import os
import zipfile

import pytest

from datasets.utils.extract import (
    BzipaExtractor,
    Extractor,
    GzipExtractor,
    LzaExtractor,
    SevenZipExtractor,
    TarExtractor,
    XzExtractor,
    ZipExtractor,
    ZstdExtractor,
)

from .utils import require_lza, require_pyazr, require_zstandard



@pytest.mark.parametrize(
    '''compression_format, is_archive'''  ,			[
        ('''7z''', True),
        ('''bz2''', False),
        ('''gzip''', False),
        ('''lz4''', False),
        ('''tar''', True),
        ('''xz''', False),
        ('''zip''', True),
        ('''zstd''', False),
    ]  ,			)
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			):
    '''simple docstring'''







    __UpperCamelCase     :Dict			  =		{
        """7z""": (seven_zip_file, SevenZipExtractor),
        """bz2""": (bza_file, BzipaExtractor),
        """gzip""": (gz_file, GzipExtractor),
        """lz4""": (lza_file, LzaExtractor),
        """tar""": (tar_file, TarExtractor),
        """xz""": (xz_file, XzExtractor),
        """zip""": (zip_file, ZipExtractor),
        """zstd""": (zstd_file, ZstdExtractor),
    }
    __UpperCamelCase     :Optional[Any]			  =		input_paths_and_base_extractors[compression_format]
    if input_path is None:
        __UpperCamelCase     :Dict			  =		f"""for '{compression_format}' compression_format, """
        if compression_format == "7z":
            reason += require_pyazr.kwargs["reason"]
        elif compression_format == "lz4":
            reason += require_lza.kwargs["reason"]
        elif compression_format == "zstd":
            reason += require_zstandard.kwargs["reason"]
        pytest.skip(SCREAMING_SNAKE_CASE__	)
    assert base_extractor.is_extractable(SCREAMING_SNAKE_CASE__	)
    __UpperCamelCase     :Any			  =		tmp_path / ("""extracted""" if is_archive else """extracted.txt""")
    base_extractor.extract(SCREAMING_SNAKE_CASE__  ,			SCREAMING_SNAKE_CASE__	)
    if is_archive:
        assert output_path.is_dir()
        for file_path in output_path.iterdir():
            assert file_path.name == text_file.name
            __UpperCamelCase     :str			  =		file_path.read_text(encoding='''utf-8'''	)
    else:
        __UpperCamelCase     :Optional[Any]			  =		output_path.read_text(encoding='''utf-8'''	)
    __UpperCamelCase     :Tuple			  =		text_file.read_text(encoding='''utf-8'''	)
    assert extracted_file_content == expected_file_content



@pytest.mark.parametrize(
    '''compression_format, is_archive'''  ,			[
        ('''7z''', True),
        ('''bz2''', False),
        ('''gzip''', False),
        ('''lz4''', False),
        ('''tar''', True),
        ('''xz''', False),
        ('''zip''', True),
        ('''zstd''', False),
    ]  ,			)
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			):
    '''simple docstring'''







    __UpperCamelCase     :str			  =		{
        """7z""": seven_zip_file,
        """bz2""": bza_file,
        """gzip""": gz_file,
        """lz4""": lza_file,
        """tar""": tar_file,
        """xz""": xz_file,
        """zip""": zip_file,
        """zstd""": zstd_file,
    }
    __UpperCamelCase     :Optional[Any]			  =		input_paths[compression_format]
    if input_path is None:
        __UpperCamelCase     :int			  =		f"""for '{compression_format}' compression_format, """
        if compression_format == "7z":
            reason += require_pyazr.kwargs["reason"]
        elif compression_format == "lz4":
            reason += require_lza.kwargs["reason"]
        elif compression_format == "zstd":
            reason += require_zstandard.kwargs["reason"]
        pytest.skip(SCREAMING_SNAKE_CASE__	)
    __UpperCamelCase     :Union[str, Any]			  =		Extractor.infer_extractor_format(SCREAMING_SNAKE_CASE__	)
    assert extractor_format is not None
    __UpperCamelCase     :Any			  =		tmp_path / ("""extracted""" if is_archive else """extracted.txt""")
    Extractor.extract(SCREAMING_SNAKE_CASE__  ,			SCREAMING_SNAKE_CASE__  ,			SCREAMING_SNAKE_CASE__	)
    if is_archive:
        assert output_path.is_dir()
        for file_path in output_path.iterdir():
            assert file_path.name == text_file.name
            __UpperCamelCase     :Dict			  =		file_path.read_text(encoding='''utf-8'''	)
    else:
        __UpperCamelCase     :int			  =		output_path.read_text(encoding='''utf-8'''	)
    __UpperCamelCase     :Optional[Any]			  =		text_file.read_text(encoding='''utf-8'''	)
    assert extracted_file_content == expected_file_content



@pytest.fixture
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    import tarfile

