semvec/pypi-packages huggingface dataset:
tfstage 0.1.7
TensorFlow project scaffolding
License: MIT
Keywords: tensorflow scaffold scaffolding

# TF Stage

A fast and canonical project setup for TensorFlow models. The most difficult part of getting started with TensorFlow isn't deep learning, it's putting together hundreds of API calls into a cohesive model.

```
$ tfstage --help
usage: tfstage [-h] name

TensorFlow project scaffolding

positional arguments:
  name                  Project name
  install_dependencies  Install pip dependencies

optional arguments:
  -h, --help            show this help message and exit
```

## Usage

1. Install `tfstage`:

    ```
    pip install tfstage
    ```

2. Create a new empty project directory

    ```
    $ mkdir my_project/
    $ cd my_project/
    ```

3. Run `tfstage my_project`:

    ```
    $ tfstage my_project
    Project created: ./my_project
    ```

4. This stubs out an entire TensorFlow project, completely runnable using a simple XOR dataset and model. For example:

    ```
    $ python -m my_project.main --job-dir logs/

    ...

    INFO:tensorflow:Saving checkpoints for 1 into logs/model.ckpt.
    INFO:tensorflow:loss = 1.20236, step = 1
    INFO:tensorflow:Starting evaluation at 2017-07-13-18:22:20
    INFO:tensorflow:Restoring parameters from logs/model.ckpt-1

    ...
    ```

## Workflow

When starting a new project we run `tfstage`, run the code to verify everything works, then search and replace the `TODO` comments in the code which mark important changes.

## Environment

High-level description of a new project:

- main.py: defines command-line arguments and sets up [`learn_runner`](https://goo.gl/I6TwxA)
- experiment.py: defines a [`tf.contrib.learn.Experiment`](https://goo.gl/nMvwLx) for training
- inputs.py: defines the input pipeline for training and evaluation
- model.py: defines the model, loss, and training optimization
- augment.py: defines any data augmentation or feature engineering
- serve.py: defines placeholders for [TensorFlow Serving](https://goo.gl/bM3jpA) and [Google Cloud ML Engine predictions](https://goo.gl/yTBv2e).

In addition, several common files are created including:

- README.md
- requirements.txt for local _development_
- setup.py for local and GCE _deployment_
- .gitignore

### Local Deployment

```
PROJECT_NAME=my_project
MODULE_NAME="${PROJECT_NAME}.main"
PACKAGE_PATH="${PROJECT_NAME}/"
JOB_DIR=logs/

gcloud ml-engine local train \
  --module-name $MODULE_NAME \
  --package-path $PACKAGE_PATH \
  --job-dir $JOB_DIR \
  -- \
  [args]
```

### Cloud Deployment

```
MODULE_NAME="${PROJECT_NAME}.main"
PACKAGE_PATH="${PROJECT_NAME}/"
JOB_NAME="${PROJECT_NAME}_1"
JOB_DIR="gs://${PROJECT_NAME}/${JOB_NAME}"
REGION=us-east1

gcloud ml-engine jobs submit training $JOB_NAME \
  --job-dir $JOB_DIR \
  --module-name $MODULE_NAME \
  --package-path $PACKAGE_PATH \
  --region $REGION \
  -- \
  [args]
```
py-heat-magic 0.0.2
py-heat as IPython magic
License: MIT
Keywords: heatmap matplotlib profiling python IPython

heat
====

|pypiv| |pyv| |Licence| |Thanks|

IPython magic command to profile and view your python code as a heat map
using `py-heat`_.

Demo
----

|Demo|

In case the demo was too fast, here is a `snapshot`_ of the last step of the
demo for deeper contemplation :)

What is the magic command?
--------------------------

.. code:: python

    %%heat

Setup
-----

Using pip
~~~~~~~~~

.. code:: bash

    pip install py-heat-magic

Directly from the repository
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: bash

    git clone https://github.com/csurfer/pyheatmagic.git
    python pyheatmagic/setup.py install

Load Extension in IPython
~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

    %load_ext heat

Usage
-----

.. code:: python

    # To view the heatmap
    %%heat

    # To save the heatmap as a file
    %%heat -o file.png

Contributing
------------

Bug Reports and Feature Requests
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Please use `issue tracker`_ for reporting bugs or feature requests.

Development
~~~~~~~~~~~

Pull requests are most welcome.

Buy the developer a cup of coffee!
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If you found the utility helpful you can buy me a cup of coffee using

|Donate|



.. _py-heat: https://github.com/csurfer/pyheat

.. _snapshot: http://i.imgur.com/isxRNV0.png

.. _issue tracker: https://github.com/csurfer/pyheatmagic/issues

.. |Donate| image:: https://www.paypalobjects.com/webstatic/en_US/i/btn/png/silver-pill-paypal-34px.png
   :target: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=3BSBW7D45C4YN&lc=US&currency_code=USD&bn=PP%2dDonationsBF%3abtn_donate_SM%2egif%3aNonHosted

.. |Thanks| image:: https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg
   :target: https://saythanks.io/to/csurfer

.. |Demo| image:: http://i.imgur.com/IUtasPH.gif

.. |Licence| image:: https://img.shields.io/badge/license-MIT-blue.svg
   :target: https://raw.githubusercontent.com/csurfer/pyheatmagic/master/LICENSE

.. |pypiv| image:: https://img.shields.io/pypi/v/py-heat-magic.svg
   :target: https://pypi.python.org/pypi/py-heat-magic

.. |pyv| image:: https://img.shields.io/pypi/pyversions/py-heat-magic.svg
   :target: https://pypi.python.org/pypi/py-heat-magic