%global _empty_manifest_terminate_build 0
Name:		python-tabnet
Version:	0.1.6
Release:	1
Summary:	Tensorflow 2.0 implementation of TabNet of any configuration.
License:	MIT
URL:		https://github.com/titu1994/tf-TabNet
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/85/84/470e95d5abe5eb5ece8cd89b89e5ff678e1b9e6e23a00045f8dd315fe6ba/tabnet-0.1.6.tar.gz
BuildArch:	noarch

Requires:	python3-tensorflow
Requires:	python3-tensorflow-gpu

%description
After the model has been forced into Eager Execution mode, the masks can be visualized in Tensorboard as follows - 
```python
writer = tf.summary.create_file_writer("logs/")
with writer.as_default():
    for i, mask in enumerate(model.tabnet.feature_selection_masks):
        print("Saving mask {} of shape {}".format(i + 1, mask.shape))
        tf.summary.image('mask_at_iter_{}'.format(i + 1), step=0, data=mask, max_outputs=1)
        writer.flush()
    agg_mask = model.tabnet.aggregate_feature_selection_mask
    print("Saving aggregate mask of shape", agg_mask.shape)
    tf.summary.image("Aggregate Mask", step=0, data=agg_mask, max_outputs=1)
    writer.flush()
writer.close()
```
# Requirements
- Tensorflow 2.0+ (1.14+ with V2 compat enabled may be sufficient for 1.x)
- Tensorflow-datasets (Only required for evaluating `train_iris.py`)

%package -n python3-tabnet
Summary:	Tensorflow 2.0 implementation of TabNet of any configuration.
Provides:	python-tabnet
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-tabnet
After the model has been forced into Eager Execution mode, the masks can be visualized in Tensorboard as follows - 
```python
writer = tf.summary.create_file_writer("logs/")
with writer.as_default():
    for i, mask in enumerate(model.tabnet.feature_selection_masks):
        print("Saving mask {} of shape {}".format(i + 1, mask.shape))
        tf.summary.image('mask_at_iter_{}'.format(i + 1), step=0, data=mask, max_outputs=1)
        writer.flush()
    agg_mask = model.tabnet.aggregate_feature_selection_mask
    print("Saving aggregate mask of shape", agg_mask.shape)
    tf.summary.image("Aggregate Mask", step=0, data=agg_mask, max_outputs=1)
    writer.flush()
writer.close()
```
# Requirements
- Tensorflow 2.0+ (1.14+ with V2 compat enabled may be sufficient for 1.x)
- Tensorflow-datasets (Only required for evaluating `train_iris.py`)

%package help
Summary:	Development documents and examples for tabnet
Provides:	python3-tabnet-doc
%description help
After the model has been forced into Eager Execution mode, the masks can be visualized in Tensorboard as follows - 
```python
writer = tf.summary.create_file_writer("logs/")
with writer.as_default():
    for i, mask in enumerate(model.tabnet.feature_selection_masks):
        print("Saving mask {} of shape {}".format(i + 1, mask.shape))
        tf.summary.image('mask_at_iter_{}'.format(i + 1), step=0, data=mask, max_outputs=1)
        writer.flush()
    agg_mask = model.tabnet.aggregate_feature_selection_mask
    print("Saving aggregate mask of shape", agg_mask.shape)
    tf.summary.image("Aggregate Mask", step=0, data=agg_mask, max_outputs=1)
    writer.flush()
writer.close()
```
# Requirements
- Tensorflow 2.0+ (1.14+ with V2 compat enabled may be sufficient for 1.x)
- Tensorflow-datasets (Only required for evaluating `train_iris.py`)

%prep
%autosetup -n tabnet-0.1.6

%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-tabnet -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.6-1
- Package Spec generated