

import unittest

from transformers import (
    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
    SummarizationPipeline,
    TFPreTrainedModel,
    pipeline,
)
from transformers.testing_utils import get_gpu_count, is_pipeline_test, require_tf, require_torch, slow, torch_device
from transformers.tokenization_utils import TruncationStrategy

from .test_pipelines_common import ANY


_SCREAMING_SNAKE_CASE							 =			-1 if torch_device == '''cpu''' else 0


@is_pipeline_test
class      lowerCamelCase_ (			unittest.TestCase):
 _lowerCAmelCase									=	MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
 _lowerCAmelCase									=	TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING




 def     a       (			self  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase							):
   __UpperCAmelCase	:  int		=     SummarizationPipeline(model=_UpperCAmelCase  ,  tokenizer=_UpperCAmelCase							)
   return summarizer, ["(CNN)The Palestinian Authority officially became", "Some other text"]




 def     a       (			self  ,  _UpperCAmelCase  ,  _UpperCAmelCase							):
   __UpperCAmelCase	:  Dict		=     summarizer.model

   __UpperCAmelCase	:  Dict		=     summarizer('(CNN)The Palestinian Authority officially became'							)
   self.assertEqual(_UpperCAmelCase  ,  [{'summary_text': ANY(_UpperCAmelCase							)}]							)

   __UpperCAmelCase	:  Tuple		=     summarizer(
       '(CNN)The Palestinian Authority officially became '  ,  num_beams=2  ,  min_length=2  ,  max_length=5  ,  )
   self.assertEqual(_UpperCAmelCase  ,  [{'summary_text': ANY(_UpperCAmelCase							)}]							)

   # Some models (Switch Transformers, LED, T5, LongT5, etc) can handle long sequences.
   __UpperCAmelCase	:  Tuple		=     [
       'SwitchTransformersConfig',
       'T5Config',
       'LongT5Config',
       'LEDConfig',
       'PegasusXConfig',
       'FSMTConfig',
       'M2M100Config',
       'ProphetNetConfig',  # positional embeddings up to a fixed maximum size (otherwise clamping the values)
   ]
   if model.config.__class__.__name__ not in model_can_handle_longer_seq:
     # Too long and exception is expected.
     # For TF models, if the weights are initialized in GPU context, we won't get expected index error from
     # the embedding layer.
     if not (
         isinstance(_UpperCAmelCase  ,  _UpperCAmelCase							)
         and get_gpu_count() > 0
         and len(summarizer.model.trainable_weights							) > 0
     ):
       with self.assertRaises(_UpperCAmelCase							):
         __UpperCAmelCase	:  str		=     summarizer('This ' * 1_000							)
   __UpperCAmelCase	:  List[Any]		=     summarizer('This ' * 1_000  ,  truncation=TruncationStrategy.ONLY_FIRST							)




 @require_torch
 def     a       (			self							):
   __UpperCAmelCase	:  List[str]		=     pipeline(task='summarization'  ,  model='sshleifer/tiny-mbart'  ,  framework='pt'							)
   __UpperCAmelCase	:  List[Any]		=     summarizer('This is a small test'							)
   self.assertEqual(
       _UpperCAmelCase  ,  [
           {
               'summary_text': 'เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป'
           }
       ]  ,  )




 @require_tf
 def     a       (			self							):
   __UpperCAmelCase	:  Optional[int]		=     pipeline(task='summarization'  ,  model='sshleifer/tiny-mbart'  ,  framework='tf'							)
   __UpperCAmelCase	:  Any		=     summarizer('This is a small test'							)
   self.assertEqual(
       _UpperCAmelCase  ,  [
           {
               'summary_text': 'เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป'
           }
       ]  ,  )




