



import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


UpperCAmelCase__       =	datasets.utils.logging.get_logger(__name__)

UpperCAmelCase__       =	["""names""", """prefix"""]
UpperCAmelCase__       =	["""warn_bad_lines""", """error_bad_lines""", """mangle_dupe_cols"""]
UpperCAmelCase__       =	["""encoding_errors""", """on_bad_lines"""]
UpperCAmelCase__       =	["""date_format"""]







@dataclass
class       __lowerCAmelCase   (      datasets.BuilderConfig						):
			UpperCamelCase        =					","
			UpperCamelCase        =					None
			UpperCamelCase        =					"infer"
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					True
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					False
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					True
			UpperCamelCase        =					True
			UpperCamelCase        =					False
			UpperCamelCase        =					True
			UpperCamelCase        =					None
			UpperCamelCase        =					"."
			UpperCamelCase        =					None
			UpperCamelCase        =					'"'
			UpperCamelCase        =					0
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					None
			UpperCamelCase        =					True
			UpperCamelCase        =					True
			UpperCamelCase        =					0
			UpperCamelCase        =					True
			UpperCamelCase        =					False
			UpperCamelCase        =					None
			UpperCamelCase        =					1_0_0_0_0
			UpperCamelCase        =					None
			UpperCamelCase        =					"strict"
			UpperCamelCase        =					"error"
			UpperCamelCase        =					None



			def    _lowerCamelCase	(						self       :  Dict)       ->   Tuple:



						"""simple docstring"""






						if self.delimiter is not None:
									_UpperCAmelCase			=       self.delimiter
						if self.column_names is not None:
									_UpperCAmelCase			=       self.column_names



			@property
			def    _lowerCamelCase	(						self       :  Optional[Any])       ->   Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       {
						    'sep': self.sep,
						    'header': self.header,
						    'names': self.names,
						    'index_col': self.index_col,
						    'usecols': self.usecols,
						    'prefix': self.prefix,
						    'mangle_dupe_cols': self.mangle_dupe_cols,
						    'engine': self.engine,
						    'converters': self.converters,
						    'true_values': self.true_values,
						    'false_values': self.false_values,
						    'skipinitialspace': self.skipinitialspace,
						    'skiprows': self.skiprows,
						    'nrows': self.nrows,
						    'na_values': self.na_values,
						    'keep_default_na': self.keep_default_na,
						    'na_filter': self.na_filter,
						    'verbose': self.verbose,
						    'skip_blank_lines': self.skip_blank_lines,
						    'thousands': self.thousands,
						    'decimal': self.decimal,
						    'lineterminator': self.lineterminator,
						    'quotechar': self.quotechar,
						    'quoting': self.quoting,
						    'escapechar': self.escapechar,
						    'comment': self.comment,
						    'encoding': self.encoding,
						    'dialect': self.dialect,
						    'error_bad_lines': self.error_bad_lines,
						    'warn_bad_lines': self.warn_bad_lines,
						    'skipfooter': self.skipfooter,
						    'doublequote': self.doublequote,
						    'memory_map': self.memory_map,
						    'float_precision': self.float_precision,
						    'chunksize': self.chunksize,
						    'encoding_errors': self.encoding_errors,
						    'on_bad_lines': self.on_bad_lines,
						    'date_format': self.date_format,
						}

						# some kwargs must not be passed if they don't have a default value
						# some others are deprecated and we can also not pass them if they are the default value
						for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
									if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()			,		_lowercase):
												del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
						if not (datasets.config.PANDAS_VERSION.major >= 2):
									for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
												del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
						if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
									for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
												del pd_read_csv_kwargs[pd_read_csv_parameter]

						return pd_read_csv_kwargs







class       __lowerCAmelCase   (      datasets.ArrowBasedBuilder						):
			UpperCamelCase        =					CsvConfig



			def    _lowerCamelCase	(						self       :  Tuple)       ->   Dict:



						"""simple docstring"""






						return datasets.DatasetInfo(features=self.config.features)



			def    _lowerCamelCase	(						self       :  List[str]			,		A       :  Union[str, Any])       ->   Optional[int]:



						"""simple docstring"""






						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}")
						_UpperCAmelCase			=       dl_manager.download_and_extract(self.config.data_files)
						if isinstance(_lowercase			,		(str, list, tuple)):
									_UpperCAmelCase			=       data_files
									if isinstance(_lowercase			,		_lowercase):
												_UpperCAmelCase			=       [files]
									_UpperCAmelCase			=       [dl_manager.iter_files(_lowercase) for file in files]
									return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,		gen_kwargs={'files': files})]
						_UpperCAmelCase			=       []
						for split_name, files in data_files.items():
									if isinstance(_lowercase			,		_lowercase):
												_UpperCAmelCase			=       [files]
									_UpperCAmelCase			=       [dl_manager.iter_files(_lowercase) for file in files]
									splits.append(datasets.SplitGenerator(name=_lowercase			,		gen_kwargs={'files': files}))
						return splits



			def    _lowerCamelCase	(						self       :  Union[str, Any]			,		A       :  Optional[int])       ->   pa.Table:



