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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool







class 		snake_case    (						__UpperCamelCase	):



   '''simple docstring'''






   snake_case_       :			Union[str, Any]        =		"""philschmid/bart-large-cnn-samsum"""
   snake_case_       :			Optional[int]        =		(
       """This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, """
       """and returns a summary of the text."""
   )
   snake_case_       :			List[str]        =		"""summarizer"""
   snake_case_       :			Optional[int]        =		AutoTokenizer
   snake_case_       :			Optional[Any]        =		AutoModelForSeqaSeqLM

   snake_case_       :			Optional[Any]        =		["""text"""]
   snake_case_       :			int        =		["""text"""]

   def   UpperCamelCase_	(       self				:      List[Any]					,		lowerCAmelCase				:      Optional[int])					->					str:

    """simple docstring"""







    return self.pre_processor(__UpperCAmelCase					,		return_tensors="""pt"""					,		truncation=__UpperCAmelCase)

   def   UpperCamelCase_	(       self				:      Dict					,		lowerCAmelCase				:      int)					->					int:

    """simple docstring"""







    return self.model.generate(**__UpperCAmelCase)[0]


   def   UpperCamelCase_	(       self				:      Any					,		lowerCAmelCase				:      int)					->					Any:

    """simple docstring"""







    return self.pre_processor.decode(__UpperCAmelCase					,		skip_special_tokens=__UpperCAmelCase					,		clean_up_tokenization_spaces=__UpperCAmelCase)








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


UpperCAmelCase__      			=						logging.get_logger(__name__)

UpperCAmelCase__      			=						{
    '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}




class 							snake_case_       (    __UpperCamelCase      ):

						"""simple docstring"""



						snake_case__        =      """glpn"""



						def __init__(self:					Tuple ,					__UpperCAmelCase:					Tuple=3 ,					__UpperCAmelCase:					Dict=4 ,					__UpperCAmelCase:					Any=[2, 2, 2, 2] ,					__UpperCAmelCase:					Optional[int]=[8, 4, 2, 1] ,					__UpperCAmelCase:					Dict=[32, 64, 160, 256] ,					__UpperCAmelCase:					List[str]=[7, 3, 3, 3] ,					__UpperCAmelCase:					Dict=[4, 2, 2, 2] ,					__UpperCAmelCase:					Optional[int]=[1, 2, 5, 8] ,					__UpperCAmelCase:					Dict=[4, 4, 4, 4] ,					__UpperCAmelCase:					List[str]="gelu" ,					__UpperCAmelCase:					str=0.0 ,					__UpperCAmelCase:					List[Any]=0.0 ,					__UpperCAmelCase:					Dict=0.02 ,					__UpperCAmelCase:					List[str]=0.1 ,					__UpperCAmelCase:					Union[str, Any]=1E-6 ,					__UpperCAmelCase:					Dict=64 ,					__UpperCAmelCase:					Dict=10 ,					__UpperCAmelCase:					Union[str, Any]=-1 ,					**__UpperCAmelCase:					Dict ,					)    ->     str:




											'''simple docstring'''



											super().__init__(**__UpperCAmelCase   )

											__a					:						Optional[Any]      =					num_channels
											__a					:						Tuple      =					num_encoder_blocks
											__a					:						int      =					depths
											__a					:						Union[str, Any]      =					sr_ratios
											__a					:						str      =					hidden_sizes
											__a					:						List[Any]      =					patch_sizes
											__a					:						Optional[Any]      =					strides
											__a					:						Any      =					mlp_ratios
											__a					:						Any      =					num_attention_heads
											__a					:						Any      =					hidden_act
											__a					:						List[Any]      =					hidden_dropout_prob
											__a					:						int      =					attention_probs_dropout_prob
											__a					:						List[str]      =					initializer_range
											__a					:						Optional[int]      =					drop_path_rate
											__a					:						Any      =					layer_norm_eps
											__a					:						List[Any]      =					decoder_hidden_size
											__a					:						Any      =					max_depth
											__a					:						int      =					head_in_index





