automatic import of python-thinc

3 files changed, 560 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..da86858 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/thinc-8.1.9.tar.gz
diff --git a/python-thinc.spec b/python-thinc.spec
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--- /dev/null
+++ b/python-thinc.spec
@@ -0,0 +1,558 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-thinc
+Version:	8.1.9
+Release:	1
+Summary:	A refreshing functional take on deep learning, compatible with your favorite libraries
+License:	MIT
+URL:		https://github.com/explosion/thinc
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/31/4d/7c07727e1d4f08e307c367c6574baf5f44fd5c4e1dfb06ea8606d047c02a/thinc-8.1.9.tar.gz
+
+Requires:	python3-blis
+Requires:	python3-murmurhash
+Requires:	python3-cymem
+Requires:	python3-preshed
+Requires:	python3-wasabi
+Requires:	python3-srsly
+Requires:	python3-catalogue
+Requires:	python3-confection
+Requires:	python3-setuptools
+Requires:	python3-numpy
+Requires:	python3-pydantic
+Requires:	python3-packaging
+Requires:	python3-dataclasses
+Requires:	python3-contextvars
+Requires:	python3-typing-extensions
+Requires:	python3-cupy
+Requires:	python3-cupy-wheel
+Requires:	python3-cupy-cuda100
+Requires:	python3-cupy-cuda101
+Requires:	python3-cupy-cuda102
+Requires:	python3-cupy-cuda110
+Requires:	python3-cupy-cuda111
+Requires:	python3-cupy-cuda112
+Requires:	python3-cupy-cuda113
+Requires:	python3-cupy-cuda114
+Requires:	python3-cupy-cuda115
+Requires:	python3-cupy-cuda116
+Requires:	python3-cupy-cuda117
+Requires:	python3-cupy-cuda11x
+Requires:	python3-cupy-cuda80
+Requires:	python3-cupy-cuda90
+Requires:	python3-cupy-cuda91
+Requires:	python3-cupy-cuda92
+Requires:	python3-ml-datasets
+Requires:	python3-mxnet
+Requires:	python3-tensorflow
+Requires:	python3-torch
+
+%description
+<a href="https://explosion.ai"><img src="https://explosion.ai/assets/img/logo.svg" width="125" height="125" align="right" /></a>
+
+# Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries
+
+### From the makers of [spaCy](https://spacy.io) and [Prodigy](https://prodi.gy)
+
+[Thinc](https://thinc.ai) is a **lightweight deep learning library** that offers an elegant,
+type-checked, functional-programming API for **composing models**, with support
+for layers defined in other frameworks such as **PyTorch, TensorFlow and MXNet**. You
+can use Thinc as an interface layer, a standalone toolkit or a flexible way to
+develop new models. Previous versions of Thinc have been running quietly in
+production in thousands of companies, via both [spaCy](https://spacy.io) and
+[Prodigy](https://prodi.gy). We wrote the new version to let users **compose,
+configure and deploy custom models** built with their favorite framework.
+
+[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/7/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=7)
+[![Current Release Version](https://img.shields.io/github/v/release/explosion/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=github)](https://github.com/explosion/thinc/releases)
+[![PyPi Version](https://img.shields.io/pypi/v/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/thinc)
+[![conda Version](https://img.shields.io/conda/vn/conda-forge/thinc.svg?style=flat-square&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/thinc)
+[![Python wheels](https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true&style=flat-square&logo=python&logoColor=white)](https://github.com/explosion/wheelwright/releases)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black)
+[![Open demo in Colab][colab]][intro_to_thinc_colab]
+
+## 🔥 Features
+
+- **Type-check** your model definitions with custom types and [`mypy`](https://mypy.readthedocs.io/en/latest/) plugin.
+- Wrap **PyTorch**, **TensorFlow** and **MXNet** models for use in your network.
+- Concise **functional-programming** approach to model definition, using composition rather than inheritance.
+- Optional custom infix notation via **operator overloading**.
