






"""simple docstring"""
# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


lowerCamelCase_							      = logging.get_logger(__name__)

lowerCamelCase_							      = {}
lowerCamelCase_							      = {}
lowerCamelCase_							      = {}

def 							snake_case (  A__      ,A__      ,A__ = None      ,):
			UpperCAmelCase_	:					str     	=   aliases if aliases is not None else []
			if format_type in _FORMAT_TYPES:
						logger.warning(
						    F"""Overwriting format type '{format_type}' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"""		)
			UpperCAmelCase_	:					Optional[int]     	=   formatter_cls
			for alias in set(aliases + [format_type]		):
						if alias in _FORMAT_TYPES_ALIASES:
									logger.warning(
									    F"""Overwriting format type alias '{alias}' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"""		)
						UpperCAmelCase_	:					str     	=   format_type

def 							snake_case (  A__      ,A__      ,A__ = None		):
			UpperCAmelCase_	:					Union[str, Any]     	=   aliases if aliases is not None else []
			for alias in set(aliases + [format_type]		):
						UpperCAmelCase_	:					Union[str, Any]     	=   unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=['''python'''])
_register_formatter(ArrowFormatter, '''arrow''', aliases=['''pa''', '''pyarrow'''])
_register_formatter(NumpyFormatter, '''numpy''', aliases=['''np'''])
_register_formatter(PandasFormatter, '''pandas''', aliases=['''pd'''])
_register_formatter(CustomFormatter, '''custom''')

if config.TORCH_AVAILABLE:
			from .torch_formatter import TorchFormatter

			_register_formatter(TorchFormatter, '''torch''', aliases=['''pt''', '''pytorch'''])
else:
			lowerCamelCase_							      = ValueError('''PyTorch needs to be installed to be able to return PyTorch tensors.''')
			_register_unavailable_formatter(_torch_error, '''torch''', aliases=['''pt''', '''pytorch'''])

if config.TF_AVAILABLE:
			from .tf_formatter import TFFormatter

			_register_formatter(TFFormatter, '''tensorflow''', aliases=['''tf'''])
else:
			lowerCamelCase_							      = ValueError('''Tensorflow needs to be installed to be able to return Tensorflow tensors.''')
			_register_unavailable_formatter(_tf_error, '''tensorflow''', aliases=['''tf'''])

if config.JAX_AVAILABLE:
			from .jax_formatter import JaxFormatter

			_register_formatter(JaxFormatter, '''jax''', aliases=[])
else:
			lowerCamelCase_							      = ValueError('''JAX needs to be installed to be able to return JAX arrays.''')
			_register_unavailable_formatter(_jax_error, '''jax''', aliases=[])

def 							snake_case (  A__		):
			if format_type in _FORMAT_TYPES_ALIASES:
						return _FORMAT_TYPES_ALIASES[format_type]
			else:
						return format_type




def 							snake_case (  A__      ,**A__		):
			UpperCAmelCase_	:					Optional[int]     	=   get_format_type_from_alias(A__		)
			if format_type in _FORMAT_TYPES:
						return _FORMAT_TYPES[format_type](**A__		)
			if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
						raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
			else:
						raise ValueError(
						    F"""Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None		)}, but got '{format_type}'"""		)











"""simple docstring"""
import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD

def 							snake_case (  A__		):
			def wrapper(*A__      ,**A__		):
						UpperCAmelCase_	:					Union[str, Any]     	=   timeit.default_timer()
						UpperCAmelCase_	:					Union[str, Any]     	=   func(*A__      ,**A__		)
						UpperCAmelCase_	:					Dict     	=   timeit.default_timer() - starttime
						return delta

			UpperCAmelCase_	:					Optional[Any]     	=   func.__name__

			return wrapper

def 							snake_case (  A__      ,A__=1_00      ,A__=None		):
			UpperCAmelCase_	:					str     	=   []
			UpperCAmelCase_	:					List[str]     	=   seq_shapes or {}
			for i in range(A__		):
						UpperCAmelCase_	:					int     	=   {}
						for col_id, (k, v) in enumerate(features.items()		):
									if isinstance(A__      ,_ArrayXD		):
												UpperCAmelCase_	:					Optional[int]     	=   np.random.rand(*v.shape		).astype(v.dtype		)
									elif isinstance(A__      ,datasets.Value		):
												if v.dtype == "string":
															UpperCAmelCase_	:					List[str]     	=   "The small grey turtle was surprisingly fast when challenged."
												else:
															UpperCAmelCase_	:					List[str]     	=   np.random.randint(10      ,size=1		).astype(v.dtype		).item()
									elif isinstance(A__      ,datasets.Sequence		):
												while isinstance(A__      ,datasets.Sequence		):
															UpperCAmelCase_	:					List[str]     	=   v.feature
												UpperCAmelCase_	:					List[Any]     	=   seq_shapes[k]
												UpperCAmelCase_	:					Dict     	=   np.random.rand(*A__		).astype(v.dtype		)
									UpperCAmelCase_	:					Dict     	=   data

						dummy_data.append((i, example)		)

			return dummy_data




def 							snake_case (  A__      ,A__      ,A__=1_00      ,A__=None		):
			UpperCAmelCase_	:					Optional[Any]     	=   generate_examples(A__      ,num_examples=A__      ,seq_shapes=A__		)

			with ArrowWriter(features=A__      ,path=A__		) as writer:
						for key, record in dummy_data:
									UpperCAmelCase_	:					Any     	=   features.encode_example(A__		)
									writer.write(A__		)

						UpperCAmelCase_	,      UpperCAmelCase_	:					Optional[int]     	=   writer.finalize()

			if not num_final_examples == num_examples:
						raise ValueError(
						    F"""Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."""		)

			UpperCAmelCase_	:					List[Any]     	=   datasets.Dataset.from_file(filename=A__      ,info=datasets.DatasetInfo(features=A__		)		)

			return dataset