 @require_torch
 @slow
 def     a       (			self							):
   __UpperCAmelCase	:  List[Any]		=     pipeline(task='summarization'  ,  device=_UpperCAmelCase							)
   __UpperCAmelCase	:  int		=     (
       ' (CNN)The Palestinian Authority officially became the 123rd member of the International Criminal Court on'
       ' Wednesday, a step that gives the court jurisdiction over alleged crimes in Palestinian territories. The'
       ' formal accession was marked with a ceremony at The Hague, in the Netherlands, where the court is based.'
       ' The Palestinians signed the ICC\'s founding Rome Statute in January, when they also accepted its'
       ' jurisdiction over alleged crimes committed "in the occupied Palestinian territory, including East'
       ' Jerusalem, since June 13, 2014." Later that month, the ICC opened a preliminary examination into the'
       ' situation in Palestinian territories, paving the way for possible war crimes investigations against'
       ' Israelis. As members of the court, Palestinians may be subject to counter-charges as well. Israel and'
       ' the United States, neither of which is an ICC member, opposed the Palestinians\' efforts to join the'
       ' body. But Palestinian Foreign Minister Riad al-Malki, speaking at Wednesday\'s ceremony, said it was a'
       ' move toward greater justice. "As Palestine formally becomes a State Party to the Rome Statute today, the'
       ' world is also a step closer to ending a long era of impunity and injustice," he said, according to an'
       ' ICC news release. "Indeed, today brings us closer to our shared goals of justice and peace." Judge'
       ' Kuniko Ozaki, a vice president of the ICC, said acceding to the treaty was just the first step for the'
       ' Palestinians. "As the Rome Statute today enters into force for the State of Palestine, Palestine'
       ' acquires all the rights as well as responsibilities that come with being a State Party to the Statute.'
       ' These are substantive commitments, which cannot be taken lightly," she said. Rights group Human Rights'
       ' Watch welcomed the development. "Governments seeking to penalize Palestine for joining the ICC should'
       ' immediately end their pressure, and countries that support universal acceptance of the court\'s treaty'
       ' should speak out to welcome its membership," said Balkees Jarrah, international justice counsel for the'
       ' group. \"What\'s objectionable is the attempts to undermine international justice, not Palestine\'s'
       ' decision to join a treaty to which over 100 countries around the world are members." In January, when'
       ' the preliminary ICC examination was opened, Israeli Prime Minister Benjamin Netanyahu described it as an'
       ' outrage, saying the court was overstepping its boundaries. The United States also said it "strongly"'
       ' disagreed with the court\'s decision. \"As we have said repeatedly, we do not believe that Palestine is a'
       ' state and therefore we do not believe that it is eligible to join the ICC," the State Department said in'
       ' a statement. It urged the warring sides to resolve their differences through direct negotiations. "We'
       ' will continue to oppose actions against Israel at the ICC as counterproductive to the cause of peace,"'
       ' it said. But the ICC begs to differ with the definition of a state for its purposes and refers to the'
       ' territories as "Palestine." While a preliminary examination is not a formal investigation, it allows the'
       ' court to review evidence and determine whether to investigate suspects on both sides. Prosecutor Fatou'
       ' Bensouda said her office would "conduct its analysis in full independence and impartiality." The war'
       ' between Israel and Hamas militants in Gaza last summer left more than 2,000 people dead. The inquiry'
       ' will include alleged war crimes committed since June. The International Criminal Court was set up in'
       ' 2002 to prosecute genocide, crimes against humanity and war crimes. CNN\'s Vasco Cotovio, Kareem Khadder'
       ' and Faith Karimi contributed to this report.'
   )
   __UpperCAmelCase	:  List[Any]		=     (
       ' The Palestinian Authority becomes the 123rd member of the International Criminal Court . The move gives'
       ' the court jurisdiction over alleged crimes in Palestinian territories . Israel and the United States'
       ' opposed the Palestinians\' efforts to join the court . Rights group Human Rights Watch welcomes the move,'
       ' says governments seeking to penalize Palestine should end pressure .'
   )
   __UpperCAmelCase	:  List[Any]		=     summarizer(_UpperCAmelCase							)
   self.assertEqual(result[0]['summary_text']  ,  _UpperCAmelCase							)








import sys
from collections.abc import Mapping

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter






class     __magic_name__     (							TensorFormatter[Mapping, np.ndarray, Mapping]     ):


 def __init__(    self		:			Optional[int]      ,    lowerCAmelCase__		:			str=None      ,    **lowerCAmelCase__		:			int     )     ->   Optional[Any]:
   super().__init__(features=lowerCAmelCase__     )
   UpperCAmelCase          =	np_array_kwargs


 def _UpperCamelCase						(    self		:			Any      ,    lowerCAmelCase__		:			Dict     )     ->   Union[str, Any]:
   if isinstance(lowerCAmelCase__      ,    lowerCAmelCase__     ):
     if column and all(
         isinstance(lowerCAmelCase__      ,    np.ndarray     ) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column     ):
       return np.stack(lowerCAmelCase__     )
     else:
       # don't use np.array(column, dtype=object)
       # since it fails in certain cases
       # see https://stackoverflow.com/q/51005699
       UpperCAmelCase          =	np.empty(len(lowerCAmelCase__     )      ,    dtype=lowerCAmelCase__     )
       UpperCAmelCase          =	column
       return out
   return column


