%global _empty_manifest_terminate_build 0
Name:		python-early-stopping
Version:	0.1.3
Release:	1
Summary:	Early stopping for neural networks
License:	MIT License
URL:		https://pypi.org/project/early-stopping/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/1c/05/780882b8f4b582e09562f69dcc3ed11035b5c4fdf9c1e983456acf50d8f0/early-stopping-0.1.3.tar.gz
BuildArch:	noarch


%description
# Early Stopping

I'm too lazy to read the Tensorflow documentation, so I made this simple early stopper. After each training step, feed the object the testing loss result for that epoch and it will return a boolean that says whether or not to break the training loop. 
# Installation

Install through pip as shown:

```bash
pip install early-stopping
```
# Example Usage

```py
from early_stopping import EarlyStopping

early_stopper = EarlyStopping(
    depth=5,
    ignore=20,
    method='consistency'
)

# Your training loop
for epoch in range(EPOCHS):
    # Train step here
    # Test step here

    # Check if we should break the loop
    if early_stopper.check(testing_loss):
        print('BREAKING THE TRAINING LOOP')
        break

```



%package -n python3-early-stopping
Summary:	Early stopping for neural networks
Provides:	python-early-stopping
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-early-stopping
# Early Stopping

I'm too lazy to read the Tensorflow documentation, so I made this simple early stopper. After each training step, feed the object the testing loss result for that epoch and it will return a boolean that says whether or not to break the training loop. 
# Installation

Install through pip as shown:

```bash
pip install early-stopping
```
# Example Usage

```py
from early_stopping import EarlyStopping

early_stopper = EarlyStopping(
    depth=5,
    ignore=20,
    method='consistency'
)

# Your training loop
for epoch in range(EPOCHS):
    # Train step here
    # Test step here

    # Check if we should break the loop
    if early_stopper.check(testing_loss):
        print('BREAKING THE TRAINING LOOP')
        break

```



%package help
Summary:	Development documents and examples for early-stopping
Provides:	python3-early-stopping-doc
%description help
# Early Stopping

I'm too lazy to read the Tensorflow documentation, so I made this simple early stopper. After each training step, feed the object the testing loss result for that epoch and it will return a boolean that says whether or not to break the training loop. 
# Installation

Install through pip as shown:

```bash
pip install early-stopping
```
# Example Usage

```py
from early_stopping import EarlyStopping

early_stopper = EarlyStopping(
    depth=5,
    ignore=20,
    method='consistency'
)

# Your training loop
for epoch in range(EPOCHS):
    # Train step here
    # Test step here

    # Check if we should break the loop
    if early_stopper.check(testing_loss):
        print('BREAKING THE TRAINING LOOP')
        break

```



%prep
%autosetup -n early-stopping-0.1.3

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

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

%changelog
* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.3-1
- Package Spec generated