
from __future__ import annotations

from typing import TypedDict

class __snake_case		(      lowerCAmelCase     ):
    _a		:						str
    _a		:						int







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    list[str]:
       if not isinstance(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				):
              raise TypeError("""The parameter s type must be str."""				)

       return [s[i:] + s[:i] for i in range(len(SCREAMING_SNAKE_CASE__				)				)]







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    BWTTransformDict:
       if not isinstance(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				):
              raise TypeError("""The parameter s type must be str."""				)
       if not s:
              raise ValueError("""The parameter s must not be empty."""				)

       lowercase							:     List[Any]       	=      all_rotations(SCREAMING_SNAKE_CASE__				)
       rotations.sort()  # sort the list of rotations in alphabetically order
       # make a string composed of the last char of each rotation
       lowercase							:     BWTTransformDict       	=      {
           "bwt_string": "".join([word[-1] for word in rotations]				),
           "idx_original_string": rotations.index(SCREAMING_SNAKE_CASE__				),
       }
       return response







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    str:
       if not isinstance(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				):
              raise TypeError("""The parameter bwt_string type must be str."""				)
       if not bwt_string:
              raise ValueError("""The parameter bwt_string must not be empty."""				)
       try:
              lowercase							:     List[str]       	=      int(SCREAMING_SNAKE_CASE__				)
       except ValueError:
              raise TypeError(
                  """The parameter idx_original_string type must be int or passive"""
                  """ of cast to int."""				)
       if idx_original_string < 0:
              raise ValueError("""The parameter idx_original_string must not be lower than 0."""				)
       if idx_original_string >= len(SCREAMING_SNAKE_CASE__				):
              raise ValueError(
                  """The parameter idx_original_string must be lower than""" """ len(bwt_string)."""				)

       lowercase							:     str       	=      [""""""] * len(SCREAMING_SNAKE_CASE__				)
       for _ in range(len(SCREAMING_SNAKE_CASE__				)				):
              for i in range(len(SCREAMING_SNAKE_CASE__				)				):
                     lowercase							:     List[str]       	=      bwt_string[i] + ordered_rotations[i]
              ordered_rotations.sort()
       return ordered_rotations[idx_original_string]


if __name__ == "__main__":
  lowercase  :					List[Any]						    =							"""Provide a string that I will generate its BWT transform: """
  lowercase  :					int						    =							input(entry_msg).strip()
  lowercase  :					List[Any]						    =							bwt_transform(s)
  print(
      F'''Burrows Wheeler transform for string \'{s}\' results '''
      F'''in \'{result["bwt_string"]}\''''
  )
  lowercase  :					Optional[Any]						    =							reverse_bwt(result["""bwt_string"""], result["""idx_original_string"""])
  print(
      F'''Reversing Burrows Wheeler transform for entry \'{result["bwt_string"]}\' '''
      F'''we get original string \'{original_string}\''''
  )


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
