semvec/pypi-packages huggingface dataset:
graphpipe-tf 1.0.4
Graphpipe helpers for TensorFlow remote ops

# GraphPipe helpers for TensorFlow

This package contains helpers and examples for using GraphPipe with tensorflow.
It contains a new plug-in operation for tensorflow that makes a call to a
GraphPipe remote model from within a local tensorflow graph.  The new operation
is called remote_op and communicates with the remote model using libcurl and
the GraphPipe protocol.

Additionaly, a new keras layer is included based on the remote operation.  This
allows you to include a layer in a keras model that makes a remote call.

Finally, various examples are included of serving tensorflow models in python.
For production, a more performant server like
[`graphpipe-tf`](https://github.com/oracle/graphpipe-go/cmd/graphpipe-tf) is
recommended, but the python server is useful for experimentation.

## List Of Examples

 * [Jupyter Notebook: serving and querying VGG with
   GraphPipe](examples/RemoteModelWithGraphPipe.ipynb)
 * [Complete client/server example](examples/simple_request.py)
 * [Simple tensorflow model server](examples/model_server.py)
 * [Keras to GraphDef](examples/convert.py)
 * [Using a remote operation](examples/call_remote_op.py)
 * [Tensorflow graph to GraphDef](examples/tf_graph.py)

## Build

Building manually requires a few libraries to be installed, but the Makefile
will happily run a build for you in a docker container.
```
  make build
```

See `build_linux.sh` for the additional headers besides libcurl that you will
need to build the C library. (From tensorflow and flatbuffers)

If you've successfully built the C library, to build installation packages:

    python setup.py bdist_wheel

Note that these are not manylinux wheels and depend on libcurl being installed
graphpipe 1.0.4
Graphpipe client and helpers

# GraphPipe for python 

GraphPipe for python consists of the flatbuffer implementation (generated from
the [graphpipe project](https://github.com/graphpipe)), utilities for
converting between flatbuffers and python types, a client for making calls
to graphpipe services, and some simple examples.

To learn more about GraphPipe, see our [documentation](https://oracle.github.io/graphpipe/)

## Build

You can install from pypi like so:

```
  pip install graphpipe
```

You an also install directly from github with pip like so:

```
  pip install git+https://github.com/oracle/graphpipe-py
```

This is a pure python package, your setup.py knowledge should do the trick
if you are have checked out the code from github.

## Develop

The tox tests can be run via `make test` if you have docker installed.

To update the graphpipe flatbuffer files, you will need to `make python` in
the graphpipe project and copy the generated files into this repository's
`graphpipe/graphpipefb/` directory


To build installation packages:

```
    python setup.py sdist bdist_wheel
```
helium-cli 0.0.5
CLI application for working with the Helium application.
Keywords: helium cli

# helium-cli
CLI application for the Helium application for mac.


## Installation:
### Source:
To install the application from source you need to start by cloning this repository. Run the following command in your terminal:
```
git clone https://github.com/JHowell45/helium-cli.git
```
Afterwards to install `cd` into the `helium-cli` application directory and run the following command:
```
pip install .
```