https://github.com/Microsoft/CNTK
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Tip revision: a05c3c642648373f4ede0956e4286257c3d59a61 authored by liqfu on 24 August 2018, 17:46:51 UTC
CNTK splice allows broadcast. This case is handled in the change. For noop (identity) ops, its inputs and outputs types shall be set according to upstream ops. ToBatch/ToSequence and Unpack Batch/Sequence ops added during model importing need tp be skipped. Model import need to handle ops with multiple outputs.
Tip revision: a05c3c6
README.md
This directory contains different scripts to support CNTK.

## CNTK Binary Installers

The directory `install` contains scripts which are used in the CNTK binary download to install
CNTK on a users system. They are NOT intended to run from this location in the repository.

* `install/windows` - A script for installing a Windows CNTK *binary* drop, cf. [here](https://docs.microsoft.com/en-us/cognitive-toolkit/Setup-Windows-Binary-Script).
* `install/linux` - A script for installing a Linux CNTK *binary* drop, cf. [here](https://docs.microsoft.com/en-us/cognitive-toolkit/Setup-Linux-Binary-Script).

## CNTK Text format Converters

Two Python Scripts for converting Data to CNTK Text format for using as an input for CNTK Text Format Reader (https://docs.microsoft.com/en-us/cognitive-toolkit/BrainScript-CNTKTextFormat-Reader).

### Convert Dictionary to Text

`txt2ctf.py` converts a set of dictionary files and a plain text file to CNTK Text format.

Run `python txt2ctf.py -h` to see usage instructions. See the comments in the beginning of the script file for the specific usage example.

### Convert UCI Format to Text

`uci2ctf.py` converts data stored in a text file in UCI format to CNTK Text format.

Run `python uci2ctf.py -h` to see usage instructions and example.

For Example:

```
python Scripts/uci2ctf.py --input_file Examples/Image/MNIST/Data/Train-28x28.txt --features_start 1 --features_dim 784 --labels_start 0 --labels_dim 1 --num_labels 10  --output_file examples/Image/MNIST/Data/Train-28x28_cntk_text.txt
```

* `input_file` - original dataset in the (columnar) UCI format
* `features_start` - index of the first feature column (start parameter in the UCIFastReader config, see [here](https://docs.microsoft.com/en-us/cognitive-toolkit/BrainScript-UCI-Fast-Reader)
* `features_dim` - number of feature columns (dim parameter in the UCIFastReader config)
* `labels_start` - index of the first label column
* `labels_dim` - number of label columns
* `num_labels` - number of possible label values (labelDim parameter in the UCIFastReader config)
* `output_file` - path and filename of the resulting dataset.

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