Add back utils.py.

deep_speech_2/demo_server.py

@@ -3,7 +3,7 @@ import os
 import time
 import random
 import argparse
-import distutils.util
+import functools
 from time import gmtime, strftime
 import SocketServer
 import struct
@@ -12,20 +12,11 @@ import paddle.v2 as paddle
 from data_utils.data import DataGenerator
 from model import DeepSpeech2Model
 from data_utils.utils import read_manifest
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('host_port',        int,    8086,    "Server's IP port.")
 add_arg('beam_size',        int,    500,    "Beam search width.")
 add_arg('num_conv_layers',  int,    2,      "# of convolution layers.")
@@ -68,8 +59,8 @@ add_arg('specgram_type',    str,
         'linear',
         "Audio feature type. Options: linear, mfcc.",
         choices=['linear', 'mfcc'])
-args = parser.parse_args()
 # yapf: disable
+args = parser.parse_args()
 
 
 class AsrTCPServer(SocketServer.TCPServer):
@@ -198,13 +189,6 @@ def start_server():
     server.serve_forever()
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=1)

deep_speech_2/evaluate.py

@@ -3,26 +3,17 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import distutils.util
 import argparse
+import functools
 import paddle.v2 as paddle
 from data_utils.data import DataGenerator
 from model import DeepSpeech2Model
 from error_rate import wer, cer
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('batch_size',       int,    128,    "Minibatch size.")
 add_arg('trainer_count',    int,    8,      "# of Trainers (CPUs or GPUs).")
 add_arg('beam_size',        int,    500,    "Beam search width.")
@@ -66,8 +57,8 @@ add_arg('specgram_type',    str,
         'linear',
         "Audio feature type. Options: linear, mfcc.",
         choices=['linear', 'mfcc'])
-args = parser.parse_args()
 # yapf: disable
+args = parser.parse_args()
 
 
 def evaluate():
@@ -120,13 +111,6 @@ def evaluate():
           (args.error_rate_type, num_ins, num_ins, error_sum / num_ins))
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=args.trainer_count)

deep_speech_2/infer.py

@@ -4,25 +4,16 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
-import distutils.util
+import functools
 import paddle.v2 as paddle
 from data_utils.data import DataGenerator
 from model import DeepSpeech2Model
 from error_rate import wer, cer
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('num_samples',      int,    10,     "# of samples to infer.")
 add_arg('trainer_count',    int,    8,      "# of Trainers (CPUs or GPUs).")
 add_arg('beam_size',        int,    500,    "Beam search width.")
@@ -65,8 +56,8 @@ add_arg('specgram_type',    str,
         'linear',
         "Audio feature type. Options: linear, mfcc.",
         choices=['linear', 'mfcc'])
-args = parser.parse_args()
 # yapf: disable
+args = parser.parse_args()
 
 
 def infer():
@@ -116,13 +107,6 @@ def infer():
               (args.error_rate_type, error_rate_func(target, result)))
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=args.trainer_count)

deep_speech_2/tools/build_vocab.py

@@ -7,26 +7,18 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
+import functools
 import codecs
 import json
 from collections import Counter
 import os.path
 import _init_paths
 from data_utils import utils
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('count_threshold',  int,    0,  "Truncation threshold for char counts.")
 add_arg('vocab_path',       str,
         'datasets/vocab/zh_vocab.txt',
@@ -37,8 +29,8 @@ add_arg('manifest_paths',   str,
         "You can provide multiple manifest files.",
         nargs='+',
         required=True)
-args = parser.parse_args()
 # yapf: disable
+args = parser.parse_args()
 
 
 def count_manifest(counter, manifest_path):
@@ -48,13 +40,6 @@ def count_manifest(counter, manifest_path):
             counter.update(char)
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
 

deep_speech_2/tools/compute_mean_std.py

@@ -4,24 +4,16 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
+import functools
 import _init_paths
 from data_utils.normalizer import FeatureNormalizer
 from data_utils.augmentor.augmentation import AugmentationPipeline
 from data_utils.featurizer.audio_featurizer import AudioFeaturizer
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('num_samples',      int,    2000,    "# of samples to for statistics.")
 add_arg('specgram_type',    str,
         'linear',
@@ -33,15 +25,8 @@ add_arg('manifest_path',    str,
 add_arg('output_path',    str,
         'mean_std.npz',
         "Filepath of write mean and stddev to (.npz).")
-args = parser.parse_args()
 # yapf: disable
-
-
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
+args = parser.parse_args()
 