+- Integrated **config system** to describe trees of objects and hyperparameters.
+- Choice of **extensible backends**.
+- **[Read more &rarr;](https://thinc.ai/docs)**
+
+## 🚀 Quickstart
+
+Thinc is compatible with **Python 3.6+** and runs on **Linux**,
+**macOS** and **Windows**. The latest releases with binary wheels are available from
+[pip](https://pypi.python.org/pypi/thinc). Before you install Thinc and its
+dependencies, make sure that your `pip`, `setuptools` and `wheel` are up to
+date. For the most recent releases, pip 19.3 or newer is recommended.
+
+```bash
+pip install -U pip setuptools wheel
+pip install thinc
+```
+
+See the [extended installation docs](https://thinc.ai/docs/install#extended) for details on optional dependencies for different backends and GPU. You might also want to [set up static type checking](https://thinc.ai/docs/install#type-checking) to take advantage of Thinc's type system.
+
+> ⚠️ If you have installed PyTorch and you are using Python 3.7+, uninstall the
+> package `dataclasses` with `pip uninstall dataclasses`, since it may have
+> been installed by PyTorch and is incompatible with Python 3.7+.
+
+### 📓 Selected examples and notebooks
+
+Also see the [`/examples`](examples) directory and [usage documentation](https://thinc.ai/docs) for more examples. Most examples are Jupyter notebooks – to launch them on [Google Colab](https://colab.research.google.com) (with GPU support!) click on the button next to the notebook name.
+
+| Notebook                                                                                                              | Description                                                                                                                                                                                       |
+| --------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [`intro_to_thinc`][intro_to_thinc]<br />[![Open in Colab][colab]][intro_to_thinc_colab]                               | Everything you need to know to get started. Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow and MXNet models. |
+| [`transformers_tagger_bert`][transformers_tagger_bert]<br />[![Open in Colab][colab]][transformers_tagger_bert_colab] | How to use Thinc, `transformers` and PyTorch to train a part-of-speech tagger. From model definition and config to the training loop.                                                             |
+| [`pos_tagger_basic_cnn`][pos_tagger_basic_cnn]<br />[![Open in Colab][colab]][pos_tagger_basic_cnn_colab]             | Implementing and training a basic CNN for part-of-speech tagging model without external dependencies and using different levels of Thinc's config system.                                         |
+| [`parallel_training_ray`][parallel_training_ray]<br />[![Open in Colab][colab]][parallel_training_ray_colab]          | How to set up synchronous and asynchronous parameter server training with Thinc and [Ray](https://ray.readthedocs.io/en/latest/).                                                                 |
+
+**[View more &rarr;](examples)**
+
+[colab]: https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg
+[intro_to_thinc]: examples/00_intro_to_thinc.ipynb
+[intro_to_thinc_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb
+[transformers_tagger_bert]: examples/02_transformers_tagger_bert.ipynb
+[transformers_tagger_bert_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/02_transformers_tagger_bert.ipynb
+[pos_tagger_basic_cnn]: examples/03_pos_tagger_basic_cnn.ipynb
+[pos_tagger_basic_cnn_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/03_pos_tagger_basic_cnn.ipynb
+[parallel_training_ray]: examples/04_parallel_training_ray.ipynb
+[parallel_training_ray_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/04_parallel_training_ray.ipynb
+
+### 📖 Documentation & usage guides
+
+| Documentation                                                                     | Description                                           |
+| --------------------------------------------------------------------------------- | ----------------------------------------------------- |
+| [Introduction](https://thinc.ai/docs)                                             | Everything you need to know.                          |
