# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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 csv
import json
import os
import pandas as pd
import librosa
import datasets


_CITATION = """\
@article{zen2019libritts,
  title={Libritts: A corpus derived from librispeech for text-to-speech},
  author={Zen, Heiga and Dang, Viet and Clark, Rob and Zhang, Yu and Weiss, Ron J and Jia, Ye and Chen, Zhifeng and Wu, Yonghui},
  journal={arXiv preprint arXiv:1904.02882},
  year={2019}
}
"""

_DESCRIPTION = """\
LibriTTS is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, prepared by Heiga Zen with the"""

_HOMEPAGE = "https://openslr.org/60/"

_LICENSE = "CC BY 4.0"

# Source data: "https://zenodo.org/record/7068130/files/vivos.tar.gz"
_DATA_URLS =  {
    "test-clean": "libritts/test-clean.tar.gz",
    "test-other": "libritts/test-other.tar.gz",
}

_PROMPTS_URLS = {
    "test-clean": "libritts/metadata_clean.csv",
    "test-other": "libritts/metadata_other.csv",
   
}

class LibriTTSDataset(datasets.GeneratorBasedBuilder):
    """LibriTTS test subsets"""

    VERSION = datasets.Version("1.1.0")

    # This is an example of a dataset with multiple configurations.
    # If you don't want/need to define several sub-sets in your dataset,
    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.

    # If you need to make complex sub-parts in the datasets with configurable options
    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
    # BUILDER_CONFIG_CLASS = MyBuilderConfig

    def _info(self):
        return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "transcription":datasets.Value("string"),
                    "normalized_transcription":datasets.Value("string"),
                    "speaker_gender": datasets.Value("string"),
                    "speaker_id": datasets.Value("int32"),
                    "audio": datasets.Audio(sampling_rate=24_000), 
                    
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name

        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
        archive_clean = dl_manager.download(_DATA_URLS["test-clean"])
        archive_other = dl_manager.download(_DATA_URLS["test-other"])
        test_clean_dir = "libritts/test-clean"
        test_other_dir = "libritts/test-other"

        return [
            datasets.SplitGenerator(
                name="testclean",
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "prompts_path": prompts_paths["test-clean"],
                    "path_to_clips": test_clean_dir + "/test-clean",
                    "audio_files": dl_manager.iter_archive(archive_clean),
                },
            ),
            datasets.SplitGenerator(
                name="testother",
                # These kwargs will be passed to _generate_examples
                gen_kwargs={
                    "prompts_path": prompts_paths["test-other"],
                    "path_to_clips": test_other_dir + "/test-other",
                    "audio_files": dl_manager.iter_archive(archive_other),
                },
            ),
        ]

    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
        """Yields examples as (key, example) tuples."""
        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
        # The `key` is here for legacy reason (tfds) and is not important in itself.
        
        # with open('eggs.csv', newline='') as csvfile:
        # spamreader = csv.reader(csvfile, delimiter=' ', quotechar='|')
        # for row in spamreader:
        print(path_to_clips)
        examples = {}
        data = pd.read_csv(prompts_path)

        for file_name,transcription,normalized_transcription,speaker_id,speaker_gender in data.values:
                    
                    examples[file_name] = {
                        
                            "transcription": transcription,
                            "normalized_transcription": normalized_transcription,
                            "speaker_id": speaker_id,
                            "speaker_gender": speaker_gender,
                        }

      
        inside_clips_dir = False
        id_ = 0
      
        for path, f in audio_files:
            path = "libritts/"+path

      
            if path.startswith(path_to_clips):
                inside_clips_dir = True
                if path in examples:
                    audio = {"path": path, "bytes": f.read()}
                    yield id_, {**examples[path], "audio": audio}
                    id_ += 1
            elif inside_clips_dir:
                break