https://github.com/Microsoft/CNTK
Tip revision: dea4a4ec3d81fa0bc7b3de6a22039f3de1b3bb1b authored by Yuqing Tang on 16 January 2018, 02:13:12 UTC
Removed the description and test cases regarding gather op input and output shape as they are not in the scope of this CF.
Removed the description and test cases regarding gather op input and output shape as they are not in the scope of this CF.
Tip revision: dea4a4e
uci2ctf.py
import argparse
def convert(file_in, file_out, features_start, features_dim,
labels_start, labels_dim, num_labels, label_type='Category', mapping_file=None):
label_map = {}
if label_type == "Category":
if mapping_file is not None:
with open(mapping_file, 'r') as f:
for line in f.read().splitlines():
label_map[line] = len(label_map)
num_labels = max(num_labels, len(label_map))
else:
label_map = {str(x) : x for x in range(num_labels)}
input_file = open(file_in, 'r')
output_file = open(file_out, 'w')
for line in input_file.readlines():
values = line.split()
if label_type != 'None':
max_length = max(labels_start + labels_dim, features_start + features_dim)
if len(values) < (labels_dim + features_dim):
raise RuntimeError(("Too few input columns ({} out of expected {}) ")
.format(len(values), (labels_dim + features_dim)))
elif len(values) < max_length:
raise RuntimeError(
("Too few input columns ({} out of expected {}) ")
.format(len(values), max_length))
labels = values[labels_start:labels_start+labels_dim]
if label_type == 'Category':
one_hot = ['0'] * num_labels
# there's only one label
label = labels[0]
if label not in label_map:
raise RuntimeError(("Illegal label value: '{}'").format(label))
one_hot[label_map[label]] = '1'
labels = one_hot
output_file.write("|labels " + " ".join(labels))
output_file.write("\t")
elif len(values) < features_start+features_dim:
raise RuntimeError(
("Too few input columns ({} out of expected {}) ")
.format(len(values), features_start+features_dim))
output_file.write(
"|features " + " ".join(values[features_start:features_start+features_dim]))
output_file.write("\n")
input_file.close()
output_file.close()
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="UCI to CNTKText format converter",
epilog=("Quick example - converting MNIST data (see Examples/Image/MNIST):"
"\n\n\t"
"--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"
"\n\n"
"For more information please visit "
"https://docs.microsoft.com/en-us/cognitive-toolkit/BrainScript-CNTKTextFormat-Reader"),
formatter_class=argparse.RawTextHelpFormatter)
requiredNamed = parser.add_argument_group('required arguments')
requiredNamed.add_argument("-in", "--input_file",
help="input file path", required=True)
requiredNamed.add_argument("-fs", "--features_start", type=int,
help="start offset of feature columns", required=True)
requiredNamed.add_argument("-fd", "--features_dim", type=int,
help=("dimension of the feature vector "
"(number of feature columns in the input file)"),
required=True)
parser.add_argument("-lt", "--label_type", default="Category",
help=("Label type (indicates how the label columns should "
" be interpreted)"),
choices=["Category", "Regression", "None"])
parser.add_argument("-ls", "--labels_start", type=int,
help=("dimension of the label vector "
"(number of label columns in the input file)"))
parser.add_argument("-nl", "--num_labels", type=int,
help="number of possible label values "
"(required for categorical labels)")
parser.add_argument("-ld", "--labels_dim", type=int, default=1,
help=("dimension of the input label vector "
"(number of label columns in the input file, "
"default is 1)"))
parser.add_argument("--mapping_file",
help=("the path to a file used to map from the label value "
"to a numerical label identifier (if omitted, the "
"label value is interpreted as a numerical "
"identifier)"))
parser.add_argument("-out", "--output_file", help="output file path")
args = parser.parse_args()
# a number of sanity checks
if args.label_type != "None" and args.labels_start is None:
parser.error("-ls/--label_start is required when label type is not 'None'")
if args.label_type == "Category":
if args.num_labels is None:
parser.error("-nl/--num_labels is required when label type is 'Category'")
if args.labels_dim > 1:
parser.error("-ld/--labels_dim cannot be greater than 1 "
"when label type is 'Category'")
if args.label_type == "Regression":
if args.num_labels > args.labels_dim:
parser.error("-nl/--num_labels is optional and "
" cannot exceed -ld/--labels_dim "
" when label type is 'Regression'")
if args.label_type != 'None':
if (((args.labels_start <= args.features_start) and
(args.labels_start + args.labels_dim > args.features_start)) or
((args.labels_start > args.features_start) and
(args.features_start + args.features_dim > args.labels_start))):
parser.error("Label and feature column ranges must not overlap.")
file_in = args.input_file
file_out = args.output_file
if not file_out:
dot = file_in.rfind(".")
if dot == -1:
dot = len(file_in)
file_out = file_in[:dot] + "_cntk_text" + file_in[dot:]
print (" Converting from UCI format\n\t '{}'\n"
" to CNTK text format\n\t '{}'".format(file_in, file_out))
convert(file_in, file_out, args.features_start, args.features_dim,
args.labels_start, args.labels_dim, args.num_labels, args.label_type, args.mapping_file)