




"""simple docstring"""


import argparse
import logging
from collections import namedtuple

import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer  # The authors' implementation

from transformers import BertTokenizer


logging.basicConfig(level=logging.INFO)
_A													=      logging.getLogger(__name__)


_A													=      """Hello world! cécé herlolip"""


_A													=      namedtuple(
    """BertAbsConfig""",
    [
        """temp_dir""",
        """large""",
        """use_bert_emb""",
        """finetune_bert""",
        """encoder""",
        """share_emb""",
        """max_pos""",
        """enc_layers""",
        """enc_hidden_size""",
        """enc_heads""",
        """enc_ff_size""",
        """enc_dropout""",
        """dec_layers""",
        """dec_hidden_size""",
        """dec_heads""",
        """dec_ff_size""",
        """dec_dropout""",
    ],
)



def 	lowercase_				(			__UpperCAmelCase    ,		__UpperCAmelCase				)						->    int:
      lowerCAmelCase__      :			Tuple   =	BertAbsConfig(
          temp_dir="""."""    ,		finetune_bert=__UpperCAmelCase    ,		large=__UpperCAmelCase    ,		share_emb=__UpperCAmelCase    ,		use_bert_emb=__UpperCAmelCase    ,		encoder="""bert"""    ,		max_pos=512    ,		enc_layers=6    ,		enc_hidden_size=512    ,		enc_heads=8    ,		enc_ff_size=512    ,		enc_dropout=0.2    ,		dec_layers=6    ,		dec_hidden_size=768    ,		dec_heads=8    ,		dec_ff_size=2048    ,		dec_dropout=0.2    ,		)
      lowerCAmelCase__      :			int   =	torch.load(__UpperCAmelCase    ,		lambda __UpperCAmelCase    ,		__UpperCAmelCase				: storage				)
      lowerCAmelCase__      :			List[str]   =	AbsSummarizer(__UpperCAmelCase    ,		torch.device("""cpu"""				)    ,		__UpperCAmelCase				)
      original.eval()

      lowerCAmelCase__      :			Any   =	BertAbsSummarizer(__UpperCAmelCase    ,		torch.device("""cpu"""				)				)
      new_model.eval()

      # -------------------
      # Convert the weights
      # -------------------

      logging.info("""convert the model"""				)
      new_model.bert.load_state_dict(original.bert.state_dict()				)
      new_model.decoder.load_state_dict(original.decoder.state_dict()				)
      new_model.generator.load_state_dict(original.generator.state_dict()				)

      # ----------------------------------
      # Make sure the outpus are identical
      # ----------------------------------

      logging.info("""Make sure that the models' outputs are identical"""				)
      lowerCAmelCase__      :			Any   =	BertTokenizer.from_pretrained("""bert-base-uncased"""				)

      # prepare the model inputs
      lowerCAmelCase__      :			List[Any]   =	tokenizer.encode("""This is sample éàalj'-."""				)
      encoder_input_ids.extend([tokenizer.pad_token_id] * (512 - len(__UpperCAmelCase				))				)
      lowerCAmelCase__      :			Any   =	torch.tensor(__UpperCAmelCase				).unsqueeze(0				)
      lowerCAmelCase__      :			Union[str, Any]   =	tokenizer.encode("""This is sample 3 éàalj'-."""				)
      decoder_input_ids.extend([tokenizer.pad_token_id] * (512 - len(__UpperCAmelCase				))				)
      lowerCAmelCase__      :			Dict   =	torch.tensor(__UpperCAmelCase				).unsqueeze(0				)

      # failsafe to make sure the weights reset does not affect the
      # loaded weights.
      assert torch.max(torch.abs(original.generator[0].weight - new_model.generator[0].weight				)				) == 0

      # forward pass
      lowerCAmelCase__      :			Optional[Any]   =	encoder_input_ids
      lowerCAmelCase__      :			str   =	decoder_input_ids
      lowerCAmelCase__      :			Any   =	None
      lowerCAmelCase__      :			Optional[Any]   =	None
      lowerCAmelCase__      :			Tuple   =	None
      lowerCAmelCase__      :			int   =	None
      lowerCAmelCase__      :			Any   =	None

