

"""simple docstring"""

import logging
import os
from typing import List, TextIO, Union

from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask


_A						=			logging.getLogger(__name__)






class 	_lowercase       (    __UpperCAmelCase		):




	def __init__(			self		,			UpperCAmelCase_=-1 )		->							str:
			# in NER datasets, the last column is usually reserved for NER label
			lowerCamelCase					:      Optional[Any]          =   label_idx




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_		,			UpperCAmelCase_ )		->							List[InputExample]:
			if isinstance(UpperCAmelCase_		,			UpperCAmelCase_ ):
					lowerCamelCase					:      str          =   mode.value
			lowerCamelCase					:      int          =   os.path.join(UpperCAmelCase_		,			F"""{mode}.txt""" )
			lowerCamelCase					:      str          =   1
			lowerCamelCase					:      Optional[Any]          =   []
			with open(UpperCAmelCase_		,			encoding='utf-8' ) as f:
					lowerCamelCase					:      Optional[Any]          =   []
					lowerCamelCase					:      Optional[Any]          =   []
					for line in f:
							if line.startswith('-DOCSTART-' ) or line == "" or line == "\n":
									if words:
											examples.append(InputExample(guid=F"""{mode}-{guid_index}"""		,			words=UpperCAmelCase_		,			labels=UpperCAmelCase_ ) )
											guid_index += 1
											lowerCamelCase					:      Any          =   []
											lowerCamelCase					:      Any          =   []
							else:
									lowerCamelCase					:      List[str]          =   line.split(' ' )
									words.append(splits[0] )
									if len(UpperCAmelCase_ ) > 1:
											labels.append(splits[self.label_idx].replace('\n'		,			'' ) )
									else:
											# Examples could have no label for mode = "test"
											labels.append('O' )
					if words:
							examples.append(InputExample(guid=F"""{mode}-{guid_index}"""		,			words=UpperCAmelCase_		,			labels=UpperCAmelCase_ ) )
			return examples




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_		,			UpperCAmelCase_		,			UpperCAmelCase_ )		->							str:
			lowerCamelCase					:      Optional[Any]          =   0
			for line in test_input_reader:
					if line.startswith('-DOCSTART-' ) or line == "" or line == "\n":
							writer.write(UpperCAmelCase_ )
							if not preds_list[example_id]:
									example_id += 1
					elif preds_list[example_id]:
							lowerCamelCase					:      Union[str, Any]          =   line.split()[0] + ' ' + preds_list[example_id].pop(0 ) + '\n'
							writer.write(UpperCAmelCase_ )
					else:
							logger.warning('Maximum sequence length exceeded: No prediction for \'%s\'.'		,			line.split()[0] )




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_ )		->							List[str]:
			if path:
					with open(UpperCAmelCase_		,			'r' ) as f:
							lowerCamelCase					:      Any          =   f.read().splitlines()
					if "O" not in labels:
							lowerCamelCase					:      List[Any]          =   ['O'] + labels
					return labels
			else:
					return ["O", "B-MISC", "I-MISC", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC"]






class 	_lowercase       (    __UpperCAmelCase		):




	def __init__(			self )		->							Union[str, Any]:
			# in CONLL2003 dataset chunk column is second-to-last
			super().__init__(label_idx=-2 )




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_ )		->							List[str]:
			if path:
					with open(UpperCAmelCase_		,			'r' ) as f:
							lowerCamelCase					:      List[str]          =   f.read().splitlines()
					if "O" not in labels:
							lowerCamelCase					:      Optional[int]          =   ['O'] + labels
					return labels
			else:
					return [
					    "O",
					    "B-ADVP",
					    "B-INTJ",
					    "B-LST",
					    "B-PRT",
					    "B-NP",
					    "B-SBAR",
					    "B-VP",
					    "B-ADJP",
					    "B-CONJP",
					    "B-PP",
					    "I-ADVP",
					    "I-INTJ",
					    "I-LST",
					    "I-PRT",
					    "I-NP",
					    "I-SBAR",
					    "I-VP",
					    "I-ADJP",
					    "I-CONJP",
					    "I-PP",
					]






class 	_lowercase       (    __UpperCAmelCase		):