+| [Concept & Design](https://thinc.ai/docs/concept)                                 | Thinc's conceptual model and how it works.            |
+| [Defining and using models](https://thinc.ai/docs/usage-models)                   | How to compose models and update state.               |
+| [Configuration system](https://thinc.ai/docs/usage-config)                        | Thinc's config system and function registry.          |
+| [Integrating PyTorch, TensorFlow & MXNet](https://thinc.ai/docs/usage-frameworks) | Interoperability with machine learning frameworks     |
+| [Layers API](https://thinc.ai/docs/api-layers)                                    | Weights layers, transforms, combinators and wrappers. |
+| [Type Checking](https://thinc.ai/docs/usage-type-checking)                        | Type-check your model definitions and more.           |
+
+## 🗺 What's where
+
+| Module                                    | Description                                                                       |
+| ----------------------------------------- | --------------------------------------------------------------------------------- |
+| [`thinc.api`](thinc/api.py)               | **User-facing API.** All classes and functions should be imported from here.      |
+| [`thinc.types`](thinc/types.py)           | Custom [types and dataclasses](https://thinc.ai/docs/api-types).                  |
+| [`thinc.model`](thinc/model.py)           | The `Model` class. All Thinc models are an instance (not a subclass) of `Model`.  |
+| [`thinc.layers`](thinc/layers)            | The layers. Each layer is implemented in its own module.                          |
+| [`thinc.shims`](thinc/shims)              | Interface for external models implemented in PyTorch, TensorFlow etc.             |
+| [`thinc.loss`](thinc/loss.py)             | Functions to calculate losses.                                                    |
+| [`thinc.optimizers`](thinc/optimizers.py) | Functions to create optimizers. Currently supports "vanilla" SGD, Adam and RAdam. |
+| [`thinc.schedules`](thinc/schedules.py)   | Generators for different rates, schedules, decays or series.                      |
+| [`thinc.backends`](thinc/backends)        | Backends for `numpy` and `cupy`.                                                  |
+| [`thinc.config`](thinc/config.py)         | Config parsing and validation and function registry system.                       |
+| [`thinc.util`](thinc/util.py)             | Utilities and helper functions.                                                   |
+
+## 🐍 Development notes
+
+Thinc uses [`black`](https://github.com/psf/black) for auto-formatting, [`flake8`](http://flake8.pycqa.org/en/latest/) for linting and [`mypy`](https://mypy.readthedocs.io/en/latest/) for type checking. All code is written compatible with **Python 3.6+**, with type hints wherever possible. See the [type reference](https://thinc.ai/docs/api-types) for more details on Thinc's custom types.
+
+### 👷‍♀️ Building Thinc from source
+
+Building Thinc from source requires the full dependencies listed in
+[`requirements.txt`](requirements.txt) to be installed. You'll also need a
+compiler to build the C extensions.
+
+```bash
+git clone https://github.com/explosion/thinc
+cd thinc
+python -m venv .env
+source .env/bin/activate
+pip install -U pip setuptools wheel
+pip install -r requirements.txt
+pip install --no-build-isolation .
+```
+
+Alternatively, install in editable mode:
+
+```bash
+pip install -r requirements.txt
+pip install --no-build-isolation --editable .
+```
+
+Or by setting `PYTHONPATH`:
+
+```bash
+export PYTHONPATH=`pwd`
+pip install -r requirements.txt
+python setup.py build_ext --inplace
+```
+
+### 🚦 Running tests
+
+Thinc comes with an [extensive test suite](thinc/tests). The following should all pass and not report any warnings or errors:
+
+```bash
+python -m pytest thinc    # test suite
+python -m mypy thinc      # type checks
+python -m flake8 thinc    # linting
+```
+
+To view test coverage, you can run `python -m pytest thinc --cov=thinc`. We aim for a 100% test coverage. This doesn't mean that we meticulously write tests for every single line – we ignore blocks that are not relevant or difficult to test and make sure that the tests execute all code paths.
