import importlib
import os
import platform
from pathlib import Path

from packaging import version

from .utils.logging import get_logger


lowerCAmelCase__      		=					get_logger(__name__)

# Datasets
lowerCAmelCase__      		=					'https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets'
lowerCAmelCase__      		=					'https://cdn-datasets.huggingface.co/datasets/datasets'
lowerCAmelCase__      		=					'https://raw.githubusercontent.com/huggingface/datasets/{revision}/datasets/{path}/{name}'

# Metrics
lowerCAmelCase__      		=					'https://s3.amazonaws.com/datasets.huggingface.co/datasets/metrics'
lowerCAmelCase__      		=					'https://cdn-datasets.huggingface.co/datasets/metric'
lowerCAmelCase__      		=					'https://raw.githubusercontent.com/huggingface/datasets/{revision}/metrics/{path}/{name}'

# Hub
lowerCAmelCase__      		=					os.environ.get('HF_ENDPOINT', 'https://huggingface.co')
lowerCAmelCase__      		=					HF_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
lowerCAmelCase__      		=					'main'

lowerCAmelCase__      		=					version.parse(platform.python_version())

if PY_VERSION < version.parse('3.8'):
    import importlib_metadata
else:
    import importlib.metadata as importlib_metadata

# General environment variables accepted values for booleans
lowerCAmelCase__      		=					{'1', 'ON', 'YES', 'TRUE'}
lowerCAmelCase__      		=					ENV_VARS_TRUE_VALUES.union({'AUTO'})


# Imports
lowerCAmelCase__      		=					version.parse(importlib_metadata.version('dill'))
lowerCAmelCase__      		=					version.parse(importlib_metadata.version('pandas'))
lowerCAmelCase__      		=					version.parse(importlib_metadata.version('pyarrow'))

lowerCAmelCase__      		=					os.environ.get('USE_TF', 'AUTO').upper()
lowerCAmelCase__      		=					os.environ.get('USE_TORCH', 'AUTO').upper()
lowerCAmelCase__      		=					os.environ.get('USE_JAX', 'AUTO').upper()

lowerCAmelCase__      		=					'N/A'
lowerCAmelCase__      		=					False

if USE_TORCH in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TF not in ENV_VARS_TRUE_VALUES:
    lowerCAmelCase__      		=					importlib.util.find_spec('torch') is not None
    if TORCH_AVAILABLE:
        try:
            lowerCAmelCase__      		=					version.parse(importlib_metadata.version('torch'))
            logger.info(F'PyTorch version {TORCH_VERSION} available.')
        except importlib_metadata.PackageNotFoundError:
            pass
else:
    logger.info('Disabling PyTorch because USE_TF is set')

lowerCAmelCase__      		=					'N/A'
lowerCAmelCase__      		=					False

if USE_TF in ENV_VARS_TRUE_AND_AUTO_VALUES and USE_TORCH not in ENV_VARS_TRUE_VALUES:
    lowerCAmelCase__      		=					importlib.util.find_spec('tensorflow') is not None
    if TF_AVAILABLE:
        # For the metadata, we have to look for both tensorflow and tensorflow-cpu
        for package in [
            "tensorflow",
            "tensorflow-cpu",
            "tensorflow-gpu",
            "tf-nightly",
            "tf-nightly-cpu",
            "tf-nightly-gpu",
            "intel-tensorflow",
            "tensorflow-rocm",
            "tensorflow-macos",
        ]:
            try:
                lowerCAmelCase__      		=					version.parse(importlib_metadata.version(package))
            except importlib_metadata.PackageNotFoundError:
                continue
            else:
                break
        else:
            lowerCAmelCase__      		=					False
    if TF_AVAILABLE:
        if TF_VERSION.major < 2:
            logger.info(F'TensorFlow found but with version {TF_VERSION}. `datasets` requires version 2 minimum.')
            lowerCAmelCase__      		=					False
        else:
            logger.info(F'TensorFlow version {TF_VERSION} available.')
else:
    logger.info('Disabling Tensorflow because USE_TORCH is set')


lowerCAmelCase__      		=					'N/A'
lowerCAmelCase__      		=					False

if USE_JAX in ENV_VARS_TRUE_AND_AUTO_VALUES:
    lowerCAmelCase__      		=					importlib.util.find_spec('jax') is not None and importlib.util.find_spec('jaxlib') is not None
    if JAX_AVAILABLE:
        try:
            lowerCAmelCase__      		=					version.parse(importlib_metadata.version('jax'))
            logger.info(F'JAX version {JAX_VERSION} available.')
        except importlib_metadata.PackageNotFoundError:
            pass
else:
    logger.info('Disabling JAX because USE_JAX is set to False')


lowerCAmelCase__      		=					os.environ.get('USE_BEAM', 'AUTO').upper()
lowerCAmelCase__      		=					'N/A'
lowerCAmelCase__      		=					False
if USE_BEAM in ENV_VARS_TRUE_AND_AUTO_VALUES:
    try:
        lowerCAmelCase__      		=					version.parse(importlib_metadata.version('apache_beam'))
        lowerCAmelCase__      		=					True
        logger.info(F'Apache Beam version {BEAM_VERSION} available.')
    except importlib_metadata.PackageNotFoundError:
        pass
else:
    logger.info('Disabling Apache Beam because USE_BEAM is set to False')