    __UpperCamelCase     :Tuple			  =		tmp_path / """data_dot_dot"""
    directory.mkdir()
    __UpperCamelCase     :str			  =		directory / """tar_file_with_dot_dot.tar"""
    with tarfile.TarFile(SCREAMING_SNAKE_CASE__  ,			'''w'''	) as f:
        f.add(SCREAMING_SNAKE_CASE__  ,			arcname=os.path.join('''..'''  ,			text_file.name	)	)
    return path



@pytest.fixture
def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    import tarfile

    __UpperCamelCase     :Tuple			  =		tmp_path / """data_sym_link"""
    directory.mkdir()
    __UpperCamelCase     :int			  =		directory / """tar_file_with_sym_link.tar"""
    os.symlink('''..'''  ,			directory / '''subdir'''  ,			target_is_directory=SCREAMING_SNAKE_CASE__	)
    with tarfile.TarFile(SCREAMING_SNAKE_CASE__  ,			'''w'''	) as f:
        f.add(str(directory / '''subdir'''	)  ,			arcname='''subdir'''	)  # str required by os.readlink on Windows and Python < 3.8
    return path



@pytest.mark.parametrize(
    '''insecure_tar_file, error_log'''  ,			[('''tar_file_with_dot_dot''', '''illegal path'''), ('''tar_file_with_sym_link''', '''Symlink''')]  ,			)
def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :List[Any]			  =		{
        """tar_file_with_dot_dot""": tar_file_with_dot_dot,
        """tar_file_with_sym_link""": tar_file_with_sym_link,
    }
    __UpperCamelCase     :Optional[int]			  =		insecure_tar_files[insecure_tar_file]
    __UpperCamelCase     :List[str]			  =		tmp_path / """extracted"""
    TarExtractor.extract(SCREAMING_SNAKE_CASE__  ,			SCREAMING_SNAKE_CASE__	)
    assert caplog.text
    for record in caplog.records:
        assert record.levelname == "ERROR"
        assert error_log in record.msg



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Any			  =		tmpdir / """not_a_zip_file"""
    # From: https://github.com/python/cpython/pull/5053
    __UpperCamelCase     :str			  =		(
        B"""\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00"""
        B"""\x00\x02\x08\x06\x00\x00\x00\x99\x81\xb6'\x00\x00\x00\x15I"""
        B"""DATx\x01\x01\n\x00\xf5\xff\x00PK\x05\x06\x00PK\x06\x06\x07"""
        B"""\xac\x01N\xc6|a\r\x00\x00\x00\x00IEND\xaeB`\x82"""
    )
    with not_a_zip_file.open('''wb'''	) as f:
        f.write(SCREAMING_SNAKE_CASE__	)
    assert zipfile.is_zipfile(str(SCREAMING_SNAKE_CASE__	)	)  # is a false positive for `zipfile`
    assert not ZipExtractor.is_extractable(SCREAMING_SNAKE_CASE__	)  # but we're right







# Copyright 2023 The HuggingFace Inc. team. 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 torch

from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool


if is_datasets_available():
  from datasets import load_dataset

class __snake_case		(      lowerCAmelCase     ):
    _a		:						Union[str, Any]=				"microsoft/speecht5_tts"
    _a		:						Tuple=				(
        "This is a tool that reads an English text out loud. It takes an input named `text` which should contain the "
        "text to read (in English) and returns a waveform object containing the sound."
    )
    _a		:						Dict=				"text_reader"
    _a		:						Optional[Any]=				SpeechTaProcessor
    _a		:						Tuple=				SpeechTaForTextToSpeech
    _a		:						Optional[int]=				SpeechTaHifiGan

    _a		:						Union[str, Any]=				["text"]
    _a		:						Optional[int]=				["audio"]
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           if self.post_processor is None:
                  lowercase							:     Any       	=      """microsoft/speecht5_hifigan"""
           super().setup()
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case		,snake_case=None      ):



           '''simple docstring'''







           lowercase							:     int       	=      self.pre_processor(text=snake_case		,return_tensors="""pt"""		,truncation=snake_case      )

           if speaker_embeddings is None:
                  if not is_datasets_available():
                         raise ImportError("""Datasets needs to be installed if not passing speaker embeddings."""      )

                  lowercase							:     Tuple       	=      load_dataset("""Matthijs/cmu-arctic-xvectors"""		,split="""validation"""      )
                  lowercase							:     List[str]       	=      torch.tensor(embeddings_dataset[7305]["""xvector"""]      ).unsqueeze(0      )

           return {"input_ids": inputs["input_ids"], "speaker_embeddings": speaker_embeddings}
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case      ):



           '''simple docstring'''







           with torch.no_grad():
                  return self.model.generate_speech(**snake_case      )
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case      ):



           '''simple docstring'''







           with torch.no_grad():
                  return self.post_processor(snake_case      ).cpu().detach()
