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# Copyright 2020 Huy Le Nguyen (@usimarit) | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
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import argparse | ||
import os | ||
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from tensorflow_asr.utils import env_util | ||
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logger = env_util.setup_environment() | ||
import tensorflow as tf | ||
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DEFAULT_YAML = os.path.join(os.path.abspath(os.path.dirname(__file__)), "config.yml") | ||
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tf.keras.backend.clear_session() | ||
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parser = argparse.ArgumentParser(prog="Conformer Testing") | ||
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parser.add_argument( | ||
"--config", | ||
type=str, | ||
default=DEFAULT_YAML, | ||
help="The file path of model configuration file", | ||
) | ||
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parser.add_argument( | ||
"--h5", | ||
type=str, | ||
default=None, | ||
help="Path to saved h5 weights", | ||
) | ||
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||
parser.add_argument( | ||
"--sentence_piece", | ||
default=False, | ||
action="store_true", | ||
help="Whether to use `SentencePiece` model", | ||
) | ||
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parser.add_argument( | ||
"--subwords", | ||
default=False, | ||
action="store_true", | ||
help="Use subwords", | ||
) | ||
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parser.add_argument( | ||
"--output_dir", | ||
type=str, | ||
default=None, | ||
help="Output directory for saved model", | ||
) | ||
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args = parser.parse_args() | ||
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assert args.h5 | ||
assert args.output_dir | ||
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from tensorflow_asr.configs.config import Config | ||
from tensorflow_asr.featurizers.speech_featurizers import TFSpeechFeaturizer | ||
from tensorflow_asr.featurizers.text_featurizers import CharFeaturizer, SentencePieceFeaturizer, SubwordFeaturizer | ||
from tensorflow_asr.models.transducer.conformer import Conformer | ||
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config = Config(args.config) | ||
speech_featurizer = TFSpeechFeaturizer(config.speech_config) | ||
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if args.sentence_piece: | ||
logger.info("Use SentencePiece ...") | ||
text_featurizer = SentencePieceFeaturizer(config.decoder_config) | ||
elif args.subwords: | ||
logger.info("Use subwords ...") | ||
text_featurizer = SubwordFeaturizer(config.decoder_config) | ||
else: | ||
logger.info("Use characters ...") | ||
text_featurizer = CharFeaturizer(config.decoder_config) | ||
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tf.random.set_seed(0) | ||
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# build model | ||
conformer = Conformer(**config.model_config, vocabulary_size=text_featurizer.num_classes) | ||
conformer.make(speech_featurizer.shape) | ||
conformer.load_weights(args.h5, by_name=True) | ||
conformer.summary(line_length=100) | ||
conformer.add_featurizers(speech_featurizer, text_featurizer) | ||
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class aModule(tf.Module): | ||
def __init__(self, model): | ||
super().__init__() | ||
self.model = model | ||
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@tf.function( | ||
input_signature=[ | ||
{ | ||
"inputs": tf.TensorSpec(shape=[None, None, 80, 1], dtype=tf.float32, name="inputs"), | ||
"inputs_length": tf.TensorSpec(shape=[None], dtype=tf.int32, name="inputs_length"), | ||
} | ||
] | ||
) | ||
def pred(self, input_batch): | ||
result = self.model.recognize(input_batch) | ||
return {"ASR": result} | ||
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module = aModule(conformer) | ||
tf.saved_model.save(module, args.output_dir, signatures={"serving_default": module.pred}) |
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[tool.black] | ||
line-length = 127 |
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cython | ||
numpy | ||
scipy | ||
sklearn | ||
pandas | ||
tensorflow-datasets>=4.2.0 | ||
tensorflow-addons>=0.11.1 | ||
setuptools>=47.1.1 | ||
librosa>=0.8.0 | ||
soundfile>=0.10.3 | ||
PyYAML>=5.3.1 | ||
matplotlib>=3.2.1 | ||
sox>=1.4.1 | ||
tqdm>=4.54.1 | ||
