






'''simple docstring'''



from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
      from PIL import Image

      from ..image_utils import load_image

if is_tf_available():
      import tensorflow as tf

      from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
      from ..tf_utils import stable_softmax

if is_torch_available():
      from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

SCREAMING_SNAKE_CASE							=						logging.get_logger(__name__)
@add_end_docstrings(__A					)
class UpperCAmelCase_       (     __A					):




      """simple docstring"""




      def __init__(			self      :		Tuple  ,   *UpperCAmelCase      :		int  ,   **UpperCAmelCase      :		Optional[Any]		)	->	Dict:


       '''simple docstring'''

       super().__init__(*UpperCAmelCase  ,   **UpperCAmelCase		)
       requires_backends(self  ,   '''vision'''		)
       self.check_model_type(
           TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
           if self.framework == '''tf'''
           else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING		)






      def 					A__   (			self      :		str  ,   UpperCAmelCase      :		str=None		)	->	Union[str, Any]:


       '''simple docstring'''

       lowercase       : Dict						={}
       if top_k is not None:
        lowercase       : Union[str, Any]						=top_k
       return {}, {}, postprocess_params






      def __call__(			self      :		str  ,   UpperCAmelCase      :		Union[str, List[str], "Image.Image", List["Image.Image"]]  ,   **UpperCAmelCase      :		str		)	->	Optional[Any]:


       '''simple docstring'''

       return super().__call__(UpperCAmelCase  ,   **UpperCAmelCase		)






      def 					A__   (			self      :		str  ,   UpperCAmelCase      :		Optional[int]		)	->	int:


       '''simple docstring'''

       lowercase       : List[Any]						=load_image(UpperCAmelCase		)
       lowercase       : Optional[Any]						=self.image_processor(images=UpperCAmelCase  ,   return_tensors=self.framework		)
       return model_inputs






      def 					A__   (			self      :		Union[str, Any]  ,   UpperCAmelCase      :		Optional[Any]		)	->	Any:


       '''simple docstring'''

       lowercase       : str						=self.model(**UpperCAmelCase		)
       return model_outputs






      def 					A__   (			self      :		int  ,   UpperCAmelCase      :		Optional[Any]  ,   UpperCAmelCase      :		Any=5		)	->	str:


       '''simple docstring'''

       if top_k > self.model.config.num_labels:
        lowercase       : Any						=self.model.config.num_labels

       if self.framework == "pt":
        lowercase       : Dict						=model_outputs.logits.softmax(-1		)[0]
        lowercase	,		lowercase       : Dict						=probs.topk(UpperCAmelCase		)
       elif self.framework == "tf":
        lowercase       : Tuple						=stable_softmax(model_outputs.logits  ,   axis=-1		)[0]
        lowercase       : Dict						=tf.math.top_k(UpperCAmelCase  ,   k=UpperCAmelCase		)
        lowercase	,		lowercase       : Any						=topk.values.numpy(), topk.indices.numpy()
       else:
        raise ValueError(f'Unsupported framework: {self.framework}'		)

       lowercase       : str						=scores.tolist()
       lowercase       : Dict						=ids.tolist()
       return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(UpperCAmelCase  ,   UpperCAmelCase		)]









'''simple docstring'''
import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class   __UpperCAmelCase				(     lowerCAmelCase			,unittest.TestCase				):



					'''simple docstring'''





					_UpperCamelCase							=		CTRLTokenizer
					_UpperCamelCase							=		False
					_UpperCamelCase							=		False



					def     __snake_case						(	self     :						str)    ->							List[Any]:
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								A_									= ['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
								A_									= dict(zip(_lowercase      ,       range(len(_lowercase))))
								A_									= ['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
								A_									= {'unk_token': '<unk>'}

								A_									= os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES['vocab_file'])
								A_									= os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES['merges_file'])
								with open(self.vocab_file      ,       'w'      ,       encoding='utf-8') as fp:
											fp.write(json.dumps(_lowercase) + '\n')
								with open(self.merges_file      ,       'w'      ,       encoding='utf-8') as fp:
											fp.write('\n'.join(_lowercase))



					def     __snake_case						(	self     :						Optional[int]      ,       **_lowercase     :						Optional[int])    ->							Union[str, Any]:
								kwargs.update(self.special_tokens_map)
								return CTRLTokenizer.from_pretrained(self.tmpdirname      ,       **_lowercase)



					def     __snake_case						(	self     :						List[Any]      ,       _lowercase     :						Union[str, Any])    ->							Dict:
								A_									= 'adapt react readapt apt'
								A_									= 'adapt react readapt apt'
								return input_text, output_text



					def     __snake_case						(	self     :						Any)    ->							Any:
								A_									= CTRLTokenizer(self.vocab_file      ,       self.merges_file      ,       **self.special_tokens_map)
								A_									= 'adapt react readapt apt'
								A_									= 'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
								A_									= tokenizer.tokenize(_lowercase)
								self.assertListEqual(_lowercase      ,       _lowercase)

								A_									= tokens + [tokenizer.unk_token]

								A_									= [0, 1, 2, 4, 5, 1, 0, 3, 6]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase)      ,       _lowercase)




