor.Example 1The following Python program shows how to get the data ...
Read MoreHow to squeeze and unsqueeze a tensor in PyTorch?
To squeeze a tensor, we use the torch.squeeze() method. It returns a new tensor with all the dimensions of the input tensor but removes size 1. For example, if the shape of the input tensor is (M ☓ 1 ☓ N ☓ 1 ☓ P), then the squeezed tensor will have the shape (M ☓ M ☓ P).To unsqueeze a tensor, we use the torch.unsqueeze() method. It returns a new tensor dimension of size 1 inserted at specific position.StepsImport the required library. In all the following Python examples, the required Python library is torch. Make sure you have already installed ...
Read MoreHow to compute the histogram of a tensor in PyTorch?
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 MoreHow to find mean across the image channels in PyTorch?
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 ...
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