'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase_ : Optional[Any]						  =      {
    "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : Tuple						  =      ["ConvNextFeatureExtractor"]
       lowerCAmelCase_ : List[str]						  =      ["ConvNextImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : Optional[int]						  =      [
           "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "ConvNextForImageClassification",
           "ConvNextModel",
           "ConvNextPreTrainedModel",
           "ConvNextBackbone",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase_ : Any						  =      [
           "TFConvNextForImageClassification",
           "TFConvNextModel",
           "TFConvNextPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_convnext import ConvNextFeatureExtractor
              from .image_processing_convnext import ConvNextImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_convnext import (
                  CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ConvNextBackbone,
                  ConvNextForImageClassification,
                  ConvNextModel,
                  ConvNextPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
       import sys

       lowerCAmelCase_ : Optional[int]						  =      _LazyModule(__name__, globals()["__file__"], _import_structure)







'''simple docstring'''

import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


lowerCAmelCase_ : Union[str, Any]						  =      datasets.utils.logging.get_logger(__name__)





@dataclass
class 							lowercase						(						datasets.BuilderConfig ):
   lowerCamelCase_    					=None
   lowerCamelCase_    					="utf-8"
   lowerCamelCase_    					=None
   lowerCamelCase_    					=None
   lowerCamelCase_    					=True  # deprecated
   lowerCamelCase_    					=None  # deprecated
   lowerCamelCase_    					=1_0 << 2_0  # 10MB
   lowerCamelCase_    					=None





class 							lowercase						(						datasets.ArrowBasedBuilder ):
   lowerCamelCase_    					=JsonConfig


   def __UpperCAmelCase       (   self				:	int)      ->					List[str]:
         if self.config.block_size is not None:
               logger.warning("The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead")
               lowercase_     =      self.config.block_size
         if self.config.use_threads is not True:
               logger.warning(
                   "The JSON loader parameter `use_threads` is deprecated and doesn't have any effect anymore.")
         if self.config.newlines_in_values is not None:
               raise ValueError("The JSON loader parameter `newlines_in_values` is no longer supported")
         return datasets.DatasetInfo(features=self.config.features)


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	int)      ->					Any:
         if not self.config.data_files:
               raise ValueError(F'At least one data file must be specified, but got data_files={self.config.data_files}')
         lowercase_     =      dl_manager.download_and_extract(self.config.data_files)
         if isinstance(__lowerCAmelCase   ,		(str, list, tuple)):
               lowercase_     =      data_files
               if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
                     lowercase_     =      [files]
               lowercase_     =      [dl_manager.iter_files(__lowerCAmelCase) for file in files]
               return [datasets.SplitGenerator(name=datasets.Split.TRAIN   ,		gen_kwargs={"files": files})]
         lowercase_     =      []
         for split_name, files in data_files.items():
               if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):
                     lowercase_     =      [files]
               lowercase_     =      [dl_manager.iter_files(__lowerCAmelCase) for file in files]
               splits.append(datasets.SplitGenerator(name=__lowerCAmelCase   ,		gen_kwargs={"files": files}))
         return splits


   def __UpperCAmelCase       (   self				:	Any   ,		__lowerCAmelCase				:	pa.Table)      ->					pa.Table:
         if self.config.features is not None:
               # adding missing columns
               for column_name in set(self.config.features) - set(pa_table.column_names):
                     lowercase_     =      self.config.features.arrow_schema.field(__lowerCAmelCase).type
                     lowercase_     =      pa_table.append_column(__lowerCAmelCase   ,		pa.array([None] * len(__lowerCAmelCase)   ,		type=__lowerCAmelCase))
               # more expensive cast to support nested structures with keys in a different order
               # allows str <-> int/float or str to Audio for example
               lowercase_     =      table_cast(__lowerCAmelCase   ,		self.config.features.arrow_schema)
         return pa_table


   def __UpperCAmelCase       (   self				:	List[Any]   ,		__lowerCAmelCase				:	List[Any])      ->					List[Any]:
         for file_idx, file in enumerate(itertools.chain.from_iterable(__lowerCAmelCase)):
               # If the file is one json object and if we need to look at the list of items in one specific field
               if self.config.field is not None:
                     with open(__lowerCAmelCase   ,		encoding=self.config.encoding   ,		errors=self.config.encoding_errors) as f:
                           lowercase_     =      json.load(__lowerCAmelCase)

