'''simple docstring'''






import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


__a										=					logging.get_logger(__name__)

__a										=					{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

__a										=					{
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

__a										=					{
    'gpt-neox-20b': 2_048,
}





class     A__							(       __SCREAMING_SNAKE_CASE   ):





   """simple docstring"""





   UpperCamelCase_       :						Any    				=     VOCAB_FILES_NAMES
   UpperCamelCase_       :						int    				=     PRETRAINED_VOCAB_FILES_MAP
   UpperCamelCase_       :						Optional[Any]    				=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   UpperCamelCase_       :						Dict    				=     ['input_ids', 'attention_mask']




   def __init__( self     :		List[Any]						,     lowerCAmelCase__     :		Any=None						,     lowerCAmelCase__     :		Any=None						,     lowerCAmelCase__     :		List[str]=None						,     lowerCAmelCase__     :		Optional[int]="<|endoftext|>"						,     lowerCAmelCase__     :		Dict="<|endoftext|>"						,     lowerCAmelCase__     :		List[Any]="<|endoftext|>"						,     lowerCAmelCase__     :		Tuple=False						,     **lowerCAmelCase__     :		int						,     )       ->    List[str]:







      """simple docstring"""




      super().__init__(
          _a						,     _a						,     tokenizer_file=_a						,     unk_token=_a						,     bos_token=_a						,     eos_token=_a						,     add_prefix_space=_a						,     **_a						,     )

      _UpperCAmelCase							:	Any							=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
      if pre_tok_state.get("add_prefix_space"						,     _a			) != add_prefix_space:
         _UpperCAmelCase							:	Optional[Any]							=   getattr(_a						,     pre_tok_state.pop("type"			)			)
         _UpperCAmelCase							:	Optional[int]							=   add_prefix_space
         _UpperCAmelCase							:	int							=   pre_tok_class(**_a			)

      _UpperCAmelCase							:	List[Any]							=   add_prefix_space




   def 			_lowerCAmelCase		( self     :		List[Any]						,     lowerCAmelCase__     :		Dict						,     lowerCAmelCase__     :		Tuple = None			)       ->    Any:







      """simple docstring"""




      _UpperCAmelCase							:	List[Any]							=   self._tokenizer.model.save(_a						,     name=_a			)
      return tuple(_a			)




   def 			_lowerCAmelCase		( self     :		Dict						,     lowerCAmelCase__     :		Tuple			)       ->    List[str]:







      """simple docstring"""




      _UpperCAmelCase							:	Optional[int]							=   []
      for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(_a						,     add_special_tokens=_a			) + [self.eos_token_id]			)

      if len(_a			) > self.model_max_length:
         _UpperCAmelCase							:	List[str]							=   input_ids[-self.model_max_length :]
      return input_ids



"""simple docstring"""




import unittest

import torch
from torch import nn

from diffusers.models.activations import get_activation
class 					__lowerCAmelCase					(   unittest.TestCase       ):


		'''simple docstring'''



		def 			__UpperCAmelCase       (  self      ):
				__a           =			get_activation('''swish'''      )

				self.assertIsInstance(_a							, nn.SiLU      )

				self.assertEqual(act(torch.tensor(-100							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertNotEqual(act(torch.tensor(-1							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(0							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(20							, dtype=torch.floataa      )      ).item()							, 20      )

		def 			__UpperCAmelCase       (  self      ):
				__a           =			get_activation('''silu'''      )

				self.assertIsInstance(_a							, nn.SiLU      )

				self.assertEqual(act(torch.tensor(-100							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertNotEqual(act(torch.tensor(-1							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(0							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(20							, dtype=torch.floataa      )      ).item()							, 20      )

		def 			__UpperCAmelCase       (  self      ):
				__a           =			get_activation('''mish'''      )

				self.assertIsInstance(_a							, nn.Mish      )

				self.assertEqual(act(torch.tensor(-200							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertNotEqual(act(torch.tensor(-1							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(0							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(20							, dtype=torch.floataa      )      ).item()							, 20      )





		def 			__UpperCAmelCase       (  self      ):
				__a           =			get_activation('''gelu'''      )

				self.assertIsInstance(_a							, nn.GELU      )

				self.assertEqual(act(torch.tensor(-100							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertNotEqual(act(torch.tensor(-1							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(0							, dtype=torch.floataa      )      ).item()							, 0      )
				self.assertEqual(act(torch.tensor(20							, dtype=torch.floataa      )      ).item()							, 20      )






