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Super Kai (Kazuya Ito)
Super Kai (Kazuya Ito)

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exp and exp2 in PyTorch

#python #pytorch #exp #exp2

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*Memos:

exp() can get the 0D or more D tensor of the zero or more elements by ex from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

  • exp() can be used with torch or a tensor.
  • The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int, float, complex or bool).
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.
  • *A float tensor is returned unless an input tensor is complex tensor.
  • The formula is y = ex.
  • The graph in Desmos: Image description 
import torch my_tensor = torch.tensor([-2., -1., 0., 1., 2., 3.]) torch.exp(input=my_tensor) my_tensor.exp() # tensor([0.1353, 0.3679, 1.0000, 2.7183, 7.3891, 20.0855])  my_tensor = torch.tensor([[-2., -1., 0.], [1., 2., 3.]]) torch.exp(input=my_tensor) # tensor([[0.1353, 0.3679, 1.0000], # [2.7183, 7.3891, 20.0855]])  my_tensor = torch.tensor([[-2, -1, 0], [1, 2, 3]]) torch.exp(input=my_tensor) # tensor([[0.1353, 0.3679, 1.0000], # [2.7183, 7.3891, 20.0855]])  my_tensor = torch.tensor([[-2.+0.j, -1.+0.j, 0.+0.j], [1.+0.j, 2.+0.j, 3.+0.j]]) torch.exp(input=my_tensor) # tensor([[0.1353+0.j, 0.3679+0.j, 1.0000+0.j], # [2.7183+0.j, 7.3891+0.j, 20.0855+0.j]])  my_tensor = torch.tensor([[True, False, True], [False, True, False]]) torch.exp(input=my_tensor) # tensor([[2.7183, 1.0000, 2.7183], # [1.0000, 2.7183, 1.0000]])
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exp2() can get the 0D or more D tensor of the zero or more elements by 2x from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

  • exp2() can be used with torch or a tensor.
  • The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int, float, complex or bool).
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.
  • *A float tensor is returned unless an input tensor is complex tensor.
  • torch.exp2() is the alias of torch.special.exp2().
  • The formula is y = 2x.
  • The graph in Desmos: Image description 
import torch my_tensor = torch.tensor([-2., -1., 0., 1., 2., 3.]) torch.exp2(input=my_tensor) my_tensor.exp2() # tensor([0.2500, 0.5000, 1.0000, 2.0000, 4.0000, 8.0000])  my_tensor = torch.tensor([[-2., -1., 0.], [1., 2., 3.]]) torch.exp2(input=my_tensor) # tensor([[0.2500, 0.5000, 1.0000], # [2.0000, 4.0000, 8.0000]])  my_tensor = torch.tensor([[-2, -1, 0], [1, 2, 3]]) torch.exp2(input=my_tensor) # tensor([[0.2500, 0.5000, 1.0000], # [2.0000, 4.0000, 8.0000]])  my_tensor = torch.tensor([[-2.+0.j, -1.+0.j, 0.+0.j], [1.+0.j, 2.+0.j, 3.+0.j]]) torch.exp2(input=my_tensor) # tensor([[0.2500+0.j, 0.5000+0.j, 1.0000+0.j], # [2.0000+0.j, 4.0000+0.j, 8.0000+0.j]])  my_tensor = torch.tensor([[True, False, True], [False, True, False]]) torch.exp2(input=my_tensor) # tensor([[2., 1., 2.], # [1., 2., 1.]])
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