
import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_A       =					"src/transformers"

# Matches is_xxx_available()
_A       =					re.compile(R"is\_([a-z_]*)_available()")
# Matches from xxx import bla
_A       =					re.compile(R"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")
_A       =					re.compile(R"^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)")


_A       =					"\n{0} = None\n"

_A       =					"\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"


_A       =					"\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"






def        lowerCamelCase__    (    __lowerCAmelCase  :  Optional[Any]    ):




			"""simple docstring"""


			if _re_test_backend.search(__lowerCAmelCase    ) is None:
						return None
			lowerCAmelCase_      =     [b[0] for b in _re_backend.findall(__lowerCAmelCase    )]
			backends.sort()
			return "_and_".join(__lowerCAmelCase    )






def        lowerCamelCase__    (    ):




			"""simple docstring"""


			with open(os.path.join(__lowerCAmelCase   ,							"__init__.py"    )   ,							"r"   ,							encoding="utf-8"   ,							newline="\n"    ) as f:
						lowerCAmelCase_      =     f.readlines()

			# Get to the point we do the actual imports for type checking
			lowerCAmelCase_      =     0
			while not lines[line_index].startswith("if TYPE_CHECKING"    ):
						line_index += 1

			lowerCAmelCase_      =     {}
			# Go through the end of the file
			while line_index < len(__lowerCAmelCase    ):
						# If the line is an if is_backend_available, we grab all objects associated.
						lowerCAmelCase_      =     find_backend(lines[line_index]    )
						if backend is not None:
									while not lines[line_index].startswith("    else:"    ):
												line_index += 1
									line_index += 1

									lowerCAmelCase_      =     []
									# Until we unindent, add backend objects to the list
									while len(lines[line_index]    ) <= 1 or lines[line_index].startswith(" " * 8    ):
												lowerCAmelCase_      =     lines[line_index]
												lowerCAmelCase_      =     _re_single_line_import.search(__lowerCAmelCase    )
												if single_line_import_search is not None:
															objects.extend(single_line_import_search.groups()[0].split(", "    )    )
												elif line.startswith(" " * 12    ):
															objects.append(line[12:-2]    )
												line_index += 1

									lowerCAmelCase_      =     objects
						else:
									line_index += 1

			return backend_specific_objects






def        lowerCamelCase__    (    __lowerCAmelCase  :  List[Any]   ,							__lowerCAmelCase  :  Optional[Any]    ):




			"""simple docstring"""


			if name.isupper():
						return DUMMY_CONSTANT.format(__lowerCAmelCase    )
			elif name.islower():
						return DUMMY_FUNCTION.format(__lowerCAmelCase   ,							__lowerCAmelCase    )
			else:
						return DUMMY_CLASS.format(__lowerCAmelCase   ,							__lowerCAmelCase    )






def        lowerCamelCase__    (    __lowerCAmelCase  :  Any=None    ):




			"""simple docstring"""


			if backend_specific_objects is None:
						lowerCAmelCase_      =     read_init()
			# For special correspondence backend to module name as used in the function requires_modulename
			lowerCAmelCase_      =     {}

			for backend, objects in backend_specific_objects.items():
						lowerCAmelCase_      =     "[" + ", ".join(F"""\"{b}\"""" for b in backend.split("_and_"    )    ) + "]"
						lowerCAmelCase_      =     "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
						dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
						dummy_file += "\n".join([create_dummy_object(__lowerCAmelCase   ,							__lowerCAmelCase    ) for o in objects]    )
						lowerCAmelCase_      =     dummy_file

			return dummy_files






def        lowerCamelCase__    (    __lowerCAmelCase  :  List[str]=False    ):




			"""simple docstring"""


			lowerCAmelCase_      =     create_dummy_files()
			# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
			lowerCAmelCase_      =     {"torch": "pt"}

			# Locate actual dummy modules and read their content.
			lowerCAmelCase_      =     os.path.join(__lowerCAmelCase   ,							"utils"    )
			lowerCAmelCase_      =     {
			    backend: os.path.join(__lowerCAmelCase   ,							F"""dummy_{short_names.get(__lowerCAmelCase   ,							__lowerCAmelCase    )}_objects.py"""    )
			    for backend in dummy_files.keys()
			}

			lowerCAmelCase_      =     {}
			for backend, file_path in dummy_file_paths.items():
						if os.path.isfile(__lowerCAmelCase    ):
									with open(__lowerCAmelCase   ,							"r"   ,							encoding="utf-8"   ,							newline="\n"    ) as f:
												lowerCAmelCase_      =     f.read()
						else:
									lowerCAmelCase_      =     ""

			for backend in dummy_files.keys():
						if dummy_files[backend] != actual_dummies[backend]:
									if overwrite:
												print(
												    F"""Updating transformers.utils.dummy_{short_names.get(__lowerCAmelCase   ,							__lowerCAmelCase    )}_objects.py as the main """
												    "__init__ has new objects."    )
												with open(dummy_file_paths[backend]   ,							"w"   ,							encoding="utf-8"   ,							newline="\n"    ) as f:
															f.write(dummy_files[backend]    )
									else:
												raise ValueError(
												    "The main __init__ has objects that are not present in "
												    F"""transformers.utils.dummy_{short_names.get(__lowerCAmelCase   ,							__lowerCAmelCase    )}_objects.py. Run `make fix-copies` """
												    "to fix this."    )


if __name__ == "__main__":
			_A       =					argparse.ArgumentParser()
			parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
			_A       =					parser.parse_args()

			check_dummies(args.fix_and_overwrite)





