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 More

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

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 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

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 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