+
+
+%package -n python3-thinc
+Summary:	A refreshing functional take on deep learning, compatible with your favorite libraries
+Provides:	python-thinc
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+BuildRequires:	python3-cffi
+BuildRequires:	gcc
+BuildRequires:	gdb
+%description -n python3-thinc
+<a href="https://explosion.ai"><img src="https://explosion.ai/assets/img/logo.svg" width="125" height="125" align="right" /></a>
+
+# Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries
+
+### From the makers of [spaCy](https://spacy.io) and [Prodigy](https://prodi.gy)
+
+[Thinc](https://thinc.ai) is a **lightweight deep learning library** that offers an elegant,
+type-checked, functional-programming API for **composing models**, with support
+for layers defined in other frameworks such as **PyTorch, TensorFlow and MXNet**. You
+can use Thinc as an interface layer, a standalone toolkit or a flexible way to
+develop new models. Previous versions of Thinc have been running quietly in
+production in thousands of companies, via both [spaCy](https://spacy.io) and
+[Prodigy](https://prodi.gy). We wrote the new version to let users **compose,
+configure and deploy custom models** built with their favorite framework.
+
+[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/7/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=7)
+[![Current Release Version](https://img.shields.io/github/v/release/explosion/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=github)](https://github.com/explosion/thinc/releases)
+[![PyPi Version](https://img.shields.io/pypi/v/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/thinc)
+[![conda Version](https://img.shields.io/conda/vn/conda-forge/thinc.svg?style=flat-square&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/thinc)
+[![Python wheels](https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true&style=flat-square&logo=python&logoColor=white)](https://github.com/explosion/wheelwright/releases)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black)
+[![Open demo in Colab][colab]][intro_to_thinc_colab]
+
+## 🔥 Features
+
+- **Type-check** your model definitions with custom types and [`mypy`](https://mypy.readthedocs.io/en/latest/) plugin.
+- Wrap **PyTorch**, **TensorFlow** and **MXNet** models for use in your network.
+- Concise **functional-programming** approach to model definition, using composition rather than inheritance.
+- Optional custom infix notation via **operator overloading**.
+- Integrated **config system** to describe trees of objects and hyperparameters.
+- Choice of **extensible backends**.
+- **[Read more &rarr;](https://thinc.ai/docs)**
+
+## 🚀 Quickstart
+
+Thinc is compatible with **Python 3.6+** and runs on **Linux**,
+**macOS** and **Windows**. The latest releases with binary wheels are available from
+[pip](https://pypi.python.org/pypi/thinc). Before you install Thinc and its
+dependencies, make sure that your `pip`, `setuptools` and `wheel` are up to
+date. For the most recent releases, pip 19.3 or newer is recommended.
+
+```bash
+pip install -U pip setuptools wheel
+pip install thinc
+```
+
+See the [extended installation docs](https://thinc.ai/docs/install#extended) for details on optional dependencies for different backends and GPU. You might also want to [set up static type checking](https://thinc.ai/docs/install#type-checking) to take advantage of Thinc's type system.
+
+> ⚠️ If you have installed PyTorch and you are using Python 3.7+, uninstall the
+> package `dataclasses` with `pip uninstall dataclasses`, since it may have
+> been installed by PyTorch and is incompatible with Python 3.7+.
+
+### 📓 Selected examples and notebooks
+
+Also see the [`/examples`](examples) directory and [usage documentation](https://thinc.ai/docs) for more examples. Most examples are Jupyter notebooks – to launch them on [Google Colab](https://colab.research.google.com) (with GPU support!) click on the button next to the notebook name.