 def _UpperCamelCase						(    self		:			Optional[Any]      ,    lowerCAmelCase__		:			Union[str, Any]     )     ->   List[Any]:
   if isinstance(lowerCAmelCase__      ,    (str, bytes, type(lowerCAmelCase__     ))     ):
     return value
   elif isinstance(lowerCAmelCase__      ,    (np.character, np.ndarray)     ) and np.issubdtype(value.dtype      ,    np.character     ):
     return value
   elif isinstance(lowerCAmelCase__      ,    np.number     ):
     return value

   UpperCAmelCase          =	{}

   if isinstance(lowerCAmelCase__      ,    np.ndarray     ) and np.issubdtype(value.dtype      ,    np.integer     ):
     UpperCAmelCase          =	{"dtype": np.intaa}
   elif isinstance(lowerCAmelCase__      ,    np.ndarray     ) and np.issubdtype(value.dtype      ,    np.floating     ):
     UpperCAmelCase          =	{"dtype": np.floataa}
   elif config.PIL_AVAILABLE and "PIL" in sys.modules:
     import PIL.Image

     if isinstance(lowerCAmelCase__      ,    PIL.Image.Image     ):
       return np.asarray(lowerCAmelCase__      ,    **self.np_array_kwargs     )

   return np.asarray(lowerCAmelCase__      ,    **{**default_dtype, **self.np_array_kwargs}     )


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			str     )     ->   Optional[int]:
   # support for torch, tf, jax etc.
   if config.TORCH_AVAILABLE and "torch" in sys.modules:
     import torch

     if isinstance(lowerCAmelCase__      ,    torch.Tensor     ):
       return self._tensorize(data_struct.detach().cpu().numpy()[()]     )
   if hasattr(lowerCAmelCase__      ,    "__array__"     ) and not isinstance(lowerCAmelCase__      ,    (np.ndarray, np.character, np.number)     ):
     UpperCAmelCase          =	data_struct.__array__()
   # support for nested types like struct of list of struct
   if isinstance(lowerCAmelCase__      ,    np.ndarray     ):
     if data_struct.dtype == object:
       return self._consolidate([self.recursive_tensorize(lowerCAmelCase__     ) for substruct in data_struct]     )
   if isinstance(lowerCAmelCase__      ,    (list, tuple)     ):
     return self._consolidate([self.recursive_tensorize(lowerCAmelCase__     ) for substruct in data_struct]     )
   return self._tensorize(lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			Union[str, Any]      ,    lowerCAmelCase__		:			dict     )     ->   Union[str, Any]:
   return map_nested(self._recursive_tensorize      ,    lowerCAmelCase__      ,    map_list=lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			int      ,    lowerCAmelCase__		:			pa.Table     )     ->   Mapping:
   UpperCAmelCase          =	self.numpy_arrow_extractor().extract_row(lowerCAmelCase__     )
   UpperCAmelCase          =	self.python_features_decoder.decode_row(lowerCAmelCase__     )
   return self.recursive_tensorize(lowerCAmelCase__     )


 def _UpperCamelCase						(    self		:			List[str]      ,    lowerCAmelCase__		:			pa.Table     )     ->   np.ndarray:
   UpperCAmelCase          =	self.numpy_arrow_extractor().extract_column(lowerCAmelCase__     )
   UpperCAmelCase          =	self.python_features_decoder.decode_column(lowerCAmelCase__      ,    pa_table.column_names[0]     )
   UpperCAmelCase          =	self.recursive_tensorize(lowerCAmelCase__     )
   UpperCAmelCase          =	self._consolidate(lowerCAmelCase__     )
   return column


 def _UpperCamelCase						(    self		:			List[Any]      ,    lowerCAmelCase__		:			pa.Table     )     ->   Mapping:
   UpperCAmelCase          =	self.numpy_arrow_extractor().extract_batch(lowerCAmelCase__     )
   UpperCAmelCase          =	self.python_features_decoder.decode_batch(lowerCAmelCase__     )
   UpperCAmelCase          =	self.recursive_tensorize(lowerCAmelCase__     )
   for column_name in batch:
     UpperCAmelCase          =	self._consolidate(batch[column_name]     )
   return batch



