
import csv
import dataclasses
import json
from dataclasses import dataclass
from typing import List, Optional, Union

from ...utils import is_tf_available, is_torch_available, logging


_A       =					logging.get_logger(__name__)







@dataclass
class 	lowerCamelCase						:
     UpperCAmelCase__							:				str
     UpperCAmelCase__							:				str
     UpperCAmelCase__							:				Optional[str] 	=						None
     UpperCAmelCase__							:				Optional[str] 	=						None





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		Any:
         return json.dumps(dataclasses.asdict(self  )							,       indent=2  ) + "\n"







@dataclass(frozen=A_    )
class 	lowerCamelCase						:
     UpperCAmelCase__							:				List[int]
     UpperCAmelCase__							:				Optional[List[int]] 	=						None
     UpperCAmelCase__							:				Optional[List[int]] 	=						None
     UpperCAmelCase__							:				Optional[Union[int, float]] 	=						None





     def 						UpperCAmelCase(self :       Any  )		->		Dict:
         return json.dumps(dataclasses.asdict(self  )  ) + "\n"







class 	lowerCamelCase						:





     def 						UpperCAmelCase(self :       Union[str, Any]							,       _A :       str  )		->		Union[str, Any]:
         raise NotImplementedError()





     def 						UpperCAmelCase(self :       Optional[Any]							,       _A :       List[str]  )		->		Optional[int]:
         raise NotImplementedError()





     def 						UpperCAmelCase(self :       Dict							,       _A :       Optional[int]  )		->		Dict:
         raise NotImplementedError()





     def 						UpperCAmelCase(self :       str							,       _A :       Union[str, Any]  )		->		int:
         raise NotImplementedError()





     def 						UpperCAmelCase(self :       Optional[int]  )		->		List[Any]:
         raise NotImplementedError()





     def 						UpperCAmelCase(self :       List[Any]							,       _A :       Any  )		->		Optional[int]:
         if len(self.get_labels()  ) > 1:
             snake_case						=   self.get_labels()[int(example.label  )]
         return example





     @classmethod
     def 						UpperCAmelCase(cls :       Any							,       _A :       List[Any]							,       _A :       List[Any]=None  )		->		Optional[int]:
         with open(_A							,       "r"							,       encoding="utf-8-sig"  ) as f:
             return list(csv.reader(_A							,       delimiter="\t"							,       quotechar=_A  )  )







class 	lowerCamelCase						(    A_    ):





     def __init__(self :       Optional[int]							,       _A :       List[Any]=None							,       _A :       Optional[int]=None							,       _A :       Dict="classification"							,       _A :       Union[str, Any]=False  )		->		Union[str, Any]:
         snake_case						=   [] if labels is None else labels
         snake_case						=   [] if examples is None else examples
         snake_case						=   mode
         snake_case						=   verbose





     def __len__(self :       int  )		->		Optional[Any]:
         return len(self.examples  )





     def __getitem__(self :       List[str]							,       _A :       Any  )		->		int:
         if isinstance(_A							,       _A  ):
             return SingleSentenceClassificationProcessor(labels=self.labels							,       examples=self.examples[idx]  )
         return self.examples[idx]





     @classmethod
     def 						UpperCAmelCase(cls :       Optional[Any]							,       _A :       Optional[int]							,       _A :       List[str]=""							,       _A :       Any=0							,       _A :       Dict=1							,       _A :       List[Any]=None							,       _A :       str=False							,       **_A :       Optional[Any]  )		->		Optional[Any]:
         snake_case						=   cls(**_A  )
         processor.add_examples_from_csv(
             _A							,       split_name=_A							,       column_label=_A							,       column_text=_A							,       column_id=_A							,       skip_first_row=_A							,       overwrite_labels=_A							,       overwrite_examples=_A							,       )
         return processor