+
+| Notebook                                                                                                              | Description                                                                                                                                                                                       |
+| --------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [`intro_to_thinc`][intro_to_thinc]<br />[![Open in Colab][colab]][intro_to_thinc_colab]                               | Everything you need to know to get started. Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow and MXNet models. |
+| [`transformers_tagger_bert`][transformers_tagger_bert]<br />[![Open in Colab][colab]][transformers_tagger_bert_colab] | How to use Thinc, `transformers` and PyTorch to train a part-of-speech tagger. From model definition and config to the training loop.                                                             |
+| [`pos_tagger_basic_cnn`][pos_tagger_basic_cnn]<br />[![Open in Colab][colab]][pos_tagger_basic_cnn_colab]             | Implementing and training a basic CNN for part-of-speech tagging model without external dependencies and using different levels of Thinc's config system.                                         |
+| [`parallel_training_ray`][parallel_training_ray]<br />[![Open in Colab][colab]][parallel_training_ray_colab]          | How to set up synchronous and asynchronous parameter server training with Thinc and [Ray](https://ray.readthedocs.io/en/latest/).                                                                 |
+
+**[View more &rarr;](examples)**
+
+[colab]: https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg
+[intro_to_thinc]: examples/00_intro_to_thinc.ipynb
+[intro_to_thinc_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb
+[transformers_tagger_bert]: examples/02_transformers_tagger_bert.ipynb
+[transformers_tagger_bert_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/02_transformers_tagger_bert.ipynb
+[pos_tagger_basic_cnn]: examples/03_pos_tagger_basic_cnn.ipynb
+[pos_tagger_basic_cnn_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/03_pos_tagger_basic_cnn.ipynb
+[parallel_training_ray]: examples/04_parallel_training_ray.ipynb
+[parallel_training_ray_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/04_parallel_training_ray.ipynb
+
+### 📖 Documentation & usage guides
+
+| Documentation                                                                     | Description                                           |
+| --------------------------------------------------------------------------------- | ----------------------------------------------------- |
+| [Introduction](https://thinc.ai/docs)                                             | Everything you need to know.                          |
+| [Concept & Design](https://thinc.ai/docs/concept)                                 | Thinc's conceptual model and how it works.            |
+| [Defining and using models](https://thinc.ai/docs/usage-models)                   | How to compose models and update state.               |
+| [Configuration system](https://thinc.ai/docs/usage-config)                        | Thinc's config system and function registry.          |
+| [Integrating PyTorch, TensorFlow & MXNet](https://thinc.ai/docs/usage-frameworks) | Interoperability with machine learning frameworks     |
+| [Layers API](https://thinc.ai/docs/api-layers)                                    | Weights layers, transforms, combinators and wrappers. |
+| [Type Checking](https://thinc.ai/docs/usage-type-checking)                        | Type-check your model definitions and more.           |
+
+## 🗺 What's where
+
+| Module                                    | Description                                                                       |
+| ----------------------------------------- | --------------------------------------------------------------------------------- |
+| [`thinc.api`](thinc/api.py)               | **User-facing API.** All classes and functions should be imported from here.      |
+| [`thinc.types`](thinc/types.py)           | Custom [types and dataclasses](https://thinc.ai/docs/api-types).                  |
+| [`thinc.model`](thinc/model.py)           | The `Model` class. All Thinc models are an instance (not a subclass) of `Model`.  |
+| [`thinc.layers`](thinc/layers)            | The layers. Each layer is implemented in its own module.                          |
+| [`thinc.shims`](thinc/shims)              | Interface for external models implemented in PyTorch, TensorFlow etc.             |
+| [`thinc.loss`](thinc/loss.py)             | Functions to calculate losses.                                                    |
+| [`thinc.optimizers`](thinc/optimizers.py) | Functions to create optimizers. Currently supports "vanilla" SGD, Adam and RAdam. |
+| [`thinc.schedules`](thinc/schedules.py)   | Generators for different rates, schedules, decays or series.                      |
+| [`thinc.backends`](thinc/backends)        | Backends for `numpy` and `cupy`.                                                  |
+| [`thinc.config`](thinc/config.py)         | Config parsing and validation and function registry system.                       |
+| [`thinc.util`](thinc/util.py)             | Utilities and helper functions.                                                   |
+
+## 🐍 Development notes
+
+Thinc uses [`black`](https://github.com/psf/black) for auto-formatting, [`flake8`](http://flake8.pycqa.org/en/latest/) for linting and [`mypy`](https://mypy.readthedocs.io/en/latest/) for type checking. All code is written compatible with **Python 3.6+**, with type hints wherever possible. See the [type reference](https://thinc.ai/docs/api-types) for more details on Thinc's custom types.
