Revision 1aab76af99f2e007b2ceb4da3daa95d71daa675f authored by Spandan Tiwari on 27 September 2018, 01:01:34 UTC, committed by Spandan Tiwari on 27 September 2018, 01:01:34 UTC
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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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