
import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin

class __snake_case		(      lowerCAmelCase					,	unittest.TestCase     ):
    _a		:						Optional[int]=				ProphetNetTokenizer
    _a		:						str=				False
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           super().setUp()

           lowercase							:     Optional[int]       	=      [
               """[UNK]""",
               """[CLS]""",
               """[SEP]""",
               """[PAD]""",
               """[MASK]""",
               """want""",
               """##want""",
               """##ed""",
               """wa""",
               """un""",
               """runn""",
               """##ing""",
               """,""",
               """low""",
               """lowest""",
           ]
           lowercase							:     Union[str, Any]       	=      os.path.join(self.tmpdirname		,VOCAB_FILES_NAMES["""vocab_file"""]      )
           with open(self.vocab_file		,"""w"""		,encoding="""utf-8"""      ) as vocab_writer:
                  vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]      )      )
    def       _SCREAMING_SNAKE_CASE       (  self		,snake_case      ):



           '''simple docstring'''







           lowercase							:     int       	=      """UNwant\u00E9d,running"""
           lowercase							:     Dict       	=      """unwanted, running"""
           return input_text, output_text
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     List[Any]       	=      self.tokenizer_class(self.vocab_file      )

           lowercase							:     List[Any]       	=      tokenizer.tokenize("""UNwant\u00E9d,running"""      )
           self.assertListEqual(snake_case		,["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]      )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case      )		,[9, 6, 7, 12, 10, 11]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Dict       	=      BasicTokenizer()

           self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz"""      )		,["""ah""", """\u535A""", """\u63A8""", """zz"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[Any]       	=      BasicTokenizer(do_lower_case=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """      )		,["""hello""", """!""", """how""", """are""", """you""", """?"""]      )
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""      )		,["""hello"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Dict       	=      BasicTokenizer(do_lower_case=snake_case		,strip_accents=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """      )		,["""hällo""", """!""", """how""", """are""", """you""", """?"""]      )
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""      )		,["""h\u00E9llo"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     List[str]       	=      BasicTokenizer(do_lower_case=snake_case		,strip_accents=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """      )		,["""hallo""", """!""", """how""", """are""", """you""", """?"""]      )
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""      )		,["""hello"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     List[str]       	=      BasicTokenizer(do_lower_case=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """      )		,["""hallo""", """!""", """how""", """are""", """you""", """?"""]      )
           self.assertListEqual(tokenizer.tokenize("""H\u00E9llo"""      )		,["""hello"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     int       	=      BasicTokenizer(do_lower_case=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """      )		,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Tuple       	=      BasicTokenizer(do_lower_case=snake_case		,strip_accents=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """      )		,["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     str       	=      BasicTokenizer(do_lower_case=snake_case		,strip_accents=snake_case      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """      )		,["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     str       	=      BasicTokenizer(do_lower_case=snake_case		,never_split=["""[UNK]"""]      )

           self.assertListEqual(
               tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]"""      )		,["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""]      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

           lowercase							:     Optional[Any]       	=      {}
           for i, token in enumerate(snake_case      ):
                  lowercase							:     Union[str, Any]       	=      i
           lowercase							:     List[str]       	=      WordpieceTokenizer(vocab=snake_case		,unk_token="""[UNK]"""      )

           self.assertListEqual(tokenizer.tokenize(""""""      )		,[]      )

           self.assertListEqual(tokenizer.tokenize("""unwanted running"""      )		,["""un""", """##want""", """##ed""", """runn""", """##ing"""]      )

           self.assertListEqual(tokenizer.tokenize("""unwantedX running"""      )		,["""[UNK]""", """runn""", """##ing"""]      )
    @require_torch
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased"""      )

           lowercase							:     Tuple       	=      ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
           lowercase							:     Union[str, Any]       	=      [1037, 2146, 20423, 2005, 7680, 7849, 3989, 1012, 102]
           lowercase							:     Optional[Any]       	=      tokenizer(snake_case		,padding=snake_case		,return_tensors="""pt"""      )
           self.assertIsInstance(snake_case		,snake_case      )
           lowercase							:     Optional[int]       	=      list(batch.input_ids.numpy()[0]      )
           self.assertListEqual(snake_case		,snake_case      )

           self.assertEqual((2, 9)		,batch.input_ids.shape      )
           self.assertEqual((2, 9)		,batch.attention_mask.shape      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           self.assertTrue(_is_whitespace(""" """      )      )
           self.assertTrue(_is_whitespace("""\t"""      )      )
           self.assertTrue(_is_whitespace("""\r"""      )      )
           self.assertTrue(_is_whitespace("""\n"""      )      )
           self.assertTrue(_is_whitespace("""\u00A0"""      )      )

           self.assertFalse(_is_whitespace("""A"""      )      )
           self.assertFalse(_is_whitespace("""-"""      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           self.assertTrue(_is_control("""\u0005"""      )      )