                     # We keep only the field we are interested in
                     lowercase_     =      dataset[self.config.field]

                     # We accept two format: a list of dicts or a dict of lists
                     if isinstance(__lowerCAmelCase   ,		(list, tuple)):
                           lowercase_     =      set().union(*[row.keys() for row in dataset])
                           lowercase_     =      {col: [row.get(__lowerCAmelCase) for row in dataset] for col in keys}
                     else:
                           lowercase_     =      dataset
                     lowercase_     =      pa.Table.from_pydict(__lowerCAmelCase)
                     yield file_idx, self._cast_table(__lowerCAmelCase)

               # If the file has one json object per line
               else:
                     with open(__lowerCAmelCase   ,		"rb") as f:
                           lowercase_     =      0
                           # Use block_size equal to the chunk size divided by 32 to leverage multithreading
                           # Set a default minimum value of 16kB if the chunk size is really small
                           lowercase_     =      max(self.config.chunksize // 32   ,		16 << 10)
                           lowercase_     =      (
                               self.config.encoding_errors if self.config.encoding_errors is not None else "strict"
                           )
                           while True:
                                 lowercase_     =      f.read(self.config.chunksize)
                                 if not batch:
                                       break
                                 # Finish current line
                                 try:
                                       batch += f.readline()
                                 except (AttributeError, io.UnsupportedOperation):
                                       batch += readline(__lowerCAmelCase)
                                 # PyArrow only accepts utf-8 encoded bytes
                                 if self.config.encoding != "utf-8":
                                       lowercase_     =      batch.decode(self.config.encoding   ,		errors=__lowerCAmelCase).encode("utf-8")
                                 try:
                                       while True:
                                             try:
                                                   lowercase_     =      paj.read_json(
                                                       io.BytesIO(__lowerCAmelCase)   ,		read_options=paj.ReadOptions(block_size=__lowerCAmelCase))
                                                   break
                                             except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
                                                   if (
                                                       isinstance(__lowerCAmelCase   ,		pa.ArrowInvalid)
                                                       and "straddling" not in str(__lowerCAmelCase)
                                                       or block_size > len(__lowerCAmelCase)
                                                   ):
                                                         raise
                                                   else:
                                                         # Increase the block size in case it was too small.
                                                         # The block size will be reset for the next file.
                                                         logger.debug(
                                                             F'Batch of {len(__lowerCAmelCase)} bytes couldn\'t be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}.')
                                                         block_size *= 2
                                 except pa.ArrowInvalid as e:
                                       try:
                                             with open(
                                                 __lowerCAmelCase   ,		encoding=self.config.encoding   ,		errors=self.config.encoding_errors) as f:
                                                   lowercase_     =      json.load(__lowerCAmelCase)
                                       except json.JSONDecodeError:
                                             logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                             raise e
                                       # If possible, parse the file as a list of json objects and exit the loop
                                       if isinstance(__lowerCAmelCase   ,		__lowerCAmelCase):  # list is the only sequence type supported in JSON
                                             try:
                                                   lowercase_     =      set().union(*[row.keys() for row in dataset])
                                                   lowercase_     =      {col: [row.get(__lowerCAmelCase) for row in dataset] for col in keys}
                                                   lowercase_     =      pa.Table.from_pydict(__lowerCAmelCase)
                                             except (pa.ArrowInvalid, AttributeError) as e:
                                                   logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                                   raise ValueError(F'Not able to read records in the JSON file at {file}.') from None
                                             yield file_idx, self._cast_table(__lowerCAmelCase)
                                             break
                                       else:
                                             logger.error(F'Failed to read file \'{file}\' with error {type(__lowerCAmelCase)}: {e}')
                                             raise ValueError(
                                                 F'Not able to read records in the JSON file at {file}. '
                                                 F'You should probably indicate the field of the JSON file containing your records. '
                                                 F'This JSON file contain the following fields: {str(list(dataset.keys()))}. '
                                                 F'Select the correct one and provide it as `field=\'XXX\'` to the dataset loading method. ') from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                                 yield (file_idx, batch_idx), self._cast_table(__lowerCAmelCase)
                                 batch_idx += 1






