add bin for hub

deepspeech/exps/deepspeech2/bin/test_hub.py

+# 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 DeepSpeech2 model."""
+import os
+import sys
+from pathlib import Path
+
+import paddle
+
+from deepspeech.exps.deepspeech2.config import get_cfg_defaults
+from deepspeech.frontend.featurizer.text_featurizer import TextFeaturizer
+from deepspeech.io.collator import SpeechCollator
+from deepspeech.models.ds2 import DeepSpeech2Model
+from deepspeech.models.ds2_online import DeepSpeech2ModelOnline
+from deepspeech.training.cli import default_argument_parser
+from deepspeech.utils import mp_tools
+from deepspeech.utils.checkpoint import Checkpoint
+from deepspeech.utils.log import Log
+from deepspeech.utils.utility import print_arguments
+from deepspeech.utils.utility import UpdateConfig
+
+logger = Log(__name__).getlog()
+
+
+class DeepSpeech2Tester_hub():
+    def __init__(self, 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)
+
+    def compute_result_transcripts(self, audio, audio_len, vocab_list, cfg):
+        result_transcripts = self.model.decode(
+            audio,
+            audio_len,
+            vocab_list,
+            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)
+        #replace the '<space>' with ' '
+        result_transcripts = [
+            self._text_featurizer.detokenize(sentence)
+            for sentence in result_transcripts
+        ]
+
+        return result_transcripts
+
+    @mp_tools.rank_zero_only
+    @paddle.no_grad()
+    def test(self):
+        self.model.eval()
+        cfg = self.config
+        audio_file = self.audio_file
+        collate_fn_test = self.collate_fn_test
+        audio, _ = collate_fn_test.process_utterance(
+            audio_file=audio_file, transcript=" ")
+        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
+        result_transcripts = self.compute_result_transcripts(
+            audio, audio_len, vocab_list, cfg.decoding)
+        logger.info("result_transcripts: " + result_transcripts[0])
+
+    def run_test(self):
+        self.resume()
+        try:
+            self.test()
+        except KeyboardInterrupt:
+            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_model()
+
+    def setup_output_dir(self):
+        """Create a directory used for output.
+        """
+        # output dir
+        if self.args.output:
+            output_dir = Path(self.args.output).expanduser()
+            output_dir.mkdir(parents=True, exist_ok=True)
+        else:
+            output_dir = Path(
+                self.args.checkpoint_path).expanduser().parent.parent
+            output_dir.mkdir(parents=True, exist_ok=True)
+        self.output_dir = output_dir
+
+    def setup_model(self):
+        config = self.config.clone()
+        with UpdateConfig(config):
+            config.model.feat_size = self.collate_fn_test.feature_size
+            config.model.dict_size = self.collate_fn_test.vocab_size
+
+        if self.args.model_type == 'offline':
+            model = DeepSpeech2Model.from_config(config.model)
+        elif self.args.model_type == 'online':
+            model = DeepSpeech2ModelOnline.from_config(config.model)
+        else:
+            raise Exception("wrong model type")
+
+        self.model = model
+
+    def setup_checkpointer(self):
+        """Create a directory used to save checkpoints into.
+
+        It is "checkpoints" inside the output directory.
+        """
+        # checkpoint dir
+        checkpoint_dir = self.output_dir / "checkpoints"
+        checkpoint_dir.mkdir(exist_ok=True)
+
+        self.checkpoint_dir = checkpoint_dir
+
+        self.checkpoint = Checkpoint(
+            kbest_n=self.config.training.checkpoint.kbest_n,
+            latest_n=self.config.training.checkpoint.latest_n)
+
+    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 main_sp(config, args):
+    exp = DeepSpeech2Tester_hub(config, args)
+    exp.setup()
+    exp.run_test()
+
+
+def main(config, args):
+    main_sp(config, args)
+
+
+if __name__ == "__main__":
+    parser = default_argument_parser()
+    parser.add_argument("--model_type")
+    parser.add_argument("--audio_file")
+    # save asr result to
+    parser.add_argument(
+        "--result_file", type=str, help="path of save the asr result")
+    args = parser.parse_args()
+    print_arguments(args, globals())
+    if args.model_type is None:
+        args.model_type = 'offline'
+    if not os.path.isfile(args.audio_file):
+        print("Please input the audio file path")
+        sys.exit(-1)
+    print("model_type:{}".format(args.model_type))
+
+    # https://yaml.org/type/float.html
+    config = get_cfg_defaults(args.model_type)
+    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)
+
+    main(config, args)

examples/aishell/s0/local/test_hub.sh

+#!/bin/bash
+
+if [ $# != 4 ];then
+    echo "usage: ${0} config_path ckpt_path_prefix model_type audio_file"
+    exit -1
+fi
+
+ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
+echo "using $ngpu gpus..."
+
+config_path=$1
+ckpt_prefix=$2
+model_type=$3
+audio_file=$4
+
+# download language model
+bash local/download_lm_ch.sh
+if [ $? -ne 0 ]; then
+   exit 1
+fi
+
+python3 -u ${BIN_DIR}/test_hub.py \
+--nproc ${ngpu} \
+--config ${config_path} \
+--result_file ${ckpt_prefix}.rsl \
+--checkpoint_path ${ckpt_prefix} \
+--model_type ${model_type} \
+--audio_file ${audio_file}
+
+if [ $? -ne 0 ]; then
+    echo "Failed in evaluation!"
+    exit 1
+fi
+
+
+exit 0

examples/aishell/s0/run.sh

@@ -15,6 +15,8 @@ avg_ckpt=avg_${avg_num}
 ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}')
 echo "checkpoint name ${ckpt}"
 
+audio_file="data/tmp.wav"
+
 if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
     # prepare data
     bash ./local/data.sh || exit -1
@@ -44,3 +46,9 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
     # test export ckpt avg_n
     CUDA_VISIBLE_DEVICES=0 ./local/test_export.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt}.jit ${model_type}|| exit -1
 fi
+
+# Optionally, you can add LM and test it with runtime.
+if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
+    # test a single .wav file
+    CUDA_VISIBLE_DEVICES=0 ./local/test_hub.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} ${model_type} ${audio_file} || exit -1
+fi