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PaddleSpeech/paddlespeech/s2t/exps/u2/bin/test_hub.py

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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
"""Evaluation for U2 model."""
import cProfile
import os
import sys
import paddle
import soundfile
from paddlespeech.s2t.exps.u2.config import get_cfg_defaults
from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
from paddlespeech.s2t.io.collator import SpeechCollator
from paddlespeech.s2t.models.u2 import U2Model
from paddlespeech.s2t.training.cli import default_argument_parser
from paddlespeech.s2t.training.trainer import Trainer
from paddlespeech.s2t.utils import layer_tools
from paddlespeech.s2t.utils import mp_tools
from paddlespeech.s2t.utils.log import Log
from paddlespeech.s2t.utils.utility import print_arguments
from paddlespeech.s2t.utils.utility import UpdateConfig
logger = Log(__name__).getlog()
# TODO(hui zhang): dynamic load
class U2Tester_Hub(Trainer):
def __init__(self, config, args):
# super().__init__(config, args)
self.args = args
self.config = config
self.audio_file = args.audio_file
self.collate_fn_test = SpeechCollator.from_config(config)
self._text_featurizer = TextFeaturizer(
unit_type=config.collator.unit_type,
vocab_filepath=None,
spm_model_prefix=config.collator.spm_model_prefix)
def setup_model(self):
config = self.config
model_conf = config.model
with UpdateConfig(model_conf):
model_conf.input_dim = self.collate_fn_test.feature_size
model_conf.output_dim = self.collate_fn_test.vocab_size
model = U2Model.from_config(model_conf)
if self.parallel:
model = paddle.DataParallel(model)
logger.info(f"{model}")
layer_tools.print_params(model, logger.info)
self.model = model
logger.info("Setup model")
@mp_tools.rank_zero_only
@paddle.no_grad()
def test(self):
self.model.eval()
cfg = self.config.decoding
audio_file = self.audio_file
collate_fn_test = self.collate_fn_test
audio, _ = collate_fn_test.process_utterance(
audio_file=audio_file, transcript="Hello")
audio_len = audio.shape[0]
audio = paddle.to_tensor(audio, dtype='float32')
audio_len = paddle.to_tensor(audio_len)
audio = paddle.unsqueeze(audio, axis=0)
vocab_list = collate_fn_test.vocab_list
text_feature = self.collate_fn_test.text_feature
result_transcripts = self.model.decode(
audio,
audio_len,
text_feature=text_feature,
decoding_method=cfg.decoding_method,
lang_model_path=cfg.lang_model_path,
beam_alpha=cfg.alpha,
beam_beta=cfg.beta,
beam_size=cfg.beam_size,
cutoff_prob=cfg.cutoff_prob,
cutoff_top_n=cfg.cutoff_top_n,
num_processes=cfg.num_proc_bsearch,
ctc_weight=cfg.ctc_weight,
decoding_chunk_size=cfg.decoding_chunk_size,
num_decoding_left_chunks=cfg.num_decoding_left_chunks,
simulate_streaming=cfg.simulate_streaming)
logger.info("The result_transcripts: " + result_transcripts[0][0])
def run_test(self):
self.resume()
try:
self.test()
except KeyboardInterrupt:
sys.exit(-1)
def setup(self):
"""Setup the experiment.
"""
paddle.set_device('gpu' if self.args.nprocs > 0 else 'cpu')
#self.setup_output_dir()
#self.setup_checkpointer()
#self.setup_dataloader()
self.setup_model()
self.iteration = 0
self.epoch = 0
def resume(self):
"""Resume from the checkpoint at checkpoints in the output
directory or load a specified checkpoint.
"""
params_path = self.args.checkpoint_path + ".pdparams"
model_dict = paddle.load(params_path)
self.model.set_state_dict(model_dict)
def check(audio_file):
logger.info("checking the audio file format......")
try:
sig, sample_rate = soundfile.read(audio_file)
except Exception as e:
logger.error(str(e))
logger.error(
"can not open the wav file, please check the audio file format")
sys.exit(-1)
logger.info("The sample rate is %d" % sample_rate)
assert (sample_rate == 16000)
logger.info("The audio file format is right")
def main_sp(config, args):
exp = U2Tester_Hub(config, args)
with exp.eval():
exp.setup()
exp.run_test()
def main(config, args):
main_sp(config, args)
if __name__ == "__main__":
parser = default_argument_parser()
# save asr result to
parser.add_argument(
"--result_file", type=str, help="path of save the asr result")
parser.add_argument(
"--audio_file", type=str, help="path of the input audio file")
args = parser.parse_args()
print_arguments(args, globals())
if not os.path.isfile(args.audio_file):
print("Please input the right audio file path")
sys.exit(-1)
check(args.audio_file)
# https://yaml.org/type/float.html
config = get_cfg_defaults()
if args.config:
config.merge_from_file(args.config)
if args.opts:
config.merge_from_list(args.opts)
config.freeze()
print(config)
if args.dump_config:
with open(args.dump_config, 'w') as f:
print(config, file=f)
# Setting for profiling
pr = cProfile.Profile()
pr.runcall(main, config, args)
pr.dump_stats('test.profile')