A fugacious python class for PyTorch-ComplexTensor
Project description
pytorch_complex
A temporal python class for PyTorch-ComplexTensor
What is this?
A Python class to perform as ComplexTensor
in PyTorch: Nothing except for the following,
class ComplexTensor:
def __init__(self, ...):
self.real = torch.Tensor(...)
self.imag = torch.Tensor(...)
Why?
PyTorch is great DNN Python library, except that it doesn't support ComplexTensor
in Python level.
https://github.com/pytorch/pytorch/issues/755
I'm looking forward to the completion, but I need ComplexTensor
for now.
I created this cheap module for the temporal replacement of it. Thus, I'll throw away this project as soon as ComplexTensor
is completely supported!
Requirements
Python>=3.6
PyTorch>=1.0
Install
pip install torch_complex
How to use
Basic mathematical operation
import numpy as np
from torch_complex.tensor import ComplexTensor
real = np.random.randn(3, 10, 10)
imag = np.random.randn(3, 10, 10)
x = ComplexTensor(real, imag)
x.numpy()
x + x
x * x
x - x
x / x
x ** 1.5
x @ x # Batch-matmul
x.conj()
x.inverse() # Batch-inverse
All are implemented with combinations of computation of RealTensor
in python level, thus the speed is not good enough.
Functional
import torch_complex.functional as F
F.cat([x, x])
F.stack([x, x])
F.matmul(x, x) # Same as x @ x
F.einsum('bij,bjk,bkl->bil', [x, x, x])
For DNN
Almost all methods that torch.Tensor
has are implemented.
x.cuda()
x.cpu()
(x + x).sum().backward()
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