


"""simple docstring"""





import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union

import numpy as np

from ...utils import is_tf_available, is_torch_available, logging


if TYPE_CHECKING:
   if is_torch_available():
      import torch
   if is_tf_available():
      import tensorflow as tf

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_codegen import CodeGenTokenizer


__UpperCAmelCase     					=   logging.get_logger(__name__)

__UpperCAmelCase     					=   {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__UpperCAmelCase     					=   {
    "vocab_file": {
        "Salesforce/codegen-350M-mono": "https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/vocab.json",
    },
    "merges_file": {
        "Salesforce/codegen-350M-mono": "https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "Salesforce/codegen-350M-mono": (
            "https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/tokenizer.json"
        ),
    },
}

__UpperCAmelCase     					=   {
    "Salesforce/codegen-350M-mono": 2_048,
}

class 			lowercase_	(			a_    ):
      __magic_name__  :				List[str] 							=					VOCAB_FILES_NAMES
      __magic_name__  :				Any 							=					PRETRAINED_VOCAB_FILES_MAP
      __magic_name__  :				int 							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __magic_name__  :				Union[str, Any] 							=					['input_ids', 'attention_mask']
      __magic_name__  :				List[str] 							=					CodeGenTokenizer







      def __init__(   self			:				Union[str, Any]		,	_lowercase			:				str=None		,	_lowercase			:				Tuple=None		,	_lowercase			:				Any=None		,	_lowercase			:				List[Any]="<|endoftext|>"		,	_lowercase			:				int="<|endoftext|>"		,	_lowercase			:				Union[str, Any]="<|endoftext|>"		,	_lowercase			:				Dict=False		,	**_lowercase			:				str		,	):
        super().__init__(
            _lowercase		,	_lowercase		,	tokenizer_file=_lowercase		,	unk_token=_lowercase		,	bos_token=_lowercase		,	eos_token=_lowercase		,	add_prefix_space=_lowercase		,	**_lowercase		,	)

        if kwargs.pop("add_bos_token"		,	_lowercase     ):
          lowerCAmelCase__     :     Any										=       kwargs.pop("name_or_path"		,	""     )
          raise ValueError(
              "Currenty GPT2\'s fast tokenizer does NOT support adding a BOS token."
              "Instead you should use GPT2\'s slow tokenizer class `CodeGenTokenizer` as follows: \n"
              f"`CodeGenTokenizer.from_pretrained('{model_id}')`\nor\n"
              f"`AutoTokenizer.from_pretrained('{model_id}', use_fast=False)`\n"
              "This issue will be fixed soon, see: https://github.com/huggingface/tokenizers/pull/1005."
              " so that the fast tokenizer works correctly."     )

        lowerCAmelCase__     :     int										=       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
        if pre_tok_state.get("add_prefix_space"		,	_lowercase     ) != add_prefix_space:
          lowerCAmelCase__     :     int										=       getattr(_lowercase		,	pre_tok_state.pop("type"     )     )
          lowerCAmelCase__     :     int										=       add_prefix_space
          lowerCAmelCase__     :     Optional[Any]										=       pre_tok_class(**_lowercase     )

        lowerCAmelCase__     :     Union[str, Any]										=       add_prefix_space







      def 					_lowerCAmelCase							(   self			:				Any		,	*_lowercase			:				int		,	**_lowercase			:				Optional[Any]     ):
        lowerCAmelCase__     :     Any										=       kwargs.get("is_split_into_words"		,	_lowercase     )
        assert self.add_prefix_space or not is_split_into_words, (
            f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
            "to use it with pretokenized inputs."
        )

        return super()._batch_encode_plus(*_lowercase		,	**_lowercase     )







      def 					_lowerCAmelCase							(   self			:				Union[str, Any]		,	*_lowercase			:				Union[str, Any]		,	**_lowercase			:				Union[str, Any]     ):
        lowerCAmelCase__     :     Any										=       kwargs.get("is_split_into_words"		,	_lowercase     )

        assert self.add_prefix_space or not is_split_into_words, (
            f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
            "to use it with pretokenized inputs."
        )

        return super()._encode_plus(*_lowercase		,	**_lowercase     )







      def 					_lowerCAmelCase							(   self			:				Dict		,	_lowercase			:				Union[str, Any]		,	_lowercase			:				Union[str, Any] = None     ):
        lowerCAmelCase__     :     str										=       self._tokenizer.model.save(_lowercase		,	name=_lowercase     )
        return tuple(_lowercase     )







      def 					_lowerCAmelCase							(   self			:				Optional[int]		,	_lowercase			:				Optional[int]		,	_lowercase			:				Optional[int] = False		,	_lowercase			:				Union[str, Any] = None		,	_lowercase			:				Union[str, Any] = None		,	**_lowercase			:				int		,	):
        lowerCAmelCase__     :     Union[str, Any]										=       super().decode(
            token_ids=_lowercase		,	skip_special_tokens=_lowercase		,	clean_up_tokenization_spaces=_lowercase		,	**_lowercase		,	)

        if truncate_before_pattern is not None and len(_lowercase     ) > 0:
          lowerCAmelCase__     :     Union[str, Any]										=       self.truncate(_lowercase		,	_lowercase     )