# Optional tools for data loading
lowerCAmelCase__      		=					importlib.util.find_spec('sqlalchemy') is not None

# Optional tools for feature decoding
lowerCAmelCase__      		=					importlib.util.find_spec('PIL') is not None
lowerCAmelCase__      		=					importlib.util.find_spec('soundfile') is not None and version.parse(
    importlib.import_module('soundfile').__libsndfile_version__
) >= version.parse('1.0.31')
lowerCAmelCase__      		=					importlib.util.find_spec('soundfile') is not None and version.parse(
    importlib.import_module('soundfile').__libsndfile_version__
) >= version.parse('1.1.0')

# Optional compression tools
lowerCAmelCase__      		=					importlib.util.find_spec('rarfile') is not None
lowerCAmelCase__      		=					importlib.util.find_spec('zstandard') is not None
lowerCAmelCase__      		=					importlib.util.find_spec('lz4') is not None
lowerCAmelCase__      		=					importlib.util.find_spec('py7zr') is not None


# Cache location
lowerCAmelCase__      		=					'~/.cache'
lowerCAmelCase__      		=					os.getenv('XDG_CACHE_HOME', DEFAULT_XDG_CACHE_HOME)
lowerCAmelCase__      		=					os.path.join(XDG_CACHE_HOME, 'huggingface')
lowerCAmelCase__      		=					os.path.expanduser(os.getenv('HF_HOME', DEFAULT_HF_CACHE_HOME))

lowerCAmelCase__      		=					os.path.join(HF_CACHE_HOME, 'datasets')
lowerCAmelCase__      		=					Path(os.getenv('HF_DATASETS_CACHE', DEFAULT_HF_DATASETS_CACHE))

lowerCAmelCase__      		=					os.path.join(HF_CACHE_HOME, 'metrics')
lowerCAmelCase__      		=					Path(os.getenv('HF_METRICS_CACHE', DEFAULT_HF_METRICS_CACHE))

lowerCAmelCase__      		=					os.path.join(HF_CACHE_HOME, 'modules')
lowerCAmelCase__      		=					Path(os.getenv('HF_MODULES_CACHE', DEFAULT_HF_MODULES_CACHE))

lowerCAmelCase__      		=					'downloads'
lowerCAmelCase__      		=					os.path.join(HF_DATASETS_CACHE, DOWNLOADED_DATASETS_DIR)
lowerCAmelCase__      		=					Path(os.getenv('HF_DATASETS_DOWNLOADED_DATASETS_PATH', DEFAULT_DOWNLOADED_DATASETS_PATH))

lowerCAmelCase__      		=					'extracted'
lowerCAmelCase__      		=					os.path.join(DEFAULT_DOWNLOADED_DATASETS_PATH, EXTRACTED_DATASETS_DIR)
lowerCAmelCase__      		=					Path(os.getenv('HF_DATASETS_EXTRACTED_DATASETS_PATH', DEFAULT_EXTRACTED_DATASETS_PATH))

# Download count for the website
lowerCAmelCase__      		=					(
    os.environ.get('HF_UPDATE_DOWNLOAD_COUNTS', 'AUTO').upper() in ENV_VARS_TRUE_AND_AUTO_VALUES
)

# Batch size constants. For more info, see:
# https://github.com/apache/arrow/blob/master/docs/source/cpp/arrays.rst#size-limitations-and-recommendations)
lowerCAmelCase__      		=					1000

# Size of the preloaded record batch in `Dataset.__iter__`
lowerCAmelCase__      		=					10

# Pickling tables works only for small tables (<4GiB)
# For big tables, we write them on disk instead
lowerCAmelCase__      		=					4 << 30

# Max shard size in bytes (e.g. to shard parquet datasets in push_to_hub or download_and_prepare)
lowerCAmelCase__      		=					'500MB'

# Parquet configuration
lowerCAmelCase__      		=					100
lowerCAmelCase__      		=					100
lowerCAmelCase__      		=					100

