
from collections import OrderedDict
from typing import Mapping

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


__magic_name__  :  int     			=   logging.get_logger(__name__)

__magic_name__  :  int     			=   {
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}


class 							lowerCamelCase       (		__snake_case					):



  """simple docstring"""





  lowerCAmelCase_								=		"""electra"""

  def __init__(					self						,    __UpperCamelCase=30522						,    __UpperCamelCase=128						,    __UpperCamelCase=256						,    __UpperCamelCase=12						,    __UpperCamelCase=4						,    __UpperCamelCase=1024						,    __UpperCamelCase="gelu"						,    __UpperCamelCase=0.1						,    __UpperCamelCase=0.1						,    __UpperCamelCase=512						,    __UpperCamelCase=2						,    __UpperCamelCase=0.02						,    __UpperCamelCase=1E-12						,    __UpperCamelCase="first"						,    __UpperCamelCase=True						,    __UpperCamelCase="gelu"						,    __UpperCamelCase=0.1						,    __UpperCamelCase=0						,    __UpperCamelCase="absolute"						,    __UpperCamelCase=True						,    __UpperCamelCase=None						,    **__UpperCamelCase						,    ):
      super().__init__(pad_token_id=__UpperCamelCase						,    **__UpperCamelCase					)

      A_								=					vocab_size
      A_								=					embedding_size
      A_								=					hidden_size
      A_								=					num_hidden_layers
      A_								=					num_attention_heads
      A_								=					intermediate_size
      A_								=					hidden_act
      A_								=					hidden_dropout_prob
      A_								=					attention_probs_dropout_prob
      A_								=					max_position_embeddings
      A_								=					type_vocab_size
      A_								=					initializer_range
      A_								=					layer_norm_eps

      A_								=					summary_type
      A_								=					summary_use_proj
      A_								=					summary_activation
      A_								=					summary_last_dropout
      A_								=					position_embedding_type
      A_								=					use_cache
      A_								=					classifier_dropout



class 							lowerCamelCase       (		__snake_case					):



  """simple docstring"""





  @property
  def 					lowercase_						(					self					):
      if self.task == "multiple-choice":
          A_								=					{0: "batch", 1: "choice", 2: "sequence"}
      else:
          A_								=					{0: "batch", 1: "sequence"}
      return OrderedDict(
          [
              ("input_ids", dynamic_axis),
              ("attention_mask", dynamic_axis),
              ("token_type_ids", dynamic_axis),
          ]					)








import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
     from PIL import Image


class 							lowerCamelCase       (		unittest.TestCase			,  __snake_case					):



  """simple docstring"""





  def 					lowercase_						(					self					):
      A_								=					load_tool("image-question-answering"					)
      self.tool.setup()
      A_								=					load_tool("image-question-answering"						,    remote=__UpperCamelCase					)

  def 					lowercase_						(					self					):
      A_								=					Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
      A_								=					self.tool(__UpperCamelCase						,    "How many cats are sleeping on the couch?"					)
      self.assertEqual(__UpperCamelCase						,    "2"					)

  def 					lowercase_						(					self					):
      A_								=					Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
      A_								=					self.remote_tool(__UpperCamelCase						,    "How many cats are sleeping on the couch?"					)
      self.assertEqual(__UpperCamelCase						,    "2"					)

  def 					lowercase_						(					self					):
      A_								=					Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
      A_								=					self.tool(image=__UpperCamelCase						,    question="How many cats are sleeping on the couch?"					)
      self.assertEqual(__UpperCamelCase						,    "2"					)

  def 					lowercase_						(					self					):
      A_								=					Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
      A_								=					self.remote_tool(image=__UpperCamelCase						,    question="How many cats are sleeping on the couch?"					)
      self.assertEqual(__UpperCamelCase						,    "2"					)






