Python - PyTorch exp() method Last Updated : 26 May, 2020 Summarize Comments Improve Suggest changes Share Like Article Like Report PyTorch torch.exp() method returns a new tensor after getting the exponent of the elements of the input tensor. Syntax: torch.exp(input, out=None) Arguments input: This is input tensor. out: The output tensor. Return: It returns a Tensor. Let's see this concept with the help of few examples: Example 1: Python3 # Importing the PyTorch library import torch # A constant tensor of size n a = torch.randn(6) print(a) # Applying the exp function and # storing the result in 'out' out = torch.exp(a) print(out) Output: 1.0532 -1.9300 0.6392 -0.7519 0.9133 0.3998 [torch.FloatTensor of size 6] 2.8667 0.1451 1.8949 0.4715 2.4925 1.4915 [torch.FloatTensor of size 6] Example 2: Python3 # Importing the PyTorch library import torch # A constant tensor of size n a = torch.FloatTensor([1, 4, 6, 3]) print(a) # Applying the exp function and # storing the result in 'out' out = torch.exp(a) print(out) Output: 1 4 6 3 [torch.FloatTensor of size 4] 2.7183 54.5981 403.4288 20.0855 [torch.FloatTensor of size 4] Comment More infoAdvertise with us Next Article Python - PyTorch exp() method P PranchalKatiyar Follow Improve Article Tags : Python Python-PyTorch Practice Tags : python Similar Reads Python - PyTorch ceil() method PyTorch torch.ceil() method returns a new tensor having the ceil value of the elements of input, Which is the smallest integer larger than or equal to each element. Syntax: torch.ceil(inp, out=None) Arguments inp: This is input tensor. out: The output tensor. Return: It returns a Tensor. Let's see t 1 min read Python - PyTorch log() method PyTorch torch.log() method gives a new tensor having the natural logarithm of the elements of input tensor. Syntax: torch.log(input, out=None) Arguments input: This is input tensor. out: The output tensor. Return: It returns a Tensor. Let's see this concept with the help of few examples: Example 1: 1 min read Python - PyTorch add() method PyTorch torch.add() method adds a constant value to each element of the input tensor and returns a new modified tensor. Syntax: torch.add(inp, c, out=None) Arguments inp: This is input tensor. c: The value that is to be added to every element of tensor. out: This is optional parameter and it is the 1 min read Python - PyTorch clamp() method PyTorch torch.clamp() method clamps all the input elements into the range [ min, max ] and return a resulting tensor. Syntax: torch.clamp(inp, min, max, out=None) Arguments inp: This is input tensor. min: This is a number and specifies the lower-bound of the range to which input to be clamped. max: 2 min read Python - PyTorch div() method PyTorch torch.div() method divides every element of the input with a constant and returns a new modified tensor. Syntax: torch.div(inp, other, out=None) Arguments inp: This is input tensor. other: This is a number to be divided to each element of input inp. out: The output tensor. Return: It returns 1 min read Like