






"""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


_UpperCamelCase						:    Optional[int]		=						-1 if torch_device == 'cpu' else 0

@is_pipeline_test
class 			a	(  unittest.TestCase      ):
    UpperCAmelCase_					:	str      	=MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
    UpperCAmelCase_					:	int      	=TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase				,						_lowerCamelCase			):
      lowercase				       =			SummarizationPipeline(model=_lowerCamelCase				,						tokenizer=_lowerCamelCase			)
      return summarizer, ["(CNN)The Palestinian Authority officially became", "Some other text"]







    def      UpperCamelCase_ (     self				,						_lowerCamelCase				,						_lowerCamelCase			):
      lowercase				       =			summarizer.model

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

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

      # Some models (Switch Transformers, LED, T5, LongT5, etc) can handle long sequences.
      lowercase				       =			[
          '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(_lowerCamelCase				,						_lowerCamelCase			)
            and get_gpu_count() > 0
            and len(summarizer.model.trainable_weights			) > 0
        ):
          with self.assertRaises(_lowerCamelCase			):
            lowercase				       =			summarizer('This ' * 1_0_0_0			)
      lowercase				       =			summarizer('This ' * 1_0_0_0				,						truncation=TruncationStrategy.ONLY_FIRST			)







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







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







    @require_torch
    @slow
    def      UpperCamelCase_ (     self			):
      lowercase				       =			pipeline(task='summarization'				,						device=_lowerCamelCase			)
      lowercase				       =			(
          ' (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.'
      )
      lowercase				       =			(
          ' 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 .'
      )
      lowercase				       =			summarizer(_lowerCamelCase			)
      self.assertEqual(result[0]['summary_text']				,						_lowerCamelCase			)










"""simple docstring"""



import argparse
import collections
from pathlib import Path

import torch
from torch.serialization import default_restore_location

from transformers import BertConfig, DPRConfig, DPRContextEncoder, DPRQuestionEncoder, DPRReader


_UpperCamelCase						:    Optional[Any]		=						collections.namedtuple(
    'CheckpointState', ['model_dict', 'optimizer_dict', 'scheduler_dict', 'offset', 'epoch', 'encoder_params']
)
def 		_SCREAMING_SNAKE_CASE					(       __snake_case     :    str       ):





  '''simple docstring'''





  print(f'Reading saved model from {model_file}'       )
  lowercase				       =			torch.load(__snake_case						,   map_location=lambda __snake_case						,   __snake_case       : default_restore_location(__snake_case						,   'cpu'       )       )
  return CheckpointState(**__snake_case       )

class 			a	:







    def __init__(     self				,						_lowerCamelCase			):
      lowercase				       =			src_file







    def      UpperCamelCase_ (     self			):
      raise NotImplementedError







    @staticmethod
    def      UpperCamelCase_ (     _lowerCamelCase				,						*_lowerCamelCase				,						**_lowerCamelCase			):
      if comp_type.startswith('c'			):
        return DPRContextEncoderState(*_lowerCamelCase				,						**_lowerCamelCase			)
      if comp_type.startswith('q'			):
        return DPRQuestionEncoderState(*_lowerCamelCase				,						**_lowerCamelCase			)
      if comp_type.startswith('r'			):
        return DPRReaderState(*_lowerCamelCase				,						**_lowerCamelCase			)
      else:
        raise ValueError('Component type must be either \'ctx_encoder\', \'question_encoder\' or \'reader\'.'			)


class 			a	(  a_      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			DPRContextEncoder(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased'			)[0]			)			)
      print(F'Loading DPR biencoder from {self.src_file}'			)
      lowercase				       =			load_states_from_checkpoint(self.src_file			)
      lowercase       ,	lowercase				       =			model.ctx_encoder, 'ctx_model.'
      # Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
      lowercase				       =			{'bert_model.embeddings.position_ids': model.ctx_encoder.bert_model.embeddings.position_ids}
      for key, value in saved_state.model_dict.items():
        if key.startswith(_lowerCamelCase			):
          lowercase				       =			key[len(_lowerCamelCase			) :]
          if not key.startswith('encode_proj.'			):
            lowercase				       =			'bert_model.' + key
          lowercase				       =			value
      encoder.load_state_dict(_lowerCamelCase			)
      return model


