




'''simple docstring'''






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 	SCREAMING_SNAKE_CASE_		(							unittest.TestCase		,  __lowerCAmelCase					):



 def  SCREAMING_SNAKE_CASE(	self			):






        '''simple docstring'''




        lowercase	:		List[str]    =   load_tool('''image-question-answering'''			)
        self.tool.setup()
        lowercase	:		Union[str, Any]    =   load_tool('''image-question-answering''' ,		remote=lowercase_			)



 def  SCREAMING_SNAKE_CASE(	self			):






        '''simple docstring'''




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



 def  SCREAMING_SNAKE_CASE(	self			):






        '''simple docstring'''




        lowercase	:		Union[str, Any]    =   Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''			)			) / '''000000039769.png'''			)
        lowercase	:		List[Any]    =   self.remote_tool(lowercase_ ,		'''How many cats are sleeping on the couch?'''			)
        self.assertEqual(lowercase_ ,		'''2'''			)



 def  SCREAMING_SNAKE_CASE(	self			):






        '''simple docstring'''




        lowercase	:		Optional[Any]    =   Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''			)			) / '''000000039769.png'''			)
        lowercase	:		int    =   self.tool(image=lowercase_ ,		question='''How many cats are sleeping on the couch?'''			)
        self.assertEqual(lowercase_ ,		'''2'''			)





 def  SCREAMING_SNAKE_CASE(	self			):






        '''simple docstring'''




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







'''simple docstring'''

from typing import List, Union

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


lowerCAmelCase_     =      logging.get_logger(__name__)

lowerCAmelCase_     =      {
    "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/config.json",
    # See all LED models at https://huggingface.co/models?filter=led
}







class lowerCamelCase   (    __lowerCAmelCase				):
				snake_case_							     = '''led'''
				snake_case_							     = {
				    '''num_attention_heads''': '''encoder_attention_heads''',
				    '''hidden_size''': '''d_model''',
				    '''attention_probs_dropout_prob''': '''attention_dropout''',
				    '''initializer_range''': '''init_std''',
				}

				def __init__(       self,						lowercase_=50265,						lowercase_=16384,						lowercase_=1024,						lowercase_=12,						lowercase_=4096,						lowercase_=16,						lowercase_=12,						lowercase_=4096,						lowercase_=16,						lowercase_=0.0,						lowercase_=0.0,						lowercase_=True,						lowercase_=True,						lowercase_="gelu",						lowercase_=1024,						lowercase_=0.1,						lowercase_=0.0,						lowercase_=0.0,						lowercase_=0.02,						lowercase_=2,						lowercase_=0.0,						lowercase_=1,						lowercase_=0,						lowercase_=2,						lowercase_ = 512,						**lowercase_,						)    ->							Union[str, Any]:
					snake_case							=					vocab_size
					snake_case							=					max_encoder_position_embeddings
					snake_case							=					max_decoder_position_embeddings
					snake_case							=					d_model
					snake_case							=					encoder_ffn_dim
					snake_case							=					encoder_layers
					snake_case							=					encoder_attention_heads
					snake_case							=					decoder_ffn_dim
					snake_case							=					decoder_layers
					snake_case							=					decoder_attention_heads
					snake_case							=					dropout
					snake_case							=					attention_dropout
					snake_case							=					activation_dropout
					snake_case							=					activation_function
					snake_case							=					init_std
					snake_case							=					encoder_layerdrop
					snake_case							=					decoder_layerdrop
					snake_case							=					classifier_dropout
					snake_case							=					use_cache
					snake_case							=					encoder_layers
					snake_case							=					attention_window

					super().__init__(
					    pad_token_id=lowercase_,						bos_token_id=lowercase_,						eos_token_id=lowercase_,						is_encoder_decoder=lowercase_,						decoder_start_token_id=lowercase_,						**lowercase_,						)