# This Python program implements an optimal binary search tree (abbreviated BST)
# building dynamic programming algorithm that delivers O(n^2) performance.
#
# The goal of the optimal BST problem is to build a low-cost BST for a
# given set of nodes, each with its own key and frequency. The frequency
# of the node is defined as how many time the node is being searched.
# The search cost of binary search tree is given by this formula:
#
# cost(1, n) = sum{i = 1 to n}((depth(node_i) + 1) * node_i_freq)
#
# where n is number of nodes in the BST. The characteristic of low-cost
# BSTs is having a faster overall search time than other implementations.
# The reason for their fast search time is that the nodes with high
# frequencies will be placed near the root of the tree while the nodes
# with low frequencies will be placed near the leaves of the tree thus
# reducing search time in the most frequent instances.
import sys
from random import randint





class      _lowerCAmelCase :




				def __init__( self    ,    _UpperCamelCase    ,    _UpperCamelCase					)    ->				str:
							lowerCAmelCase_      =     key
							lowerCAmelCase_      =     freq




				def __str__( self					)    ->				Any:
							return f"""Node(key={self.key}, freq={self.freq})"""






def        lowerCamelCase__    (    __lowerCAmelCase  :  Optional[int]   ,							__lowerCAmelCase  :  Dict   ,							__lowerCAmelCase  :  Optional[Any]   ,							__lowerCAmelCase  :  Optional[int]   ,							__lowerCAmelCase  :  int   ,							__lowerCAmelCase  :  List[Any]    ):




			"""simple docstring"""


			if i > j or i < 0 or j > len(__lowerCAmelCase    ) - 1:
						return

			lowerCAmelCase_      =     root[i][j]
			if parent == -1:  # root does not have a parent
						print(F"""{key[node]} is the root of the binary search tree."""    )
			elif is_left:
						print(F"""{key[node]} is the left child of key {parent}."""    )
			else:
						print(F"""{key[node]} is the right child of key {parent}."""    )

			print_binary_search_tree(__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							node - 1   ,							key[node]   ,							__lowerCAmelCase    )
			print_binary_search_tree(__lowerCAmelCase   ,							__lowerCAmelCase   ,							node + 1   ,							__lowerCAmelCase   ,							key[node]   ,							__lowerCAmelCase    )






def        lowerCamelCase__    (    __lowerCAmelCase  :  Union[str, Any]    ):




			"""simple docstring"""


			nodes.sort(key=lambda __lowerCAmelCase    : node.key    )

			lowerCAmelCase_      =     len(__lowerCAmelCase    )

			lowerCAmelCase_      =     [nodes[i].key for i in range(__lowerCAmelCase    )]
			lowerCAmelCase_      =     [nodes[i].freq for i in range(__lowerCAmelCase    )]

			# This 2D array stores the overall tree cost (which's as minimized as possible);
			# for a single key, cost is equal to frequency of the key.
			lowerCAmelCase_      =     [[freqs[i] if i == j else 0 for j in range(__lowerCAmelCase    )] for i in range(__lowerCAmelCase    )]
			# sum[i][j] stores the sum of key frequencies between i and j inclusive in nodes
			# array
			lowerCAmelCase_      =     [[freqs[i] if i == j else 0 for j in range(__lowerCAmelCase    )] for i in range(__lowerCAmelCase    )]
			# stores tree roots that will be used later for constructing binary search tree
			lowerCAmelCase_      =     [[i if i == j else 0 for j in range(__lowerCAmelCase    )] for i in range(__lowerCAmelCase    )]

			for interval_length in range(2   ,							n + 1    ):
						for i in range(n - interval_length + 1    ):
									lowerCAmelCase_      =     i + interval_length - 1

									lowerCAmelCase_      =     sys.maxsize  # set the value to "infinity"
									lowerCAmelCase_      =     total[i][j - 1] + freqs[j]

									# Apply Knuth's optimization
									# Loop without optimization: for r in range(i, j + 1):
									for r in range(root[i][j - 1]   ,							root[i + 1][j] + 1    ):  # r is a temporal root
												lowerCAmelCase_      =     dp[i][r - 1] if r != i else 0  # optimal cost for left subtree
												lowerCAmelCase_      =     dp[r + 1][j] if r != j else 0  # optimal cost for right subtree
												lowerCAmelCase_      =     left + total[i][j] + right

												if dp[i][j] > cost:
															lowerCAmelCase_      =     cost
															lowerCAmelCase_      =     r

			print("Binary search tree nodes:"    )
			for node in nodes:
						print(__lowerCAmelCase    )

			print(F"""\nThe cost of optimal BST for given tree nodes is {dp[0][n - 1]}."""    )
			print_binary_search_tree(__lowerCAmelCase   ,							__lowerCAmelCase   ,							0   ,							n - 1   ,							-1   ,							__lowerCAmelCase    )






def        lowerCamelCase__    (    ):




			"""simple docstring"""


			lowerCAmelCase_      =     [Node(__lowerCAmelCase   ,							randint(1   ,							50    )    ) for i in range(10   ,							0   ,							-1    )]
			find_optimal_binary_search_tree(__lowerCAmelCase    )


if __name__ == "__main__":
			main()