        return decoded_text







      def 					_lowerCAmelCase							(   self			:				str		,	_lowercase			:				List[Any]		,	_lowercase			:				Optional[int]     ):
        def find_re(_lowercase			:				Union[str, Any]		,	_lowercase			:				Union[str, Any]		,	_lowercase			:				List[str]     ):
          lowerCAmelCase__     :     int										=       pattern.search(_lowercase		,	_lowercase     )
          return m.start() if m else -1

        lowerCAmelCase__     :     Optional[int]										=       [re.compile(_lowercase		,	re.MULTILINE     ) for pattern in truncate_before_pattern]

        lowerCAmelCase__     :     Optional[int]										=       list(re.finditer("^print"		,	_lowercase		,	re.MULTILINE     )     )

        if len(_lowercase     ) > 1:
          lowerCAmelCase__     :     str										=       completion[: prints[1].start()]

        lowerCAmelCase__     :     Any										=       list(re.finditer("^def"		,	_lowercase		,	re.MULTILINE     )     )

        if len(_lowercase     ) > 1:
          lowerCAmelCase__     :     Any										=       completion[: defs[1].start()]

        lowerCAmelCase__     :     int										=       0

        lowerCAmelCase__     :     Tuple										=       [
            pos for pos in [find_re(_lowercase		,	_lowercase		,	_lowercase     ) for terminal in terminals] if pos != -1
        ]

        if len(_lowercase     ) > 0:
          return completion[: min(_lowercase     )]
        else:
          return completion


"""simple docstring"""


def  lowercase						(	lowerCAmelCase__						):
			lowerCamelCase_					=  generate_pascal_triangle(lowerCAmelCase__						)
			for row_idx in range(lowerCAmelCase__						):
						# Print left spaces
						for _ in range(num_rows - row_idx - 1						):
									print(end=''' '''						)
						# Print row values
						for col_idx in range(row_idx + 1						):
									if col_idx != row_idx:
												print(triangle[row_idx][col_idx]	,end=''' '''						)
									else:
												print(triangle[row_idx][col_idx]	,end=''''''						)
						print()






def  lowercase						(	lowerCAmelCase__						):

			if not isinstance(lowerCAmelCase__	,lowerCAmelCase__						):
						raise TypeError('''The input value of \'num_rows\' should be \'int\''''						)

			if num_rows == 0:
						return []
			elif num_rows < 0:
						raise ValueError(
						    '''The input value of \'num_rows\' should be greater than or equal to 0'''						)

			lowerCamelCase_					=  []
			for current_row_idx in range(lowerCAmelCase__						):
						lowerCamelCase_					=  populate_current_row(lowerCAmelCase__	,lowerCAmelCase__						)
						triangle.append(lowerCAmelCase__						)
			return triangle






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__						):
			lowerCamelCase_					=  [-1] * (current_row_idx + 1)
			# first and last elements of current row are equal to 1
			lowerCamelCase_		, lowerCamelCase_					=  1, 1
			for current_col_idx in range(1	,lowerCAmelCase__						):
						calculate_current_element(
						    lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__						)
			return current_row






def  lowercase						(	lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,lowerCAmelCase__	,):
			lowerCamelCase_					=  triangle[current_row_idx - 1][current_col_idx - 1]
			lowerCamelCase_					=  triangle[current_row_idx - 1][current_col_idx]
			lowerCamelCase_					=  above_to_left_elt + above_to_right_elt






def  lowercase						(	lowerCAmelCase__						):

			if not isinstance(lowerCAmelCase__	,lowerCAmelCase__						):
						raise TypeError('''The input value of \'num_rows\' should be \'int\''''						)

			if num_rows == 0:
						return []
			elif num_rows < 0:
						raise ValueError(
						    '''The input value of \'num_rows\' should be greater than or equal to 0'''						)

			lowerCamelCase_					=  [[1]]

			for row_index in range(1	,lowerCAmelCase__						):
						lowerCamelCase_					=  [0] + result[-1] + [0]
						lowerCamelCase_					=  row_index + 1
						# Calculate the number of distinct elements in a row
						lowerCamelCase_					=  sum(divmod(lowerCAmelCase__	,2						)						)
						lowerCamelCase_					=  [
						    temp_row[i - 1] + temp_row[i] for i in range(1	,distinct_elements + 1						)
						]
						lowerCamelCase_					=  row_first_half[: (row_index + 1) // 2]
						row_second_half.reverse()
						lowerCamelCase_					=  row_first_half + row_second_half
						result.append(lowerCAmelCase__						)

			return result






def  lowercase						(	):
			from collections.abc import Callable
			from timeit import timeit

			def benchmark_a_function(lowerCAmelCase__	,lowerCAmelCase__						) -> None:
						lowerCamelCase_					=  f"{func.__name__}({value})"
						lowerCamelCase_					=  timeit(f"__main__.{call}"	,setup='''import __main__'''						)
						# print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
						print(f"{call:38} -- {timing:.4f} seconds"						)

			for value in range(15						):  # (1, 7, 14):
						for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
									benchmark_a_function(lowerCAmelCase__	,lowerCAmelCase__						)
						print()


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						benchmark()