+
+### 👷‍♀️ Building Thinc from source
+
+Building Thinc from source requires the full dependencies listed in
+[`requirements.txt`](requirements.txt) to be installed. You'll also need a
+compiler to build the C extensions.
+
+```bash
+git clone https://github.com/explosion/thinc
+cd thinc
+python -m venv .env
+source .env/bin/activate
+pip install -U pip setuptools wheel
+pip install -r requirements.txt
+pip install --no-build-isolation .
+```
+
+Alternatively, install in editable mode:
+
+```bash
+pip install -r requirements.txt
+pip install --no-build-isolation --editable .
+```
+
+Or by setting `PYTHONPATH`:
+
+```bash
+export PYTHONPATH=`pwd`
+pip install -r requirements.txt
+python setup.py build_ext --inplace
+```
+
+### 🚦 Running tests
+
+Thinc comes with an [extensive test suite](thinc/tests). The following should all pass and not report any warnings or errors:
+
+```bash
+python -m pytest thinc    # test suite
+python -m mypy thinc      # type checks
+python -m flake8 thinc    # linting
+```
+
+To view test coverage, you can run `python -m pytest thinc --cov=thinc`. We aim for a 100% test coverage. This doesn't mean that we meticulously write tests for every single line – we ignore blocks that are not relevant or difficult to test and make sure that the tests execute all code paths.
+
+
+%package help
+Summary:	Development documents and examples for thinc
+Provides:	python3-thinc-doc
+%description help
+<a href="https://explosion.ai"><img src="https://explosion.ai/assets/img/logo.svg" width="125" height="125" align="right" /></a>
+
+# Thinc: A refreshing functional take on deep learning, compatible with your favorite libraries
+
+### From the makers of [spaCy](https://spacy.io) and [Prodigy](https://prodi.gy)
+
+[Thinc](https://thinc.ai) is a **lightweight deep learning library** that offers an elegant,
+type-checked, functional-programming API for **composing models**, with support
+for layers defined in other frameworks such as **PyTorch, TensorFlow and MXNet**. You
+can use Thinc as an interface layer, a standalone toolkit or a flexible way to
+develop new models. Previous versions of Thinc have been running quietly in
+production in thousands of companies, via both [spaCy](https://spacy.io) and
+[Prodigy](https://prodi.gy). We wrote the new version to let users **compose,
+configure and deploy custom models** built with their favorite framework.
+
+[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/7/master.svg?logo=azure-pipelines&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=7)
+[![Current Release Version](https://img.shields.io/github/v/release/explosion/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=github)](https://github.com/explosion/thinc/releases)
+[![PyPi Version](https://img.shields.io/pypi/v/thinc.svg?include_prereleases&sort=semver&style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/thinc)
+[![conda Version](https://img.shields.io/conda/vn/conda-forge/thinc.svg?style=flat-square&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/thinc)
+[![Python wheels](https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true&style=flat-square&logo=python&logoColor=white)](https://github.com/explosion/wheelwright/releases)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/ambv/black)
+[![Open demo in Colab][colab]][intro_to_thinc_colab]
+
+## 🔥 Features
+
+- **Type-check** your model definitions with custom types and [`mypy`](https://mypy.readthedocs.io/en/latest/) plugin.
+- Wrap **PyTorch**, **TensorFlow** and **MXNet** models for use in your network.
+- Concise **functional-programming** approach to model definition, using composition rather than inheritance.
+- Optional custom infix notation via **operator overloading**.
+- Integrated **config system** to describe trees of objects and hyperparameters.
+- Choice of **extensible backends**.