colorama>=0.4.4 | ||
nlpaug>=1.1.1 | ||
nltk>=3.5 | ||
sentencepiece>=0.1.94 | ||
absl-py==0.12.0 | ||
appdirs==1.4.4 | ||
astroid==2.6.6 | ||
attrs==21.2.0 | ||
audioread==2.1.9 | ||
black==21.7b0 | ||
certifi==2021.5.30 | ||
cffi==1.14.6 | ||
charset-normalizer==2.0.4 | ||
click==8.0.1 | ||
colorama==0.4.4 | ||
cycler==0.10.0 | ||
Cython==0.29.24 | ||
decorator==5.0.9 | ||
dill==0.3.4 | ||
flake8==3.9.2 | ||
future==0.18.2 | ||
googleapis-common-protos==1.53.0 | ||
idna==3.2 | ||
isort==5.9.3 | ||
joblib==1.0.1 | ||
kiwisolver==1.3.1 | ||
lazy-object-proxy==1.6.0 | ||
librosa==0.8.1 | ||
llvmlite==0.36.0 | ||
matplotlib==3.4.3 | ||
mccabe==0.6.1 | ||
mypy-extensions==0.4.3 | ||
nlpaug==1.1.7 | ||
nltk==3.6.2 | ||
numba==0.53.1 | ||
numpy==1.19.5 | ||
packaging==21.0 | ||
pandas==1.3.1 | ||
pathspec==0.9.0 | ||
Pillow==8.3.1 | ||
pooch==1.4.0 | ||
promise==2.3 | ||
protobuf==3.17.3 | ||
pycodestyle==2.7.0 | ||
pycparser==2.20 | ||
pyflakes==2.3.1 | ||
pyparsing==2.4.7 | ||
python-dateutil==2.8.2 | ||
pytz==2021.1 | ||
PyYAML==5.4.1 | ||
regex==2021.8.3 | ||
requests==2.26.0 | ||
resampy==0.2.2 | ||
scikit-learn==0.24.2 | ||
scipy==1.7.1 | ||
sentencepiece==0.1.96 | ||
six==1.15.0 | ||
sklearn==0.0 | ||
SoundFile==0.10.3.post1 | ||
sox==1.4.1 | ||
tensorflow-addons==0.13.0 | ||
tensorflow-datasets==4.4.0 | ||
tensorflow-metadata==1.2.0 | ||
termcolor==1.1.0 | ||
threadpoolctl==2.2.0 | ||
toml==0.10.2 | ||
tomli==1.2.1 | ||
tqdm==4.62.1 | ||
typeguard==2.12.1 | ||
urllib3==1.26.6 | ||
wrapt==1.12.1 |
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@@ -1,8 +1,8 @@ | ||
[flake8] | ||
ignore = E402,E701,E702,E704,E251,W503,W504,C901 | ||
ignore = E402,E701,E702,E704,E251,E203,W503,W504,C901 | ||
max-line-length = 127 | ||
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[pep8] | ||
ignore = E402,E701,E702,E704,E251,W503,W504,C901 | ||
ignore = E402,E701,E702,E704,E251,E203,W503,W504,C901 | ||
max-line-length = 127 | ||
indent-size = 4 |
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@@ -22,7 +22,7 @@ | |
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setuptools.setup( | ||
name="TensorFlowASR", | ||
version="1.0.2", | ||
version="1.0.3", | ||
author="Huy Le Nguyen", | ||
author_email="[email protected]", | ||
description="Almost State-of-the-art Automatic Speech Recognition using Tensorflow 2", | ||
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@@ -32,12 +32,14 @@ | |
packages=setuptools.find_packages(include=["tensorflow_asr*"]), | ||
install_requires=requirements, | ||
extras_require={ | ||
"tf2.3": ["tensorflow>=2.3.0,<2.4", "tensorflow-text>2.3.0,<2.4", "tensorflow-io>=0.16.0,<0.17"], | ||
"tf2.3-gpu": ["tensorflow-gpu>=2.3.0,<2.4", "tensorflow-text>=2.3.0,<2.4", "tensorflow-io>=0.16.0,<0.17"], | ||
"tf2.4": ["tensorflow>=2.4.0,<2.5", "tensorflow-text>=2.4.0,<2.5", "tensorflow-io>=0.17.0,<0.18"], | ||
"tf2.4-gpu": ["tensorflow-gpu>=2.4.0,<2.5", "tensorflow-text>=2.4.0,<2.5", "tensorflow-io>=0.17.0,<0.18"], | ||
"tf2.5": ["tensorflow>=2.5.0,<2.6", "tensorflow-text>=2.5.0,<2.6", "tensorflow-io>=0.18.0,<0.19"], | ||
"tf2.5-gpu": ["tensorflow-gpu>=2.5.0,<2.6", "tensorflow-text>=2.5.0,<2.6", "tensorflow-io>=0.18.0,<0.19"] | ||
"tf2.3": ["tensorflow~=2.3.0", "tensorflow-text~=2.3.0", "tensorflow-io~=0.16.0"], | ||
"tf2.3-gpu": ["tensorflow-gpu~=2.3.0", "tensorflow-text~=2.3.0", "tensorflow-io~=0.16.0"], | ||
"tf2.4": ["tensorflow~=2.4.0", "tensorflow-text~=2.4.0", "tensorflow-io~=0.17.0"], | ||
"tf2.4-gpu": ["tensorflow-gpu~=2.4.0", "tensorflow-text~=2.4.0", "tensorflow-io~=0.17.0"], | ||
"tf2.5": ["tensorflow~=2.5.0", "tensorflow-text~=2.5.0", "tensorflow-io~=0.18.0"], | ||
"tf2.5-gpu": ["tensorflow-gpu~=2.5.0", "tensorflow-text~=2.5.0", "tensorflow-io~=0.18.0"], | ||
"tf2.6": ["tensorflow~=2.6.0", "tensorflow-text~=2.6.0rc0", "tensorflow-io~=0.20.0"], | ||
"tf2.6-gpu": ["tensorflow-gpu~=2.6.0", "tensorflow-text~=2.6.0rc0", "tensorflow-io~=0.20.0"], | ||
}, | ||
classifiers=[ | ||
"Programming Language :: Python :: 3.6", | ||
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@@ -46,7 +48,7 @@ | |
"Intended Audience :: Science/Research", | ||
"Operating System :: POSIX :: Linux", | ||
"License :: OSI Approved :: Apache Software License", | ||
"Topic :: Software Development :: Libraries :: Python Modules" | ||
"Topic :: Software Development :: Libraries :: Python Modules", | ||
], | ||
python_requires='>=3.6', | ||
python_requires=">=3.6", | ||
) |
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