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_		,			UpperCAmelCase_ )		->							List[InputExample]:
			if isinstance(UpperCAmelCase_		,			UpperCAmelCase_ ):
					lowerCamelCase					:      Union[str, Any]          =   mode.value
			lowerCamelCase					:      Optional[int]          =   os.path.join(UpperCAmelCase_		,			F"""{mode}.txt""" )
			lowerCamelCase					:      str          =   1
			lowerCamelCase					:      int          =   []

			with open(UpperCAmelCase_		,			encoding='utf-8' ) as f:
					for sentence in parse_incr(UpperCAmelCase_ ):
							lowerCamelCase					:      List[Any]          =   []
							lowerCamelCase					:      Optional[Any]          =   []
							for token in sentence:
									words.append(token['form'] )
									labels.append(token['upos'] )
							assert len(UpperCAmelCase_ ) == len(UpperCAmelCase_ )
							if words:
									examples.append(InputExample(guid=F"""{mode}-{guid_index}"""		,			words=UpperCAmelCase_		,			labels=UpperCAmelCase_ ) )
									guid_index += 1
			return examples




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_		,			UpperCAmelCase_		,			UpperCAmelCase_ )		->							Tuple:
			lowerCamelCase					:      Any          =   0
			for sentence in parse_incr(UpperCAmelCase_ ):
					lowerCamelCase					:      Optional[Any]          =   preds_list[example_id]
					lowerCamelCase					:      Union[str, Any]          =   ''
					for token in sentence:
							out += F"""{token['form']} ({token['upos']}|{s_p.pop(0 )}) """
					out += "\n"
					writer.write(UpperCAmelCase_ )
					example_id += 1




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_ )		->							List[str]:
			if path:
					with open(UpperCAmelCase_		,			'r' ) as f:
							return f.read().splitlines()
			else:
					return [
					    "ADJ",
					    "ADP",
					    "ADV",
					    "AUX",
					    "CCONJ",
					    "DET",
					    "INTJ",
					    "NOUN",
					    "NUM",
					    "PART",
					    "PRON",
					    "PROPN",
					    "PUNCT",
					    "SCONJ",
					    "SYM",
					    "VERB",
					    "X",
					]








"""simple docstring"""

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


_A						=			logging.get_logger(__name__)

_A						=			{
    'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
        'https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}






class 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     'trajectory_transformer'
	lowercase_				=     ['past_key_values']
	lowercase_				=     {
	    'hidden_size': 'n_embd',
	    'num_attention_heads': 'n_head',
	    'num_hidden_layers': 'n_layer',
	}




	def __init__(			self		,			UpperCAmelCase_=100		,			UpperCAmelCase_=5		,			UpperCAmelCase_=1		,			UpperCAmelCase_=1		,			UpperCAmelCase_=249		,			UpperCAmelCase_=6		,			UpperCAmelCase_=17		,			UpperCAmelCase_=25		,			UpperCAmelCase_=4		,			UpperCAmelCase_=4		,			UpperCAmelCase_=128		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.0006		,			UpperCAmelCase_=512		,			UpperCAmelCase_=0.02		,			UpperCAmelCase_=1E-1_2		,			UpperCAmelCase_=1		,			UpperCAmelCase_=True		,			UpperCAmelCase_=1		,			UpperCAmelCase_=50256		,			UpperCAmelCase_=50256		,			**UpperCAmelCase_		,			)		->							List[Any]:
			lowerCamelCase					:      int          =   vocab_size
			lowerCamelCase					:      List[str]          =   action_weight
			lowerCamelCase					:      List[Any]          =   reward_weight
			lowerCamelCase					:      List[str]          =   value_weight
			lowerCamelCase					:      Tuple          =   max_position_embeddings
			lowerCamelCase					:      List[str]          =   block_size
			lowerCamelCase					:      Any          =   action_dim
			lowerCamelCase					:      List[Any]          =   observation_dim
			lowerCamelCase					:      Any          =   transition_dim
			lowerCamelCase					:      int          =   learning_rate
			lowerCamelCase					:      Union[str, Any]          =   n_layer
			lowerCamelCase					:      Tuple          =   n_head
			lowerCamelCase					:      Any          =   n_embd
			lowerCamelCase					:      Union[str, Any]          =   embd_pdrop
			lowerCamelCase					:      Optional[int]          =   attn_pdrop
			lowerCamelCase					:      int          =   resid_pdrop
			lowerCamelCase					:      Optional[int]          =   initializer_range
			lowerCamelCase					:      List[str]          =   layer_norm_eps
			lowerCamelCase					:      Any          =   kaiming_initializer_range
			lowerCamelCase					:      str          =   use_cache
			super().__init__(pad_token_id=UpperCAmelCase_		,			bos_token_id=UpperCAmelCase_		,			eos_token_id=UpperCAmelCase_		,			**UpperCAmelCase_ )