+- **[Read more &rarr;](https://thinc.ai/docs)**
+
+## 🚀 Quickstart
+
+Thinc is compatible with **Python 3.6+** and runs on **Linux**,
+**macOS** and **Windows**. The latest releases with binary wheels are available from
+[pip](https://pypi.python.org/pypi/thinc). Before you install Thinc and its
+dependencies, make sure that your `pip`, `setuptools` and `wheel` are up to
+date. For the most recent releases, pip 19.3 or newer is recommended.
+
+```bash
+pip install -U pip setuptools wheel
+pip install thinc
+```
+
+See the [extended installation docs](https://thinc.ai/docs/install#extended) for details on optional dependencies for different backends and GPU. You might also want to [set up static type checking](https://thinc.ai/docs/install#type-checking) to take advantage of Thinc's type system.
+
+> ⚠️ If you have installed PyTorch and you are using Python 3.7+, uninstall the
+> package `dataclasses` with `pip uninstall dataclasses`, since it may have
+> been installed by PyTorch and is incompatible with Python 3.7+.
+
+### 📓 Selected examples and notebooks
+
+Also see the [`/examples`](examples) directory and [usage documentation](https://thinc.ai/docs) for more examples. Most examples are Jupyter notebooks – to launch them on [Google Colab](https://colab.research.google.com) (with GPU support!) click on the button next to the notebook name.
+
+| Notebook                                                                                                              | Description                                                                                                                                                                                       |
+| --------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [`intro_to_thinc`][intro_to_thinc]<br />[![Open in Colab][colab]][intro_to_thinc_colab]                               | Everything you need to know to get started. Composing and training a model on the MNIST data, using config files, registering custom functions and wrapping PyTorch, TensorFlow and MXNet models. |
+| [`transformers_tagger_bert`][transformers_tagger_bert]<br />[![Open in Colab][colab]][transformers_tagger_bert_colab] | How to use Thinc, `transformers` and PyTorch to train a part-of-speech tagger. From model definition and config to the training loop.                                                             |
+| [`pos_tagger_basic_cnn`][pos_tagger_basic_cnn]<br />[![Open in Colab][colab]][pos_tagger_basic_cnn_colab]             | Implementing and training a basic CNN for part-of-speech tagging model without external dependencies and using different levels of Thinc's config system.                                         |
+| [`parallel_training_ray`][parallel_training_ray]<br />[![Open in Colab][colab]][parallel_training_ray_colab]          | How to set up synchronous and asynchronous parameter server training with Thinc and [Ray](https://ray.readthedocs.io/en/latest/).                                                                 |
+
+**[View more &rarr;](examples)**
+
+[colab]: https://gistcdn.githack.com/ines/dcf354aa71a7665ae19871d7fd14a4e0/raw/461fc1f61a7bc5860f943cd4b6bcfabb8c8906e7/colab-badge.svg
+[intro_to_thinc]: examples/00_intro_to_thinc.ipynb
+[intro_to_thinc_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/00_intro_to_thinc.ipynb
+[transformers_tagger_bert]: examples/02_transformers_tagger_bert.ipynb
+[transformers_tagger_bert_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/02_transformers_tagger_bert.ipynb
+[pos_tagger_basic_cnn]: examples/03_pos_tagger_basic_cnn.ipynb
+[pos_tagger_basic_cnn_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/03_pos_tagger_basic_cnn.ipynb
+[parallel_training_ray]: examples/04_parallel_training_ray.ipynb
+[parallel_training_ray_colab]: https://colab.research.google.com/github/explosion/thinc/blob/master/examples/04_parallel_training_ray.ipynb
+
+### 📖 Documentation & usage guides
+
+| Documentation                                                                     | Description                                           |
+| --------------------------------------------------------------------------------- | ----------------------------------------------------- |
+| [Introduction](https://thinc.ai/docs)                                             | Everything you need to know.                          |
+| [Concept & Design](https://thinc.ai/docs/concept)                                 | Thinc's conceptual model and how it works.            |
