relu with clamp and with torch.nn.functional

relu.py

import torch
import torch.nn.functional as F

#----------- Implementing the math -----------#

def relu(z):
  return torch.clamp(z, 0, None) # None specifies that we don't require an upper-bound

z = torch.tensor([[-0.2], [0.], [0.6]]) # Three neurons with different values

relu = relu(z)

#----------- Using Pytorch -----------#

torch_relu = F.relu(z)

#----------- Comparing outputs -----------#

print(f"Pytorch ReLU: \n{torch_relu} \nOur ReLU: \n{relu}")
'''
Out:
Pytorch ReLU: 
tensor([[0.0000],[0.0000],[0.6000]]) 
Our ReLU: 
tensor([[0.0000],[0.0000],[0.6000]])
'''