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@@ -0,0 +1 @@ +/torch_complex-0.4.3.tar.gz diff --git a/python-torch-complex.spec b/python-torch-complex.spec new file mode 100644 index 0000000..e0b8440 --- /dev/null +++ b/python-torch-complex.spec @@ -0,0 +1,337 @@ +%global _empty_manifest_terminate_build 0 +Name: python-torch-complex +Version: 0.4.3 +Release: 1 +Summary: A fugacious python class for PyTorch-ComplexTensor +License: Apache Software License +URL: https://github.com/kamo-naoyuki/torch_complex +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/1d/fe/638980e57d68dd79fa94d7db43598b2c2bceb74a3715774d854476c556d1/torch_complex-0.4.3.tar.gz +BuildArch: noarch + +Requires: python3-numpy + +%description +# pytorch_complex + +[](https://badge.fury.io/py/torch-complex) +[](https://pypi.org/project/torch-complex/) +[](https://pepy.tech/project/torch-complex) +[](https://travis-ci.org/kamo-naoyuki/pytorch_complex) +[](https://codecov.io/gh/kamo-naoyuki/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, + +```python +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 +```python +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 + +```python +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. + +```python +x.cuda() +x.cpu() +(x + x).sum().backward() +``` + + + + +%package -n python3-torch-complex +Summary: A fugacious python class for PyTorch-ComplexTensor +Provides: python-torch-complex +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-torch-complex +# pytorch_complex + +[](https://badge.fury.io/py/torch-complex) +[](https://pypi.org/project/torch-complex/) +[](https://pepy.tech/project/torch-complex) +[](https://travis-ci.org/kamo-naoyuki/pytorch_complex) +[](https://codecov.io/gh/kamo-naoyuki/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, + +```python +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 +```python +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 + +```python +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. + +```python +x.cuda() +x.cpu() +(x + x).sum().backward() +``` + + + + +%package help +Summary: Development documents and examples for torch-complex +Provides: python3-torch-complex-doc +%description help +# pytorch_complex + +[](https://badge.fury.io/py/torch-complex) +[](https://pypi.org/project/torch-complex/) +[](https://pepy.tech/project/torch-complex) +[](https://travis-ci.org/kamo-naoyuki/pytorch_complex) +[](https://codecov.io/gh/kamo-naoyuki/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, + +```python +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 +```python +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 + +```python +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. + +```python +x.cuda() +x.cpu() +(x + x).sum().backward() +``` + + + + +%prep +%autosetup -n torch-complex-0.4.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-torch-complex -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.3-1 +- Package Spec generated @@ -0,0 +1 @@ +24e09f8f0d3e89821f3b25ff0db7e3d0 torch_complex-0.4.3.tar.gz |