



"""simple docstring"""







import logging
import os
from typing import List, Tuple

import numpy as np
import psutil
import torch
import torch.distributed as dist

from transformers import RagRetriever


UpperCamelCase     =							logging.getLogger(__name__)






class       UpperCamelCase__			(   _lowerCAmelCase      ):

			"""simple docstring"""


			def __init__(      self						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__=None		)      ->	Optional[Any]:
				super().__init__(
				    SCREAMING_SNAKE_CASE__						,	question_encoder_tokenizer=SCREAMING_SNAKE_CASE__						,	generator_tokenizer=SCREAMING_SNAKE_CASE__						,	index=SCREAMING_SNAKE_CASE__						,	init_retrieval=SCREAMING_SNAKE_CASE__						,	)
				A__											=					None


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	int:
				logger.info("initializing retrieval"		)

				# initializing a separate process group for retrieval as the default
				# nccl backend doesn't support gather/scatter operations while gloo
				# is too slow to replace nccl for the core gpu communication
				if dist.is_initialized():
					logger.info("dist initialized"		)
					# needs to be set manually
					A__											=					self._infer_socket_ifname()
					# avoid clash with the NCCL port
					A__											=					str(distributed_port + 1		)
					A__											=					dist.new_group(ranks=SCREAMING_SNAKE_CASE__						,	backend="gloo"		)

				# initialize retriever only on the main worker
				if not dist.is_initialized() or self._is_main():
					logger.info("dist not initialized / main"		)
					self.index.init_index()

				# all processes wait untill the retriever is initialized by the main process
				if dist.is_initialized():
					torch.distributed.barrier(group=self.process_group		)


			def   snake_case__	(      self		)      ->	str:
				return dist.get_rank(group=self.process_group		) == 0


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__=torch.floataa		)      ->	int:
				A__											=					torch.empty(SCREAMING_SNAKE_CASE__						,	dtype=SCREAMING_SNAKE_CASE__		)
				dist.scatter(SCREAMING_SNAKE_CASE__						,	src=0						,	scatter_list=SCREAMING_SNAKE_CASE__						,	group=self.process_group		)
				return target_tensor


			def   snake_case__	(      self		)      ->	List[Any]:
				A__											=					psutil.net_if_addrs()
				# a hacky way to deal with varying network interface names
				A__											=					next((addr for addr in addrs if addr.startswith("e"		))						,	SCREAMING_SNAKE_CASE__		)
				return ifname







			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)      ->	Tuple[np.ndarray, List[dict]]:

				# single GPU training
				if not dist.is_initialized():
					A__							,							A__											=					self._main_retrieve(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)
					return retrieved_doc_embeds, doc_ids, self.index.get_doc_dicts(SCREAMING_SNAKE_CASE__		)

				# distributed training
				A__											=					dist.get_world_size(group=self.process_group		)

				# gather logic
				A__											=					None
				if self._is_main():
					A__											=					[torch.empty(question_hidden_states.shape						,	dtype=torch.floataa		) for _ in range(SCREAMING_SNAKE_CASE__		)]
				dist.gather(torch.tensor(SCREAMING_SNAKE_CASE__		)						,	dst=0						,	gather_list=SCREAMING_SNAKE_CASE__						,	group=self.process_group		)

				# scatter logic
				A__											=					question_hidden_states.shape[0]
				A__											=					[]
				A__											=					[]
				if self._is_main():
					assert len(SCREAMING_SNAKE_CASE__		) == world_size
					A__							,							A__											=					self._main_retrieve(torch.cat(SCREAMING_SNAKE_CASE__		).numpy()						,	SCREAMING_SNAKE_CASE__		)
					A__							,							A__											=					torch.tensor(SCREAMING_SNAKE_CASE__		), torch.tensor(SCREAMING_SNAKE_CASE__		)
					A__											=					self._chunk_tensor(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)
					A__											=					self._chunk_tensor(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)
				A__											=					self._scattered(SCREAMING_SNAKE_CASE__						,	[n_queries, n_docs]						,	target_type=torch.intaa		)
				A__											=					self._scattered(SCREAMING_SNAKE_CASE__						,	[n_queries, n_docs, question_hidden_states.shape[1]]		)

				return retrieved_doc_embeds.numpy(), doc_ids.numpy(), self.index.get_doc_dicts(SCREAMING_SNAKE_CASE__		)









"""simple docstring"""







class       UpperCamelCase__			:

			"""simple docstring"""


			def __init__(      self						,	SCREAMING_SNAKE_CASE__ = ""						,	SCREAMING_SNAKE_CASE__ = False		)      ->	None:
				# Mapping from the first character of the prefix of the node
				A__											=					{}