# Offline mode
lowerCAmelCase__      		=					os.environ.get('HF_DATASETS_OFFLINE', 'AUTO').upper() in ENV_VARS_TRUE_VALUES

# In-memory
lowerCAmelCase__      		=					0  # Disabled
lowerCAmelCase__      		=					float(os.environ.get('HF_DATASETS_IN_MEMORY_MAX_SIZE', DEFAULT_IN_MEMORY_MAX_SIZE))

# File names
lowerCAmelCase__      		=					'dataset.arrow'
lowerCAmelCase__      		=					'indices.arrow'
lowerCAmelCase__      		=					'state.json'
lowerCAmelCase__      		=					'dataset_info.json'
lowerCAmelCase__      		=					'dataset_infos.json'
lowerCAmelCase__      		=					'LICENSE'
lowerCAmelCase__      		=					'metric_info.json'
lowerCAmelCase__      		=					'dataset_dict.json'

lowerCAmelCase__      		=					'datasets_modules'

lowerCAmelCase__      		=					255

# Streaming
lowerCAmelCase__      		=					20
lowerCAmelCase__      		=					5

# Datasets without script
lowerCAmelCase__      		=					200
lowerCAmelCase__      		=					10
lowerCAmelCase__      		=					200

# Progress bars
lowerCAmelCase__      		=					0.05  # 20 progress updates per sec

import unittest

from cer import CER


lowerCAmelCase__      		=					CER()
class 							a_					(		unittest.TestCase		):






 '''simple docstring'''






 def 						__snake_case		(     self   :    Any):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['White House']
        lowerCAmelCase__	      =   ['white house']
        # S = 2, D = 0, I = 0, N = 11, CER = 2 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.1_818_181_818) < 1e-6)




 def 						__snake_case		(     self   :    List[Any]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['were wolf']
        lowerCAmelCase__	      =   ['werewolf']
        # S = 0, D = 0, I = 1, N = 9, CER = 1 / 9
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.1_111_111) < 1e-6)

        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['weae     wolf']
        # S = 1, D = 1, I = 0, N = 8, CER = 0.25
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.25) < 1e-6)

        # consecutive whitespaces case 1
        lowerCAmelCase__	      =   ['were wolf']
        lowerCAmelCase__	      =   ['were               wolf']
        # S = 0, D = 0, I = 0, N = 9, CER = 0
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.0) < 1e-6)

        # consecutive whitespaces case 2
        lowerCAmelCase__	      =   ['were   wolf']
        lowerCAmelCase__	      =   ['were               wolf']
        # S = 0, D = 0, I = 0, N = 9, CER = 0
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.0) < 1e-6)




 def 						__snake_case		(     self   :    Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['weaewolf']
        # S = 1, D = 0, I = 0, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['wereawolf']
        # S = 0, D = 1, I = 0, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['wereolf']
        # S = 0, D = 0, I = 1, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    str):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertEqual(lowercase__     ,       0.0)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf', 'I am your father']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertEqual(lowercase__     ,       0.0)

        lowerCAmelCase__	      =   ['werewolf', 'I am your father', 'doge']
        lowerCAmelCase__	      =   ['werxwolf', 'I       am your father', 'doge']
        # S = 1, D = 0, I = 0, N = 28, CER = 1 / 28
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.03_571_428) < 1e-6)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['My hovercraft', 'is full of eels']
        lowerCAmelCase__	      =   ['My hovercraft is full', ' of eels']
        # S = 0, D = 0, I = 2, N = 28, CER = 2 / 28
        # whitespace at the front of " of eels" will be strip during preporcessing
        # so need to insert 2 whitespaces
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__     ,       concatenate_texts=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.071_428) < 1e-6)




 def 						__snake_case		(     self   :    Dict):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['我能吞下玻璃而不伤身体']
        lowerCAmelCase__	      =   [' 能吞虾玻璃而 不霜身体啦']
        # S = 3, D = 2, I = 0, N = 11, CER = 5 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.4_545_454_545) < 1e-6)

        lowerCAmelCase__	      =   ['我能吞下玻璃', '而不伤身体']
        lowerCAmelCase__	      =   ['我    能 吞 下 玻 璃', '而不伤身体']
        # S = 0, D = 5, I = 0, N = 11, CER = 5 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.454_545_454_545) < 1e-6)

        lowerCAmelCase__	      =   ['我能吞下玻璃而不伤身体']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertFalse(lowercase__     ,       0.0)




 def 						__snake_case		(     self   :    Dict):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['']
        lowerCAmelCase__	      =   ['Hypothesis']
        with self.assertRaises(lowercase__):
               cer.compute(predictions=lowercase__     ,       references=lowercase__)


if __name__ == "__main__":
    unittest.main()