+| [Defining and using models](https://thinc.ai/docs/usage-models)                   | How to compose models and update state.               |
+| [Configuration system](https://thinc.ai/docs/usage-config)                        | Thinc's config system and function registry.          |
+| [Integrating PyTorch, TensorFlow & MXNet](https://thinc.ai/docs/usage-frameworks) | Interoperability with machine learning frameworks     |
+| [Layers API](https://thinc.ai/docs/api-layers)                                    | Weights layers, transforms, combinators and wrappers. |
+| [Type Checking](https://thinc.ai/docs/usage-type-checking)                        | Type-check your model definitions and more.           |
+
+## 🗺 What's where
+
+| Module                                    | Description                                                                       |
+| ----------------------------------------- | --------------------------------------------------------------------------------- |
+| [`thinc.api`](thinc/api.py)               | **User-facing API.** All classes and functions should be imported from here.      |
+| [`thinc.types`](thinc/types.py)           | Custom [types and dataclasses](https://thinc.ai/docs/api-types).                  |
+| [`thinc.model`](thinc/model.py)           | The `Model` class. All Thinc models are an instance (not a subclass) of `Model`.  |
+| [`thinc.layers`](thinc/layers)            | The layers. Each layer is implemented in its own module.                          |
+| [`thinc.shims`](thinc/shims)              | Interface for external models implemented in PyTorch, TensorFlow etc.             |
+| [`thinc.loss`](thinc/loss.py)             | Functions to calculate losses.                                                    |
+| [`thinc.optimizers`](thinc/optimizers.py) | Functions to create optimizers. Currently supports "vanilla" SGD, Adam and RAdam. |
+| [`thinc.schedules`](thinc/schedules.py)   | Generators for different rates, schedules, decays or series.                      |
+| [`thinc.backends`](thinc/backends)        | Backends for `numpy` and `cupy`.                                                  |
+| [`thinc.config`](thinc/config.py)         | Config parsing and validation and function registry system.                       |
+| [`thinc.util`](thinc/util.py)             | Utilities and helper functions.                                                   |
+
+## 🐍 Development notes
+
+Thinc uses [`black`](https://github.com/psf/black) for auto-formatting, [`flake8`](http://flake8.pycqa.org/en/latest/) for linting and [`mypy`](https://mypy.readthedocs.io/en/latest/) for type checking. All code is written compatible with **Python 3.6+**, with type hints wherever possible. See the [type reference](https://thinc.ai/docs/api-types) for more details on Thinc's custom types.
+
+### 👷‍♀️ Building Thinc from source
+
+Building Thinc from source requires the full dependencies listed in
+[`requirements.txt`](requirements.txt) to be installed. You'll also need a
+compiler to build the C extensions.
+
+```bash
+git clone https://github.com/explosion/thinc
+cd thinc
+python -m venv .env
+source .env/bin/activate
+pip install -U pip setuptools wheel
+pip install -r requirements.txt
+pip install --no-build-isolation .
+```
+
+Alternatively, install in editable mode:
+
+```bash
+pip install -r requirements.txt
+pip install --no-build-isolation --editable .
+```
+
+Or by setting `PYTHONPATH`:
+
+```bash
+export PYTHONPATH=`pwd`
+pip install -r requirements.txt
+python setup.py build_ext --inplace
+```
+
+### 🚦 Running tests
+
+Thinc comes with an [extensive test suite](thinc/tests). The following should all pass and not report any warnings or errors:
+
+```bash
+python -m pytest thinc    # test suite
+python -m mypy thinc      # type checks
+python -m flake8 thinc    # linting
+```
+
+To view test coverage, you can run `python -m pytest thinc --cov=thinc`. We aim for a 100% test coverage. This doesn't mean that we meticulously write tests for every single line – we ignore blocks that are not relevant or difficult to test and make sure that the tests execute all code paths.
+
+
+%prep
+%autosetup -n thinc-8.1.9
+
+%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-thinc -f filelist.lst
+%dir %{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 8.1.9-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..3b6ac9b
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+d14cf6f7720196fad490d709d744adfd  thinc-8.1.9.tar.gz