


import os

import numpy
import onnx







def   __lowerCAmelCase						(						lowercase  :  Any						,							lowercase  :  List[Any]			)     ->						Union[str, Any]:


    """simple docstring"""





    snake_case   :				Any				 =   a.name
    snake_case   :				List[Any]				 =   b.name

    snake_case   :				Union[str, Any]				 =   ""
    snake_case   :				Optional[int]				 =   ""

    snake_case   :				Optional[Any]				 =   a == b

    snake_case   :				Union[str, Any]				 =   name_a
    snake_case   :				List[Any]				 =   name_b

    return res







def   __lowerCAmelCase						(						lowercase  :  Optional[int]						,							lowercase  :  Tuple						,							lowercase  :  Dict			)     ->						Dict:


    """simple docstring"""





    for i, input_name in enumerate(node_proto.input			):
        if input_name == name:
            node_proto.input.insert(lowercase						,							lowercase			)
            node_proto.input.pop(i + 1			)

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







def   __lowerCAmelCase						(						lowercase  :  List[str]						,							lowercase  :  Optional[Any]						,							lowercase  :  int			)     ->						List[str]:


    """simple docstring"""





    for n in graph_proto.node:
        _node_replace_input_with(lowercase						,							lowercase						,							lowercase			)







def   __lowerCAmelCase						(						lowercase  :  List[Any]						,							lowercase  :  Union[str, Any]						,							lowercase  :  Any			)     ->						Optional[Any]:


    """simple docstring"""





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

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







def   __lowerCAmelCase						(						lowercase  :  Any			)     ->						Dict:


    """simple docstring"""





    snake_case   :				Optional[int]				 =   os.path.dirname(lowercase			)
    snake_case   :				Tuple				 =   os.path.basename(lowercase			)

    snake_case   :				List[str]				 =   onnx.load(os.path.join(lowercase						,							lowercase			)			)

    snake_case   :				List[Any]				 =   list(model.graph.initializer			)

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

    snake_case   :				Union[str, Any]				 =   0

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

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

                snake_case   :				Union[str, Any]				 =   inits[j].data_type
                snake_case   :				List[Any]				 =   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: "						,							lowercase			)
                total_reduced_size += mem_size

                snake_case   :				int				 =   inits[i].name
                snake_case   :				List[str]				 =   inits[j].name

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

    print("total reduced size: "						,							total_reduced_size / 1024 / 1024 / 1024						,							"GB"			)

    snake_case   :				int				 =   sorted(lowercase			)
    _remove_dup_initializers_from_model(lowercase						,							lowercase						,							lowercase			)

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

    return new_model









"""simple docstring"""



import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class _lowerCAmelCase    (				snake_case_   ,							unittest.TestCase     ):
   __UpperCAmelCase			:	List[Any]							  =  MgpstrTokenizer
   __UpperCAmelCase			:	Optional[int]							  =  False
   __UpperCAmelCase			:	Optional[int]							  =  {}
   __UpperCAmelCase			:	List[str]							  =  False







   def 			lowerCamelCase		(     self						)     ->		int:

       '''simple docstring'''




       super().setUp()

       # fmt: off
       snake_case   :				List[str]				 =   ["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
       # fmt: on
       snake_case   :				Union[str, Any]				 =   dict(zip(UpperCamelCase__						,     range(len(UpperCamelCase__						)						)						)						)

       snake_case   :				int				 =   os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES["vocab_file"]						)
       with open(self.vocab_file						,     "w"						,     encoding="utf-8"						) as fp:
           fp.write(json.dumps(UpperCamelCase__						) + "\n"						)







   def 			lowerCamelCase		(     self						,     **UpperCamelCase__						)     ->		List[str]:

       '''simple docstring'''




       return MgpstrTokenizer.from_pretrained(self.tmpdirname						,     **UpperCamelCase__						)







   def 			lowerCamelCase		(     self						,     UpperCamelCase__						)     ->		List[Any]:

       '''simple docstring'''




       snake_case   :				int				 =   "tester"
       snake_case   :				List[str]				 =   "tester"
       return input_text, output_text







   @unittest.skip("MGP-STR always lower cases letters."						)
   def 			lowerCamelCase		(     self						)     ->		str:

       '''simple docstring'''




       pass







   def 			lowerCamelCase		(     self						)     ->		Tuple:

       '''simple docstring'''




       snake_case   :				int				 =   self.get_tokenizers(do_lower_case=UpperCamelCase__						)
       for tokenizer in tokenizers:
           with self.subTest(F'{tokenizer.__class__.__name__}'						):
               snake_case   :				List[Any]				 =   "[SPECIAL_TOKEN]"

               tokenizer.add_special_tokens({"cls_token": special_token}						)
               snake_case   :				str				 =   tokenizer.encode([special_token]						,     add_special_tokens=UpperCamelCase__						)
               self.assertEqual(len(UpperCamelCase__						)						,     1						)

               snake_case   :				List[Any]				 =   tokenizer.decode(UpperCamelCase__						,     skip_special_tokens=UpperCamelCase__						)
               self.assertTrue(special_token not in decoded						)







   def 			lowerCamelCase		(     self						)     ->		List[Any]:

       '''simple docstring'''




       snake_case   :				List[str]				 =   self.get_tokenizers()
       for tokenizer in tokenizers:
           with self.subTest(F'{tokenizer.__class__.__name__}'						):
               snake_case ,snake_case   :				Union[str, Any]				 =   self.get_input_output_texts(UpperCamelCase__						)

               snake_case   :				Dict				 =   tokenizer.tokenize(UpperCamelCase__						)
               snake_case   :				Tuple				 =   tokenizer.convert_tokens_to_ids(UpperCamelCase__						)
               snake_case   :				List[Any]				 =   tokenizer.encode(UpperCamelCase__						,     add_special_tokens=UpperCamelCase__						)
               self.assertListEqual(UpperCamelCase__						,     UpperCamelCase__						)

               snake_case   :				Dict				 =   tokenizer.convert_ids_to_tokens(UpperCamelCase__						)
               self.assertNotEqual(len(UpperCamelCase__						)						,     0						)
               snake_case   :				Tuple				 =   tokenizer.decode(UpperCamelCase__						)
               self.assertIsInstance(UpperCamelCase__						,     UpperCamelCase__						)

               self.assertEqual(text_a.replace(" "						,     ""						)						,     UpperCamelCase__						)







   @unittest.skip("MGP-STR tokenizer only handles one sequence."						)
   def 			lowerCamelCase		(     self						)     ->		List[Any]:

       '''simple docstring'''




       pass







   @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"						)
   def 			lowerCamelCase		(     self						)     ->		Tuple:

       '''simple docstring'''




       pass





