How to Compute the Error Function of a Tensor in PyTorch Last Updated : 03 May, 2022 Summarize Comments Improve Suggest changes Share Like Article Like Report In this article, we are going to cover how to compute the error function of a tensor in Python using PyTorch. torch.special.erf() method We can compute the error function of a tensor by using torch.special.erf() method. This method accepts the input tensor of any dimension and it returns a tensor with a computed error function with the same dimension as the input tensor. The below syntax is used to compute the error function of a tensor. Syntax: torch.special.erf(input) Parameters: input: This is our input tensor. Return: This method returns a tensor with computed error function of input tensor. Example 1: The following program is to understand how to compute the error function of the 1D tensor. Python3 # import required libraries import torch # creating a 1D tensor tens = torch.tensor([-0.7336, -0.9200, -0.4742, -0.4470, -0.3472]) # print above created tensor print("\n Input Tensor:", tens) # compute the error function er = torch.special.erf(tens) # Display result print("\n After Computed Error function :", er) Output: Example 2: The following program is to know how to compute the error function of a batch of tensors. Python3 # import required libraries import torch # creating a batch of tensor tens = torch.tensor([[[0.8636, -0.4195, -0.4681], [0.1265, 1.2233, 0.1978], [1.1389, 0.3686, 1.2339]], [[1.6362, 0.6235, 1.2631], [0.3336, 1.5336, 1.3677], [0.5637, 1.3236, 0.2696]]]) # print above created tensor print("\n\n Input Tensor: \n", tens) # compute the error function er = torch.special.erf(tens) # Display result print("\n\n After Computed Error function: \n", er) Output: Comment More infoAdvertise with us Next Article How to Compute the Logistic Sigmoid Function of Tensor Elements in PyTorch M mukulsomukesh Follow Improve Article Tags : Python Python-PyTorch Practice Tags : python Similar Reads How to Compute the Logistic Sigmoid Function of Tensor Elements in PyTorch In this article, we will see how to compute the logistic sigmoid function of Tensor Elements in PyTorch. The torch.special.expit() & torch.sigmoid() methods are logistic functions in a tensor. torch.sigmoid() is an alias of torch.special.expit() method. Â So, these methods will take the torch ten 2 min read How to compute the element-wise angle of given input tensor in PyTorch? In this article, we are going to see how to compute the element-wise angle of a given input tensor in PyTorch. torch.angle() method Pytorch is an open-source deep learning framework available with a Python and C++ interface. Pytorch resides inside the torch module. In PyTorch, we will use torch.angl 3 min read How To Sort The Elements of a Tensor in PyTorch? In this article, we are going to see how to sort the elements of a PyTorch Tensor in Python. To sort the elements of a PyTorch tensor, we use torch.sort() method. Â We can sort the elements along with columns or rows when the tensor is 2-dimensional. Syntax: torch.sort(input, dim=- 1, descending=Fals 3 min read How to Get the Value of a Tensor in PyTorch When working with PyTorch, a powerful and flexible deep learning framework, you often need to access and manipulate the values stored within tensors. Tensors are the core data structures in PyTorch, representing multi-dimensional arrays that can store various types of data, including scalars, vector 5 min read How to compute element-wise entropy of an input tensor in PyTorch In this article, we are going to discuss how to compute the element-wise entropy of an input tensor in PyTorch, we can compute this by using torch.special.entr() method. torch.special.entr() method torch.special.entr() method computes the element-wise entropy, This method accepts a tensor as input a 2 min read How to find the transpose of a tensor in PyTorch? In this article, we are going to discuss how to find the transpose of the tensor in PyTorch. The transpose is obtained by changing the rows to columns and columns to rows. we can transpose a tensor by using transpose() method. the below syntax is used to find the transpose of the tensor. Syntax: tor 2 min read Like