





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase_   =   logging.get_logger(__name__)

lowerCAmelCase_   =   {
    "squeezebert/squeezebert-uncased": (
        "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"
    ),
    "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json",
    "squeezebert/squeezebert-mnli-headless": (
        "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"
    ),
}

class 				A    (__UpperCAmelCase				):
      _SCREAMING_SNAKE_CASE					=							SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
      _SCREAMING_SNAKE_CASE					=							"""squeezebert"""



      def __init__(					self     ,  lowercase_=3_0522     ,  lowercase_=768     ,  lowercase_=12     ,  lowercase_=12     ,  lowercase_=3072     ,  lowercase_="gelu"     ,  lowercase_=0.1     ,  lowercase_=0.1     ,  lowercase_=512     ,  lowercase_=2     ,  lowercase_=0.02     ,  lowercase_=1E-12     ,  lowercase_=0     ,  lowercase_=768     ,  lowercase_=4     ,  lowercase_=4     ,  lowercase_=4     ,  lowercase_=1     ,  lowercase_=4     ,  lowercase_=4     ,  **lowercase_     ,  )      ->   Tuple:



             '''simple docstring'''

             super().__init__(pad_token_id=lowercase_     ,  **lowercase_					)

             _snake_case      :							Optional[Any]     				=						vocab_size
             _snake_case      :							Union[str, Any]     				=						hidden_size
             _snake_case      :							List[str]     				=						num_hidden_layers
             _snake_case      :							Dict     				=						num_attention_heads
             _snake_case      :							List[Any]     				=						hidden_act
             _snake_case      :							str     				=						intermediate_size
             _snake_case      :							List[str]     				=						hidden_dropout_prob
             _snake_case      :							Optional[Any]     				=						attention_probs_dropout_prob
             _snake_case      :							Dict     				=						max_position_embeddings
             _snake_case      :							Tuple     				=						type_vocab_size
             _snake_case      :							Optional[Any]     				=						initializer_range
             _snake_case      :							str     				=						layer_norm_eps
             _snake_case      :							Optional[Any]     				=						embedding_size
             _snake_case      :							Optional[Any]     				=						q_groups
             _snake_case      :							Optional[Any]     				=						k_groups
             _snake_case      :							Dict     				=						v_groups
             _snake_case      :							List[Any]     				=						post_attention_groups
             _snake_case      :							List[Any]     				=						intermediate_groups
             _snake_case      :							Optional[int]     				=						output_groups


class 				A    (__UpperCAmelCase				):



      @property
      def    __a (					self					)      ->   Mapping[str, Mapping[int, str]]:



             '''simple docstring'''

             if self.task == "multiple-choice":
                    _snake_case      :							List[str]     				=						{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
             else:
                    _snake_case      :							Optional[Any]     				=						{0: '''batch''', 1: '''sequence'''}
             return OrderedDict(
                 [
                     ('''input_ids''', dynamic_axis),
                     ('''attention_mask''', dynamic_axis),
                     ('''token_type_ids''', dynamic_axis),
                 ]					)













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 				A    (unittest.TestCase       ,__UpperCAmelCase				):



      def    __a (					self					)      ->   str:



             '''simple docstring'''

             _snake_case      :							List[Any]     				=						load_tool('''translation'''					)
             self.tool.setup()
             _snake_case      :							Any     				=						load_tool('''translation'''     ,  remote=lowercase_					)



      def    __a (					self					)      ->   Optional[int]:



             '''simple docstring'''

             _snake_case      :							Tuple     				=						self.tool('''Hey, what\'s up?'''     ,  src_lang='''English'''     ,  tgt_lang='''French'''					)
             self.assertEqual(lowercase_     ,  '''- Hé, comment ça va?'''					)



      def    __a (					self					)      ->   Union[str, Any]:



             '''simple docstring'''

             _snake_case      :							Optional[int]     				=						self.remote_tool('''Hey, what\'s up?'''     ,  src_lang='''English'''     ,  tgt_lang='''French'''					)
             self.assertEqual(lowercase_     ,  '''- Hé, comment ça va?'''					)



      def    __a (					self					)      ->   List[Any]:



             '''simple docstring'''

             _snake_case      :							Dict     				=						self.tool(text='''Hey, what\'s up?'''     ,  src_lang='''English'''     ,  tgt_lang='''French'''					)
             self.assertEqual(lowercase_     ,  '''- Hé, comment ça va?'''					)



      def    __a (					self					)      ->   Dict:



             '''simple docstring'''

             _snake_case      :							List[Any]     				=						self.remote_tool(text='''Hey, what\'s up?'''     ,  src_lang='''English'''     ,  tgt_lang='''French'''					)
             self.assertEqual(lowercase_     ,  '''- Hé, comment ça va?'''					)



      def    __a (					self					)      ->   str:



             '''simple docstring'''

             _snake_case      :							Optional[int]     				=						['''Hey, what\'s up?''', '''English''', '''Spanish''']
             _snake_case      :							Dict     				=						self.tool(*lowercase_					)

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

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



      def    __a (					self					)      ->   Tuple:



             '''simple docstring'''

             _snake_case      :							Union[str, Any]     				=						['''Hey, what\'s up?''', '''English''', '''Spanish''']
             _snake_case      :							Dict     				=						self.tool(*lowercase_					)

             if not isinstance(lowercase_     ,  lowercase_					):
                    _snake_case      :							Optional[Any]     				=						[outputs]

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

             for output, output_type in zip(lowercase_     ,  self.tool.outputs					):
                    _snake_case      :							List[str]     				=						AGENT_TYPE_MAPPING[output_type]
                    self.assertTrue(isinstance(lowercase_     ,  lowercase_					)					)



      def    __a (					self					)      ->   List[Any]:



             '''simple docstring'''

             _snake_case      :							Dict     				=						['''Hey, what\'s up?''', '''English''', '''Spanish''']

             _snake_case      :							Any     				=						[]

             for _input, input_type in zip(lowercase_     ,  self.tool.inputs					):
                    if isinstance(lowercase_     ,  lowercase_					):
                           _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      :							List[Any]     				=						self.tool(*lowercase_					)

             if not isinstance(lowercase_     ,  lowercase_					):
                    _snake_case      :							Any     				=						[outputs]

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