      # The original model does not apply the geneator layer immediatly but rather in
      # the beam search (where it combines softmax + linear layer). Since we already
      # apply the softmax in our generation process we only apply the linear layer here.
      # We make sure that the outputs of the full stack are identical
      lowerCAmelCase__      :			Any   =	original(__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase				)[0]
      lowerCAmelCase__      :			Any   =	original.generator(__UpperCAmelCase				)

      lowerCAmelCase__      :			List[str]   =	new_model(
          __UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase				)[0]
      lowerCAmelCase__      :			Optional[int]   =	new_model.generator(__UpperCAmelCase				)

      lowerCAmelCase__      :			List[str]   =	torch.max(torch.abs(output_converted_model - output_original_model				)				).item()
      print("""Maximum absolute difference beween weights: {:.2f}""".format(__UpperCAmelCase				)				)
      lowerCAmelCase__      :			List[Any]   =	torch.max(torch.abs(output_converted_generator - output_original_generator				)				).item()
      print("""Maximum absolute difference beween weights: {:.2f}""".format(__UpperCAmelCase				)				)

      lowerCAmelCase__      :			str   =	torch.allclose(__UpperCAmelCase    ,		__UpperCAmelCase    ,		atol=1E-3				)
      if are_identical:
            logging.info("""all weights are equal up to 1e-3"""				)
      else:
            raise ValueError("""the weights are different. The new model is likely different from the original one."""				)

      # The model has been saved with torch.save(model) and this is bound to the exact
      # directory structure. We save the state_dict instead.
      logging.info("""saving the model's state dictionary"""				)
      torch.save(
          new_model.state_dict()    ,		"""./bertabs-finetuned-cnndm-extractive-abstractive-summarization/pytorch_model.bin"""				)


if __name__ == "__main__":
  _A													=      argparse.ArgumentParser()
  parser.add_argument(
      """--bertabs_checkpoint_path""",
      default=None,
      type=str,
      required=True,
      help="""Path the official PyTorch dump.""",
  )
  parser.add_argument(
      """--pytorch_dump_folder_path""",
      default=None,
      type=str,
      required=True,
      help="""Path to the output PyTorch model.""",
  )
  _A													=      parser.parse_args()

  convert_bertabs_checkpoints(
      args.bertabs_checkpoint_path,
      args.pytorch_dump_folder_path,
  )











"""simple docstring"""


import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)


class _lowerCamelCase    (					unittest.TestCase						):






   def 	_lowerCAmelCase   (		self       :		Dict   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Vector([1, 2, 3]   )
         self.assertEqual(x.component(0   )   ,     1   )
         self.assertEqual(x.component(2   )   ,     3   )
         lowerCAmelCase__      :			Union[str, Any]   =	Vector()






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	Vector([0, 0, 0, 0, 0, 1]   )
         self.assertEqual(str(UpperCamelCase   )   ,     """(0,0,0,0,0,1)"""   )






   def 	_lowerCAmelCase   (		self       :		Any   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			List[Any]   =	Vector([1, 2, 3, 4]   )
         self.assertEqual(len(UpperCamelCase   )   ,     4   )






   def 	_lowerCAmelCase   (		self       :		List[str]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	Vector([1, 2]   )
         lowerCAmelCase__      :			Optional[int]   =	Vector([1, 2, 3, 4, 5]   )
         lowerCAmelCase__      :			Union[str, Any]   =	Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   )
         lowerCAmelCase__      :			List[Any]   =	Vector([1, -1, 1, -1, 2, -3, 4, -5]   )
         self.assertAlmostEqual(x.euclidean_length()   ,     2.236   ,     3   )
         self.assertAlmostEqual(y.euclidean_length()   ,     7.416   ,     3   )
         self.assertEqual(z.euclidean_length()   ,     0   )
         self.assertAlmostEqual(w.euclidean_length()   ,     7.616   ,     3   )






   def 	_lowerCAmelCase   (		self       :		Any   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			int   =	Vector([1, 2, 3]   )
         lowerCAmelCase__      :			Optional[Any]   =	Vector([1, 1, 1]   )
         self.assertEqual((x + y).component(0   )   ,     2   )
         self.assertEqual((x + y).component(1   )   ,     3   )
         self.assertEqual((x + y).component(2   )   ,     4   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Union[str, Any]   =	Vector([1, 2, 3]   )
         lowerCAmelCase__      :			Dict   =	Vector([1, 1, 1]   )
         self.assertEqual((x - y).component(0   )   ,     0   )
         self.assertEqual((x - y).component(1   )   ,     1   )
         self.assertEqual((x - y).component(2   )   ,     2   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Any   =	Vector([1, 2, 3]   )
         lowerCAmelCase__      :			Any   =	Vector([2, -1, 4]   )  # for test of dot product
         lowerCAmelCase__      :			Any   =	Vector([1, -2, -1]   )
         self.assertEqual(str(x * 3.0   )   ,     """(3.0,6.0,9.0)"""   )
         self.assertEqual((a * b)   ,     0   )






   def 	_lowerCAmelCase   (		self       :		int   )			->						None:

