CNTK/Scripts
Mark Hillebrand ac1a9469ef Bump release tags to v2.0.beta3.0, v2.0.beta3.0+ in CNTK.cpp 2016-11-10 09:13:44 +01:00
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linux Bump release tags to v2.0.beta3.0, v2.0.beta3.0+ in CNTK.cpp 2016-11-10 09:13:44 +01:00
windows Bump release tags to v2.0.beta3.0, v2.0.beta3.0+ in CNTK.cpp 2016-11-10 09:13:44 +01:00
README.md Scripts/README.md: minimal documentation for binary drop install scripts 2016-11-04 10:34:03 +01:00
pytest.ini
txt2ctf.py txt2ctf.py: escape pipe symbol 2016-10-28 15:44:26 +02:00
uci2ctf.py

README.md

This directory contains different scripts for using CNTK.

CNTK Binary Installers

  • windows/install.ps1: installation script for installing a Windows CNTK binary drop, cf. here.
  • linux/install-cntk.sh: installation script for installing a Linux CNTK binary drop, cf. here.

CNTK Text format Converters

Two Python Scripts for converting Data to CNTK Text format for using as an input for CNTK Text Format Reader (see https://github.com/microsoft/CNTK/wiki/CNTKTextFormat-Reader).

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.

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. Also see a usage example below:

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 https://github.com/Microsoft/CNTK/wiki/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.