           self.assertFalse(_is_control("""A"""      )      )
           self.assertFalse(_is_control(""" """      )      )
           self.assertFalse(_is_control("""\t"""      )      )
           self.assertFalse(_is_control("""\r"""      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           self.assertTrue(_is_punctuation("""-"""      )      )
           self.assertTrue(_is_punctuation("""$"""      )      )
           self.assertTrue(_is_punctuation("""`"""      )      )
           self.assertTrue(_is_punctuation("""."""      )      )

           self.assertFalse(_is_punctuation("""A"""      )      )
           self.assertFalse(_is_punctuation(""" """      )      )
    @slow
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[int]       	=      self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased"""      )

           lowercase							:     List[Any]       	=      tokenizer.encode("""sequence builders"""		,add_special_tokens=snake_case      )
           lowercase							:     Optional[int]       	=      tokenizer.encode("""multi-sequence build"""		,add_special_tokens=snake_case      )

           lowercase							:     Optional[Any]       	=      tokenizer.build_inputs_with_special_tokens(snake_case      )
           lowercase							:     Tuple       	=      tokenizer.build_inputs_with_special_tokens(snake_case		,snake_case      )

           assert encoded_sentence == text + [102]
           assert encoded_pair == text + [102] + text_a + [102]


import os

import numpy
import onnx







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       lowercase							:     int       	=      a.name
       lowercase							:     Any       	=      b.name

       lowercase							:     Optional[Any]       	=      """"""
       lowercase							:     Dict       	=      """"""

       lowercase							:     int       	=      a == b

       lowercase							:     int       	=      name_a
       lowercase							:     List[str]       	=      name_b

       return res







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    str:
       for i, input_name in enumerate(node_proto.input				):
              if input_name == name:
                     node_proto.input.insert(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
                     node_proto.input.pop(i + 1				)

       if node_proto.op_type == "If":
              _graph_replace_input_with(node_proto.attribute[0].g					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
              _graph_replace_input_with(node_proto.attribute[1].g					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       if node_proto.op_type == "Loop":
              _graph_replace_input_with(node_proto.attribute[0].g					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       for n in graph_proto.node:
              _node_replace_input_with(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[Any]:
       lowercase							:     Any       	=      list(model.graph.initializer				)
       lowercase							:     Dict       	=      list(model_without_ext.graph.initializer				)
       for i, ref_i in ind_to_replace:
              assert inits_with_data[i].name == inits[i].name
              assert inits_with_data[ref_i].name == inits[ref_i].name
              assert i > ref_i

              lowercase							:     Union[str, Any]       	=      inits[i].name
              lowercase							:     Dict       	=      inits[ref_i].name

              model_without_ext.graph.initializer.remove(inits[i]				)

              # for n in model.graph.node:
              _graph_replace_input_with(model_without_ext.graph					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    List[str]:
       lowercase							:     Union[str, Any]       	=      os.path.dirname(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Dict       	=      os.path.basename(SCREAMING_SNAKE_CASE__				)

       lowercase							:     str       	=      onnx.load(os.path.join(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)				)

       lowercase							:     List[str]       	=      list(model.graph.initializer				)

       lowercase							:     Tuple       	=      set()
       lowercase							:     int       	=      {}
       lowercase							:     Optional[Any]       	=      []

       lowercase							:     Dict       	=      0

       for i in range(len(SCREAMING_SNAKE_CASE__				)				):
              if i in dup_set:
                     continue

              for j in range(i + 1					,	len(SCREAMING_SNAKE_CASE__				)				):
                     if j in dup_set:
                            continue
                     if _is_equal_tensor_proto(inits[i]					,	inits[j]				):
                            dup_set.add(SCREAMING_SNAKE_CASE__				)
                            dup_set.add(SCREAMING_SNAKE_CASE__				)

                            lowercase							:     int       	=      inits[j].data_type
                            lowercase							:     Optional[int]       	=      numpy.prod(inits[j].dims				)
                            if dtype == 1:
                                   mem_size *= 4
                            elif dtype == 6:
                                   mem_size *= 4
                            elif dtype == 7 or dtype == 11:
                                   mem_size *= 8
                            else:
                                   print("""unexpected data type: """					,	SCREAMING_SNAKE_CASE__				)
                            total_reduced_size += mem_size

                            lowercase							:     Tuple       	=      inits[i].name
                            lowercase							:     int       	=      inits[j].name

                            if name_i in dup_map:
                                   dup_map[name_i].append(SCREAMING_SNAKE_CASE__				)
                            else:
                                   lowercase							:     List[str]       	=      [name_j]
                            ind_to_replace.append((j, i)				)

       print("""total reduced size: """					,	total_reduced_size / 1_024 / 1_024 / 1_024					,	"""GB"""				)

       lowercase							:     str       	=      sorted(SCREAMING_SNAKE_CASE__				)
       _remove_dup_initializers_from_model(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       lowercase							:     Optional[Any]       	=      """optimized_""" + model_file_name
       lowercase							:     Dict       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       onnx.save(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       return new_model