class 			a	(  a_      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			DPRQuestionEncoder(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased'			)[0]			)			)
      print(F'Loading DPR biencoder from {self.src_file}'			)
      lowercase				       =			load_states_from_checkpoint(self.src_file			)
      lowercase       ,	lowercase				       =			model.question_encoder, 'question_model.'
      # Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
      lowercase				       =			{'bert_model.embeddings.position_ids': model.question_encoder.bert_model.embeddings.position_ids}
      for key, value in saved_state.model_dict.items():
        if key.startswith(_lowerCamelCase			):
          lowercase				       =			key[len(_lowerCamelCase			) :]
          if not key.startswith('encode_proj.'			):
            lowercase				       =			'bert_model.' + key
          lowercase				       =			value
      encoder.load_state_dict(_lowerCamelCase			)
      return model


class 			a	(  a_      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			DPRReader(DPRConfig(**BertConfig.get_config_dict('bert-base-uncased'			)[0]			)			)
      print(F'Loading DPR reader from {self.src_file}'			)
      lowercase				       =			load_states_from_checkpoint(self.src_file			)
      # Fix changes from https://github.com/huggingface/transformers/commit/614fef1691edb806de976756d4948ecbcd0c0ca3
      lowercase				       =			{
          'encoder.bert_model.embeddings.position_ids': model.span_predictor.encoder.bert_model.embeddings.position_ids
      }
      for key, value in saved_state.model_dict.items():
        if key.startswith('encoder.'			) and not key.startswith('encoder.encode_proj'			):
          lowercase				       =			'encoder.bert_model.' + key[len('encoder.'			) :]
        lowercase				       =			value
      model.span_predictor.load_state_dict(_lowerCamelCase			)
      return model


def 		_SCREAMING_SNAKE_CASE					(       __snake_case     :    str						,   __snake_case     :    Path						,   __snake_case     :    Path       ):





  '''simple docstring'''





  lowercase				       =			Path(__snake_case       )
  dest_dir.mkdir(exist_ok=__snake_case       )

  lowercase				       =			DPRState.from_type(__snake_case						,   src_file=__snake_case       )
  lowercase				       =			dpr_state.load_dpr_model()
  model.save_pretrained(__snake_case       )
  model.from_pretrained(__snake_case       )  # sanity check


if __name__ == "__main__":
    _UpperCamelCase						:    Optional[int]		=						argparse.ArgumentParser()
    # Required parameters
    parser.add_argument(
        '--type', type=str, help='Type of the component to convert: \'ctx_encoder\', \'question_encoder\' or \'reader\'.'
    )
    parser.add_argument(
        '--src',
        type=str,
        help=(
            'Path to the dpr checkpoint file. They can be downloaded from the official DPR repo'
            ' https://github.com/facebookresearch/DPR. Note that in the official repo, both encoders are stored in the'
            ' \'retriever\' checkpoints.'
        ),
    )
    parser.add_argument('--dest', type=str, default=None, help='Path to the output PyTorch model directory.')
    _UpperCamelCase						:    List[Any]		=						parser.parse_args()

    _UpperCamelCase						:    int		=						Path(args.src)
    _UpperCamelCase						:    List[Any]		=						F'''converted-{src_file.name}''' if args.dest is None else args.dest
    _UpperCamelCase						:    Optional[Any]		=						Path(dest_dir)
    assert src_file.exists()
    assert (
        args.type is not None
    ), "Please specify the component type of the DPR model to convert: 'ctx_encoder', 'question_encoder' or 'reader'."
    convert(args.type, src_file, dest_dir)


