tensorflow-qnd 0.0.4

# tensorflow-qnd

[](https://badge.fury.io/py/tensorflow-qnd)
[](https://travis-ci.org/raviqqe/tensorflow-qnd)
[](https://unlicense.org)

Quick and Distributed TensorFlow command framework

tensorflow-qnd is a TensorFlow framework to create commands to experiment with
models on multiple computers.
While made to be used on multiple computers in a cluster, this library is also
useful to exploit multiple GPUs on a single machine.


## Installation

Python 3.5+ and TensorFlow 0.12+ are required.

```
$ pip3 install --user --upgrade tensorflow-qnd
```


## Usage

```
def_run(batch_inputs=True, prepare_filename_queues=True)
Define `run()` function.

See also `help(def_run())`.

Args:
batch_inputs: If `True`, create batches from Tensors
returned from `train_input_fn()` and `train_input_fn()` and feed
them to a model.
prepare_filename_queues: If `True`, create filename queues for train
and eval data based on file paths specified by command line
arguments.

Returns:
`run()` function.


run(model_fn, train_input_fn, eval_input_fn=None)
Run `tf.contrib.learn.python.learn.learn_runner.run()`.

Args:
model_fn: A function to construct a model.
Types of its arguments must be one of the following:
`Tensor, ...`,
`Tensor, ..., mode=ModeKeys`.
Types of its return values must be one of the following:
`Tensor, Tensor, Operation, eval_metrics=dict<str, Tensor>`
(predictions, loss, train_op, and eval_metrics (if any)),
`ModelFnOps`.
train_input_fn, eval_input_fn: Functions to serve input Tensors
fed into the model. If `eval_input_fn` is `None`,
`train_input_fn` will be used instead.
Types of its arguments must be one of the following:
`QueueBase` (a filename queue),
`None` (No argument).
Types of its return values must be one of the following:
`Tensor, Tensor` (x and y),
`dict<str, Tensor>, dict<str, Tensor>`
(features and labels).
The keys of `dict` arguments must match with names of
`model_fn` arguments.

Returns:
Return value of `tf.contrib.learn.python.learn.learn_runner.run()`.


add_flag(name, *args, **kwargs)
Add a flag.

Args:
name: Flag name. Real flag name will be `"--{}".format(name)`.
*args, **kwargs: The rest arguments are the same as
`argparse.add_argument()`.


add_required_flag(name, *args, **kwargs)
Add a required flag.

Its interface is the same as `add_flag()` but `required=True` is set by
default.
```


## Examples

See [examples](examples) directory.


## License

[The Unlicense](https://unlicense.org)