     @classmethod
     def 						UpperCAmelCase(cls :       Optional[int]							,       _A :       Union[str, Any]							,       _A :       int=None							,       **_A :       Union[str, Any]  )		->		int:
         snake_case						=   cls(**_A  )
         processor.add_examples(_A							,       labels=_A  )
         return processor





     def 						UpperCAmelCase(self :       List[Any]							,       _A :       List[str]							,       _A :       str=""							,       _A :       Union[str, Any]=0							,       _A :       Union[str, Any]=1							,       _A :       Any=None							,       _A :       List[Any]=False							,       _A :       Optional[int]=False							,       _A :       int=False							,       )		->		int:
         snake_case						=   self._read_tsv(_A  )
         if skip_first_row:
             snake_case						=   lines[1:]
         snake_case						=   []
         snake_case						=   []
         snake_case						=   []
         for i, line in enumerate(_A  ):
             texts.append(line[column_text]  )
             labels.append(line[column_label]  )
             if column_id is not None:
                 ids.append(line[column_id]  )
             else:
                 snake_case						=   f'{split_name}-{i}' if split_name else str(_A  )
                 ids.append(_A  )

         return self.add_examples(
             _A							,       _A							,       _A							,       overwrite_labels=_A							,       overwrite_examples=_A  )





     def 						UpperCAmelCase(self :       Union[str, Any]							,       _A :       Optional[Any]							,       _A :       Tuple=None							,       _A :       Optional[int]=None							,       _A :       Dict=False							,       _A :       List[str]=False  )		->		Dict:
         if labels is not None and len(_A  ) != len(_A  ):
             raise ValueError(
                 f'Text and labels have mismatched lengths {len(_A  )} and {len(_A  )}'  )
         if ids is not None and len(_A  ) != len(_A  ):
             raise ValueError(f'Text and ids have mismatched lengths {len(_A  )} and {len(_A  )}'  )
         if ids is None:
             snake_case						=   [None] * len(_A  )
         if labels is None:
             snake_case						=   [None] * len(_A  )
         snake_case						=   []
         snake_case						=   set()
         for text_or_text_and_label, label, guid in zip(_A							,       _A							,       _A  ):
             if isinstance(_A							,       (tuple, list)  ) and label is None:
                 snake_case	,				snake_case						=   text_or_text_and_label
             else:
                 snake_case						=   text_or_text_and_label
             added_labels.add(_A  )
             examples.append(InputExample(guid=_A							,       text_a=_A							,       text_b=_A							,       label=_A  )  )

         # Update examples
         if overwrite_examples:
             snake_case						=   examples
         else:
             self.examples.extend(_A  )

         # Update labels
         if overwrite_labels:
             snake_case						=   list(_A  )
         else:
             snake_case						=   list(set(self.labels  ).union(_A  )  )

         return self.examples





     def 						UpperCAmelCase(self :       Any							,       _A :       int							,       _A :       List[Any]=None							,       _A :       Optional[int]=False							,       _A :       Dict=0							,       _A :       Optional[int]=True							,       _A :       int=None							,       )		->		Any:
         if max_length is None:
             snake_case						=   tokenizer.max_len

         snake_case						=   {label: i for i, label in enumerate(self.labels  )}

         snake_case						=   []
         for ex_index, example in enumerate(self.examples  ):
             if ex_index % 1_0_0_0_0 == 0:
                 logger.info(f'Tokenizing example {ex_index}'  )

             snake_case						=   tokenizer.encode(
                 example.text_a							,       add_special_tokens=_A							,       max_length=min(_A							,       tokenizer.max_len  )							,       )
             all_input_ids.append(_A  )

         snake_case						=   max(len(_A  ) for input_ids in all_input_ids  )

         snake_case						=   []
         for ex_index, (input_ids, example) in enumerate(zip(_A							,       self.examples  )  ):
             if ex_index % 1_0_0_0_0 == 0:
                 logger.info(f'Writing example {ex_index}/{len(self.examples  )}'  )
             # The mask has 1 for real tokens and 0 for padding tokens. Only real
             # tokens are attended to.
             snake_case						=   [1 if mask_padding_with_zero else 0] * len(_A  )

             # Zero-pad up to the sequence length.
             snake_case						=   batch_length - len(_A  )
             if pad_on_left:
                 snake_case						=   ([pad_token] * padding_length) + input_ids
                 snake_case						=   ([0 if mask_padding_with_zero else 1] * padding_length) + attention_mask
             else:
                 snake_case						=   input_ids + ([pad_token] * padding_length)
                 snake_case						=   attention_mask + ([0 if mask_padding_with_zero else 1] * padding_length)

             if len(_A  ) != batch_length:
                 raise ValueError(f'Error with input length {len(_A  )} vs {batch_length}'  )
             if len(_A  ) != batch_length:
                 raise ValueError(f'Error with input length {len(_A  )} vs {batch_length}'  )

             if self.mode == "classification":
                 snake_case						=   label_map[example.label]
             elif self.mode == "regression":
                 snake_case						=   float(example.label  )
             else:
                 raise ValueError(self.mode  )

