

import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING

import numpy as np
import pyarrow as pa

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


if TYPE_CHECKING:
						import tensorflow as tf

class 					__UpperCamelCase					(       TensorFormatter[Mapping, "tf.Tensor", Mapping]      ):







	def __init__( self:			Dict	,			__UpperCamelCase:			Optional[Any]=None	,			**__UpperCamelCase:			int   ):

						'''simple docstring'''





						super().__init__(features=snake_case_   )
						__magic_name__				=     tf_tensor_kwargs
						import tensorflow as tf  # noqa: import tf at initialization







	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple	,			__UpperCamelCase:			List[str]   ):

						'''simple docstring'''





						import tensorflow as tf

						if isinstance(snake_case_	,			snake_case_   ) and column:
											if all(
											    isinstance(snake_case_	,			tf.Tensor   ) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column   ):
																return tf.stack(snake_case_   )
											elif all(
											    isinstance(snake_case_	,			(tf.Tensor, tf.RaggedTensor)   ) and x.ndim == 1 and x.dtype == column[0].dtype
											    for x in column   ):
																# only rag 1-D tensors, otherwise some dimensions become ragged even though they were consolidated
																return tf.ragged.stack(snake_case_   )

						return column







	def 						_SCREAMING_SNAKE_CASE				( self:			List[Any]	,			__UpperCamelCase:			List[Any]   ):

						'''simple docstring'''





						import tensorflow as tf

						if value is None:
											return value

						__magic_name__				=     {}

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

											if isinstance(snake_case_	,			PIL.Image.Image   ):
																__magic_name__				=     np.asarray(snake_case_   )

						return tf.convert_to_tensor(snake_case_	,			**{**default_dtype, **self.tf_tensor_kwargs}   )







	def 						_SCREAMING_SNAKE_CASE				( self:			Union[str, Any]	,			__UpperCamelCase:			Dict   ):

						'''simple docstring'''





						import tensorflow as tf

						# support for torch, tf, jax etc.
						if config.TORCH_AVAILABLE and "torch" in sys.modules:
											import torch

											if isinstance(snake_case_	,			torch.Tensor   ):
																return self._tensorize(data_struct.detach().cpu().numpy()[()]   )
						if hasattr(snake_case_	,			'__array__'   ) and not isinstance(snake_case_	,			tf.Tensor   ):
											__magic_name__				=     data_struct.__array__()
						# support for nested types like struct of list of struct
						if isinstance(snake_case_	,			np.ndarray   ):
											if data_struct.dtype == object:  # tf tensors cannot be instantied from an array of objects
																return self._consolidate([self.recursive_tensorize(snake_case_   ) for substruct in data_struct]   )
						elif isinstance(snake_case_	,			(list, tuple)   ):
											return self._consolidate([self.recursive_tensorize(snake_case_   ) for substruct in data_struct]   )
						return self._tensorize(snake_case_   )







	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[int]	,			__UpperCamelCase:			Union[str, Any]   ):

						'''simple docstring'''





						return map_nested(self._recursive_tensorize	,			snake_case_	,			map_list=snake_case_   )







	def 						_SCREAMING_SNAKE_CASE				( self:			Any	,			__UpperCamelCase:			List[Any]   ):

						'''simple docstring'''





						__magic_name__				=     self.numpy_arrow_extractor().extract_row(snake_case_   )
						__magic_name__				=     self.python_features_decoder.decode_row(snake_case_   )
						return self.recursive_tensorize(snake_case_   )







	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[Any]	,			__UpperCamelCase:			Optional[Any]   ):

						'''simple docstring'''





						__magic_name__				=     self.numpy_arrow_extractor().extract_column(snake_case_   )
						__magic_name__				=     self.python_features_decoder.decode_column(snake_case_	,			pa_table.column_names[0]   )
						__magic_name__				=     self.recursive_tensorize(snake_case_   )
						__magic_name__				=     self._consolidate(snake_case_   )
						return column







	def 						_SCREAMING_SNAKE_CASE				( self:			Optional[int]	,			__UpperCamelCase:			Dict   ):

						'''simple docstring'''





						__magic_name__				=     self.numpy_arrow_extractor().extract_batch(snake_case_   )
						__magic_name__				=     self.python_features_decoder.decode_batch(snake_case_   )
						__magic_name__				=     self.recursive_tensorize(snake_case_   )
						for column_name in batch:
											__magic_name__				=     self._consolidate(batch[column_name]   )
						return batch






"""simple docstring"""
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


_a   :      List[Any]       =				-1 if torch_device == """cpu""" else 0






@is_pipeline_test
class   _UpperCAmelCase					(       unittest.TestCase):
    __lowercase				:			List[str]	=       MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    __lowercase				:			str	=       TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    def        lowerCamelCase__						(     self    ,     snake_case_    ,     snake_case_    ,     snake_case_  ):
      _snake_case  :    int            = SummarizationPipeline(model=snake_case_    ,     tokenizer=snake_case_  )
      return summarizer, ["(CNN)The Palestinian Authority officially became", "Some other text"]
    def        lowerCamelCase__						(     self    ,     snake_case_    ,     snake_case_  ):
      _snake_case  :    str            = summarizer.model

      _snake_case  :    Optional[int]            = summarizer("(CNN)The Palestinian Authority officially became"  )
      self.assertEqual(snake_case_    ,     [{"summary_text": ANY(snake_case_  )}]  )

      _snake_case  :    List[str]            = summarizer(
          "(CNN)The Palestinian Authority officially became "    ,     num_beams=2    ,     min_length=2    ,     max_length=5    ,     )
      self.assertEqual(snake_case_    ,     [{"summary_text": ANY(snake_case_  )}]  )

      # Some models (Switch Transformers, LED, T5, LongT5, etc) can handle long sequences.
      _snake_case  :    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(snake_case_    ,     snake_case_  )
            and get_gpu_count() > 0
            and len(summarizer.model.trainable_weights  ) > 0
        ):
          with self.assertRaises(snake_case_  ):
            _snake_case  :    Tuple            = summarizer("This " * 10_00  )
      _snake_case  :    Any            = summarizer("This " * 10_00    ,     truncation=TruncationStrategy.ONLY_FIRST  )
    @require_torch
    def        lowerCamelCase__						(     self  ):
      _snake_case  :    List[Any]            = pipeline(task="summarization"    ,     model="sshleifer/tiny-mbart"    ,     framework="pt"  )
      _snake_case  :    List[Any]            = summarizer("This is a small test"  )
      self.assertEqual(
          snake_case_    ,     [
              {
                  "summary_text": "เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป"
              }
          ]    ,     )
    @require_tf
    def        lowerCamelCase__						(     self  ):
      _snake_case  :    Dict            = pipeline(task="summarization"    ,     model="sshleifer/tiny-mbart"    ,     framework="tf"  )
      _snake_case  :    Union[str, Any]            = summarizer("This is a small test"  )
      self.assertEqual(
          snake_case_    ,     [
              {
                  "summary_text": "เข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไปเข้าไป"
              }
          ]    ,     )


    @require_torch
    @slow
    def        lowerCamelCase__						(     self  ):
      _snake_case  :    Tuple            = pipeline(task="summarization"    ,     device=snake_case_  )
      _snake_case  :    Any            = (
          " (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."
      )
      _snake_case  :    int            = (
          " 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 ."
      )
      _snake_case  :    Union[str, Any]            = summarizer(snake_case_  )
      self.assertEqual(result[0]["summary_text"]    ,     snake_case_  )