         """simple docstring"""
         self.assertEqual(str(zero_vector(10   )   ).count("""0"""   )   ,     10   )






   def 	_lowerCAmelCase   (		self       :		Tuple   )			->						None:

         """simple docstring"""
         self.assertEqual(str(unit_basis_vector(3   ,     1   )   )   ,     """(0,1,0)"""   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Vector([1, 2, 3]   )
         lowerCAmelCase__      :			Optional[Any]   =	Vector([1, 0, 1]   )
         self.assertEqual(str(axpy(2   ,     UpperCamelCase   ,     UpperCamelCase   )   )   ,     """(3,4,7)"""   )






   def 	_lowerCAmelCase   (		self       :		Optional[int]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Vector([1, 0, 0, 0, 0, 0]   )
         lowerCAmelCase__      :			Any   =	x.copy()
         self.assertEqual(str(UpperCamelCase   )   ,     str(UpperCamelCase   )   )






   def 	_lowerCAmelCase   (		self       :		Optional[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Vector([1, 0, 0]   )
         x.change_component(0   ,     0   )
         x.change_component(1   ,     1   )
         self.assertEqual(str(UpperCamelCase   )   ,     """(0,1,0)"""   )






   def 	_lowerCAmelCase   (		self       :		int   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[int]   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         self.assertEqual("""|1,2,3|\n|2,4,5|\n|6,7,8|\n"""   ,     str(UpperCamelCase   )   )






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         lowerCAmelCase__      :			Dict   =	[[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
         for x in range(a.height()   ):
               for y in range(a.width()   ):
                     self.assertEqual(minors[x][y]   ,     a.minor(UpperCamelCase   ,     UpperCamelCase   )   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			str   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         lowerCAmelCase__      :			int   =	[[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
         for x in range(a.height()   ):
               for y in range(a.width()   ):
                     self.assertEqual(cofactors[x][y]   ,     a.cofactor(UpperCamelCase   ,     UpperCamelCase   )   )






   def 	_lowerCAmelCase   (		self       :		int   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Union[str, Any]   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         self.assertEqual(-5   ,     a.determinant()   )






   def 	_lowerCAmelCase   (		self       :		int   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]   ,     3   ,     3   )
         lowerCAmelCase__      :			Tuple   =	Vector([1, 2, 3]   )
         self.assertEqual("""(14,32,50)"""   ,     str(a * x   )   )
         self.assertEqual("""|2,4,6|\n|8,10,12|\n|14,16,18|\n"""   ,     str(a * 2   )   )






   def 	_lowerCAmelCase   (		self       :		str   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         a.change_component(0   ,     2   ,     5   )
         self.assertEqual("""|1,2,5|\n|2,4,5|\n|6,7,8|\n"""   ,     str(UpperCamelCase   )   )






   def 	_lowerCAmelCase   (		self       :		Tuple   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         self.assertEqual(7   ,     a.component(2   ,     1   )   ,     0.01   )






   def 	_lowerCAmelCase   (		self       :		Any   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Tuple   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         lowerCAmelCase__      :			List[Any]   =	Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]   ,     3   ,     3   )
         self.assertEqual("""|2,4,10|\n|4,8,10|\n|12,14,18|\n"""   ,     str(a + b   )   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   )			->						None:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]   ,     3   ,     3   )
         lowerCAmelCase__      :			Dict   =	Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]   ,     3   ,     3   )
         self.assertEqual("""|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"""   ,     str(a - b   )   )






   def 	_lowerCAmelCase   (		self       :		Union[str, Any]   )			->						None:

         """simple docstring"""
         self.assertEqual(
             """|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"""   ,     str(square_zero_matrix(5   )   )   ,     )


if __name__ == "__main__":
  unittest.main()





