delete unused file ami_dataset.py, test=doc

examples/ami/sd0/local/ami_dataset.py

-# Copyright (c) 2022 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.
-import collections
-import json
-
-from paddle.io import Dataset
-
-from paddleaudio.backends import load as load_audio
-from paddleaudio.datasets.dataset import feat_funcs
-
-
-class AMIDataset(Dataset):
-    """
-    AMI dataset.
-    """
-
-    meta_info = collections.namedtuple(
-        'META_INFO', ('id', 'duration', 'wav', 'start', 'stop', 'record_id'))
-
-    def __init__(self, json_file: str, feat_type: str='raw', **kwargs):
-        """
-        Ags:
-            json_file (:obj:`str`): Data prep JSON file.
-            labels (:obj:`List[int]`): Labels of audio files.
-            feat_type (:obj:`str`, `optional`, defaults to `raw`):
-                It identifies the feature type that user wants to extrace of an audio file.
-        """
-        if feat_type not in feat_funcs.keys():
-            raise RuntimeError(
-                f"Unknown feat_type: {feat_type}, it must be one in {list(feat_funcs.keys())}"
-            )
-
-        self.json_file = json_file
-        self.feat_type = feat_type
-        self.feat_config = kwargs
-        self._data = self._get_data()
-        super(AMIDataset, self).__init__()
-
-    def _get_data(self):
-        with open(self.json_file, "r") as f:
-            meta_data = json.load(f)
-        data = []
-        for key in meta_data:
-            sub_seg = meta_data[key]["wav"]
-            wav = sub_seg["file"]
-            duration = sub_seg["duration"]
-            start = sub_seg["start"]
-            stop = sub_seg["stop"]
-            rec_id = str(key).rsplit("_", 2)[0]
-            data.append(
-                self.meta_info(
-                    str(key),
-                    float(duration), wav, int(start), int(stop), str(rec_id)))
-        return data
-
-    def _convert_to_record(self, idx: int):
-        sample = self._data[idx]
-
-        record = {}
-        # To show all fields in a namedtuple: `type(sample)._fields`
-        for field in type(sample)._fields:
-            record[field] = getattr(sample, field)
-
-        waveform, sr = load_audio(record['wav'])
-        waveform = waveform[record['start']:record['stop']]
-
-        feat_func = feat_funcs[self.feat_type]
-        feat = feat_func(
-            waveform, sr=sr, **self.feat_config) if feat_func else waveform
-
-        record.update({'feat': feat})
-
-        return record
-
-    def __getitem__(self, idx):
-        return self._convert_to_record(idx)
-
-    def __len__(self):
-        return len(self._data)