				# A node will be a leaf if the tree contains its word
				A__											=					is_leaf

				A__											=					prefix


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	tuple[str, str, str]:
				A__											=					0
				for q, w in zip(self.prefix						,	SCREAMING_SNAKE_CASE__		):
					if q != w:
						break

					x += 1

				return self.prefix[:x], self.prefix[x:], word[x:]


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	None:
				for word in words:
					self.insert(SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	None:
				# Case 1: If the word is the prefix of the node
				# Solution: We set the current node as leaf
				if self.prefix == word:
					A__											=					True

				# Case 2: The node has no edges that have a prefix to the word
				# Solution: We create an edge from the current node to a new one
				# containing the word
				elif word[0] not in self.nodes:
					A__											=					RadixNode(prefix=SCREAMING_SNAKE_CASE__						,	is_leaf=SCREAMING_SNAKE_CASE__		)

				else:
					A__											=					self.nodes[word[0]]
					A__							,							A__							,							A__											=					incoming_node.match(
					    SCREAMING_SNAKE_CASE__		)

					# Case 3: The node prefix is equal to the matching
					# Solution: We insert remaining word on the next node
					if remaining_prefix == "":
						self.nodes[matching_string[0]].insert(SCREAMING_SNAKE_CASE__		)

					# Case 4: The word is greater equal to the matching
					# Solution: Create a node in between both nodes, change
					# prefixes and add the new node for the remaining word
					else:
						A__											=					remaining_prefix

						A__											=					self.nodes[matching_string[0]]
						A__											=					RadixNode(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		)
						A__											=					aux_node

						if remaining_word == "":
							A__											=					True
						else:
							self.nodes[matching_string[0]].insert(SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	bool:
				A__											=					self.nodes.get(word[0]						,	SCREAMING_SNAKE_CASE__		)
				if not incoming_node:
					return False
				else:
					A__							,							A__							,							A__											=					incoming_node.match(
					    SCREAMING_SNAKE_CASE__		)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
						return False
					# This applies when the word and the prefix are equal
					elif remaining_word == "":
						return incoming_node.is_leaf
					# We have word remaining so we check the next node
					else:
						return incoming_node.find(SCREAMING_SNAKE_CASE__		)


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	bool:
				A__											=					self.nodes.get(word[0]						,	SCREAMING_SNAKE_CASE__		)
				if not incoming_node:
					return False
				else:
					A__							,							A__							,							A__											=					incoming_node.match(
					    SCREAMING_SNAKE_CASE__		)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
						return False
					# We have word remaining so we check the next node
					elif remaining_word != "":
						return incoming_node.delete(SCREAMING_SNAKE_CASE__		)
					else:
						# If it is not a leaf, we don't have to delete
						if not incoming_node.is_leaf:
							return False
						else:
							# We delete the nodes if no edges go from it
							if len(incoming_node.nodes		) == 0:
								del self.nodes[word[0]]
								# We merge the current node with its only child
								if len(self.nodes		) == 1 and not self.is_leaf:
									A__											=					list(self.nodes.values()		)[0]
									A__											=					merging_node.is_leaf
									self.prefix += merging_node.prefix
									A__											=					merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
							elif len(incoming_node.nodes		) > 1:
								A__											=					False
							# If there is 1 edge, we merge it with its child
							else:
								A__											=					list(incoming_node.nodes.values()		)[0]
								A__											=					merging_node.is_leaf
								incoming_node.prefix += merging_node.prefix
								A__											=					merging_node.nodes

							return True







			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__ = 0		)      ->	None:
				if self.prefix != "":
					print("-" * height						,	self.prefix						,	"  (leaf)" if self.is_leaf else ""		)

				for value in self.nodes.values():
					value.print_tree(height + 1		)



def       _lowerCamelCase				(							)	-> bool:






	"""simple docstring"""





	A__											=					"banana bananas bandana band apple all beast".split()
	A__											=					RadixNode()
	root.insert_many(UpperCAmelCase_     )

	assert all(root.find(UpperCAmelCase_     ) for word in words     )
	assert not root.find("bandanas"     )
	assert not root.find("apps"     )
	root.delete("all"     )
	assert not root.find("all"     )
	root.delete("banana"     )
	assert not root.find("banana"     )
	assert root.find("bananas"     )

	return True

def       _lowerCamelCase				(							)	-> None:






	"""simple docstring"""





	assert test_trie()

def       _lowerCamelCase				(							)	-> None:






	"""simple docstring"""





	A__											=					RadixNode()
	A__											=					"banana bananas bandanas bandana band apple all beast".split()
	root.insert_many(UpperCAmelCase_     )

	print("Words:",	UpperCAmelCase_     )
	print("Tree:"     )
	root.print_tree()


if __name__ == "__main__":
			main()