 
 def main():

deep_speech_2/train.py

@@ -4,24 +4,15 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
-import distutils.util
+import functools
 import paddle.v2 as paddle
 from model import DeepSpeech2Model
 from data_utils.data import DataGenerator
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('batch_size',       int,    256,    "Minibatch size.")
 add_arg('trainer_count',    int,    8,      "# of Trainers (CPUs or GPUs).")
 add_arg('num_passes',       int,    200,    "# of training epochs.")
@@ -70,8 +61,8 @@ add_arg('shuffle_method',   str,
         'batch_shuffle_clipped',
         "Shuffle method.",
         choices=['instance_shuffle', 'batch_shuffle', 'batch_shuffle_clipped'])
-args = parser.parse_args()
 # yapf: disable
+args = parser.parse_args()
 
 
 def train():
@@ -123,13 +114,6 @@ def train():
         is_local=args.is_local)
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=args.trainer_count)

deep_speech_2/tune.py

@@ -4,26 +4,17 @@ from __future__ import division
 from __future__ import print_function
 
 import numpy as np
-import distutils.util
 import argparse
+import functools
 import paddle.v2 as paddle
 from data_utils.data import DataGenerator
 from model import DeepSpeech2Model
 from error_rate import wer
+from utils import add_arguments, print_arguments
 
-
-def add_arg(argname, type, default, help, **kwargs):
-    type = distutils.util.strtobool if type == bool else type
-    parser.add_argument(
-        "--" + argname,
-        default=default,
-        type=type,
-        help=help + ' Default: %(default)s.',
-        **kwargs)
-
-
-# yapf: disable
 parser = argparse.ArgumentParser(description=__doc__)
+add_arg = functools.partial(add_arguments, argparser=parser)
+# yapf: disable
 add_arg('num_samples',      int,    100,    "# of samples to infer.")
 add_arg('trainer_count',    int,    8,      "# of Trainers (CPUs or GPUs).")
 add_arg('beam_size',        int,    500,    "Beam search width.")
@@ -66,9 +57,8 @@ add_arg('specgram_type',    str,
         'linear',
         "Audio feature type. Options: linear, mfcc.",
         choices=['linear', 'mfcc'])
-args = parser.parse_args()
 # yapf: disable
-
+args = parser.parse_args()
 
 
 def tune():
@@ -130,13 +120,6 @@ def tune():
               (alpha, beta, wer_sum / num_ins))
 
 
-def print_arguments(args):
-    print("-----------  Configuration Arguments -----------")
-    for arg, value in sorted(vars(args).iteritems()):
-        print("%s: %s" % (arg, value))
-    print("------------------------------------------------")
-
-
 def main():
     print_arguments(args)
     paddle.init(use_gpu=args.use_gpu, trainer_count=args.trainer_count)

deep_speech_2/utils.py

+"""Contains common utility functions."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import distutils.util
+
+
+def print_arguments(args):
+    """Print argparse's arguments.
+
+    Usage:
+
+    .. code-block:: python
+
+        parser = argparse.ArgumentParser()
+        parser.add_argument("name", default="Jonh", type=str, help="User name.")
+        args = parser.parse_args()
+        print_arguments(args)
+
+    :param args: Input argparse.Namespace for printing.
+    :type args: argparse.Namespace
+    """
+    print("-----------  Configuration Arguments -----------")
+    for arg, value in sorted(vars(args).iteritems()):
+        print("%s: %s" % (arg, value))
+    print("------------------------------------------------")
+
+
+def add_arguments(argname, type, default, help, argparser, **kwargs):
+    """Add argparse's argument.
+
+    Usage:
+
+    .. code-block:: python
+
+        parser = argparse.ArgumentParser()
+        add_argument("name", str, "Jonh", "User name.", parser)
+        args = parser.parse_args()
+    """
+    type = distutils.util.strtobool if type == bool else type
+    argparser.add_argument(
+        "--" + argname,
+        default=default,
+        type=type,
+        help=help + ' Default: %(default)s.',
+        **kwargs)