             if ex_index < 5 and self.verbose:
                 logger.info("*** Example ***"  )
                 logger.info(f'guid: {example.guid}'  )
                 logger.info(f'input_ids: {" ".join([str(_A  ) for x in input_ids]  )}'  )
                 logger.info(f'attention_mask: {" ".join([str(_A  ) for x in attention_mask]  )}'  )
                 logger.info(f'label: {example.label} (id = {label})'  )

             features.append(InputFeatures(input_ids=_A							,       attention_mask=_A							,       label=_A  )  )

         if return_tensors is None:
             return features
         elif return_tensors == "tf":
             if not is_tf_available():
                 raise RuntimeError("return_tensors set to 'tf' but TensorFlow 2.0 can't be imported"  )
             import tensorflow as tf

             def gen():
                 for ex in features:
                     yield ({"input_ids": ex.input_ids, "attention_mask": ex.attention_mask}, ex.label)

             snake_case						=   tf.data.Dataset.from_generator(
                 _A							,       ({"input_ids": tf.intaa, "attention_mask": tf.intaa}, tf.intaa)							,       ({"input_ids": tf.TensorShape([None]  ), "attention_mask": tf.TensorShape([None]  )}, tf.TensorShape([]  ))							,       )
             return dataset
         elif return_tensors == "pt":
             if not is_torch_available():
                 raise RuntimeError("return_tensors set to 'pt' but PyTorch can't be imported"  )
             import torch
             from torch.utils.data import TensorDataset

             snake_case						=   torch.tensor([f.input_ids for f in features]							,       dtype=torch.long  )
             snake_case						=   torch.tensor([f.attention_mask for f in features]							,       dtype=torch.long  )
             if self.mode == "classification":
                 snake_case						=   torch.tensor([f.label for f in features]							,       dtype=torch.long  )
             elif self.mode == "regression":
                 snake_case						=   torch.tensor([f.label for f in features]							,       dtype=torch.float  )

             snake_case						=   TensorDataset(_A							,       _A							,       _A  )
             return dataset
         else:
             raise ValueError("return_tensors should be one of 'tf' or 'pt'"  )



import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types







class 	lowerCamelCase						(    unittest.TestCase				,					A_    ):





     def 						UpperCAmelCase(self :       Any  )		->		int:
         snake_case						=   load_tool("translation"  )
         self.tool.setup()
         snake_case						=   load_tool("translation"							,       remote=_A  )





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		Optional[int]:
         snake_case						=   self.tool("Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       str  )		->		int:
         snake_case						=   self.remote_tool("Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       str  )		->		List[str]:
         snake_case						=   self.tool(text="Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		str:
         snake_case						=   self.remote_tool(text="Hey, what's up?"							,       src_lang="English"							,       tgt_lang="French"  )
         self.assertEqual(_A							,       "- Hé, comment ça va?"  )





     def 						UpperCAmelCase(self :       Any  )		->		Tuple:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]
         snake_case						=   self.tool(*_A  )

         # There is a single output
         if len(self.tool.outputs  ) == 1:
             snake_case						=   [outputs]

         self.assertListEqual(output_types(_A  )							,       self.tool.outputs  )





     def 						UpperCAmelCase(self :       List[str]  )		->		List[Any]:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]
         snake_case						=   self.tool(*_A  )

         if not isinstance(_A							,       _A  ):
             snake_case						=   [outputs]

         self.assertEqual(len(_A  )							,       len(self.tool.outputs  )  )

         for output, output_type in zip(_A							,       self.tool.outputs  ):
             snake_case						=   AGENT_TYPE_MAPPING[output_type]
             self.assertTrue(isinstance(_A							,       _A  )  )





     def 						UpperCAmelCase(self :       int  )		->		Any:
         snake_case						=   ["Hey, what's up?", "English", "Spanish"]

         snake_case						=   []

         for _input, input_type in zip(_A							,       self.tool.inputs  ):
             if isinstance(_A							,       _A  ):
                 _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input  ) for _input_type in input_type]  )
             else:
                 _inputs.append(AGENT_TYPE_MAPPING[input_type](_input  )  )

        # Should not raise an error
         snake_case						=   self.tool(*_A  )

         if not isinstance(_A							,       _A  ):
             snake_case						=   [outputs]

         self.assertEqual(len(_A  )							,       len(self.tool.outputs  )  )