						"""simple docstring"""






						if self.config.features is not None:
									_UpperCAmelCase			=       self.config.features.arrow_schema
									if all(not require_storage_cast(_lowercase) for feature in self.config.features.values()):
												# cheaper cast
												_UpperCAmelCase			=       pa.Table.from_arrays([pa_table[field.name] for field in schema]			,		schema=_lowercase)
									else:
												# more expensive cast; allows str <-> int/float or str to Audio for example
												_UpperCAmelCase			=       table_cast(_lowercase			,		_lowercase)
						return pa_table



			def    _lowerCamelCase	(						self       :  Any			,		A       :  List[Any])       ->   Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       self.config.features.arrow_schema if self.config.features else None
						# dtype allows reading an int column as str
						_UpperCAmelCase			=       (
						    {
						        name: dtype.to_pandas_dtype() if not require_storage_cast(_lowercase) else object
						        for name, dtype, feature in zip(schema.names			,		schema.types			,		self.config.features.values())
						    }
						    if schema is not None
						    else None
						)
						for file_idx, file in enumerate(itertools.chain.from_iterable(_lowercase)):
									_UpperCAmelCase			=       pd.read_csv(_lowercase			,		iterator=_lowercase			,		dtype=_lowercase			,		**self.config.pd_read_csv_kwargs)
									try:
												for batch_idx, df in enumerate(_lowercase):
															_UpperCAmelCase			=       pa.Table.from_pandas(_lowercase)
															# 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(_lowercase)
									except ValueError as e:
												logger.error(F"Failed to read file '{file}' with error {type(_lowercase)}: {e}")
												raise





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase__       =	logging.get_logger(__name__)

UpperCAmelCase__       =	{
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}







class       __lowerCAmelCase   (      A						):
			UpperCamelCase        =					'''decision_transformer'''
			UpperCamelCase        =					['''past_key_values''']
			UpperCamelCase        =					{
			    '''max_position_embeddings''': '''n_positions''',
			    '''num_attention_heads''': '''n_head''',
			    '''num_hidden_layers''': '''n_layer''',
			}



			def __init__(						self       :  Any			,		A       :  Optional[int]=17			,		A       :  List[str]=4			,		A       :  int=1_28			,		A       :  Union[str, Any]=40_96			,		A       :  Any=True			,		A       :  Any=1			,		A       :  List[Any]=10_24			,		A       :  List[Any]=3			,		A       :  Tuple=1			,		A       :  Any=None			,		A       :  Optional[int]="relu"			,		A       :  Union[str, Any]=0.1			,		A       :  Optional[int]=0.1			,		A       :  Optional[int]=0.1			,		A       :  Optional[int]=1E-5			,		A       :  List[Any]=0.0_2			,		A       :  Tuple=True			,		A       :  Union[str, Any]=True			,		A       :  str=5_02_56			,		A       :  Union[str, Any]=5_02_56			,		A       :  List[Any]=False			,		A       :  Optional[int]=False			,		**A       :  int			,		)       ->   Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       state_dim
						_UpperCAmelCase			=       act_dim
						_UpperCAmelCase			=       hidden_size
						_UpperCAmelCase			=       max_ep_len
						_UpperCAmelCase			=       action_tanh
						_UpperCAmelCase			=       vocab_size
						_UpperCAmelCase			=       n_positions
						_UpperCAmelCase			=       n_layer
						_UpperCAmelCase			=       n_head
						_UpperCAmelCase			=       n_inner
						_UpperCAmelCase			=       activation_function
						_UpperCAmelCase			=       resid_pdrop
						_UpperCAmelCase			=       embd_pdrop
						_UpperCAmelCase			=       attn_pdrop
						_UpperCAmelCase			=       layer_norm_epsilon
						_UpperCAmelCase			=       initializer_range
						_UpperCAmelCase			=       scale_attn_weights
						_UpperCAmelCase			=       use_cache
						_UpperCAmelCase			=       scale_attn_by_inverse_layer_idx
						_UpperCAmelCase			=       reorder_and_upcast_attn

						_UpperCAmelCase			=       bos_token_id
						_UpperCAmelCase			=       eos_token_id

						super().__init__(bos_token_id=A			,		eos_token_id=A			,		**A)
