
"""simple docstring"""

import os
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ... import AutoTokenizer
from ...utils import logging


_A            = 'block_records.npy'


_A            = logging.get_logger(__name__)
def 		UpperCAmelCase					(		a_,						a_			):





		'''simple docstring'''


		import tensorflow.compat.va as tf

		lowerCamelCase     :			Dict		=    tf.data.TFRecordDataset(a_,						buffer_size=512 * 1024 * 1024			)
		lowerCamelCase     :			List[str]		=    blocks_dataset.batch(a_,						drop_remainder=a_			)
		lowerCamelCase     :			List[Any]		=    next(blocks_dataset.take(1			).as_numpy_iterator()			)

		return np_record






class        _lowercase   :




	def __init__( self		, UpperCAmelCase_		, UpperCAmelCase_		, UpperCAmelCase_=2		, UpperCAmelCase_=1000		, UpperCAmelCase_=100		, UpperCAmelCase_=100000		, )		->							int:
			from scann.scann_ops.py.scann_ops_pybind import builder as Builder

			lowerCamelCase     :			List[Any]		=    Builder(db=UpperCAmelCase_		, num_neighbors=UpperCAmelCase_		, distance_measure='dot_product'					)
			lowerCamelCase     :			str		=    builder.tree(
			    num_leaves=UpperCAmelCase_		, num_leaves_to_search=UpperCAmelCase_		, training_sample_size=UpperCAmelCase_					)
			lowerCamelCase     :			Union[str, Any]		=    builder.score_ah(dimensions_per_block=UpperCAmelCase_					)

			lowerCamelCase     :			str		=    builder.build()




	def 			_UpperCamelCase    ( self		, UpperCAmelCase_					)		->							int:
			lowerCamelCase	,    lowerCamelCase     :			Optional[int]		=    self.searcher.search_batched(question_projection.detach().cpu()					)
			return retrieved_block_ids.astype('int64'					)






class        _lowercase   :




	def __init__( self		, UpperCAmelCase_		, UpperCAmelCase_					)		->							List[Any]:
			super().__init__()
			lowerCamelCase     :			str		=    block_records
			lowerCamelCase     :			List[str]		=    tokenizer




	def __call__( self		, UpperCAmelCase_		, UpperCAmelCase_		, UpperCAmelCase_		, UpperCAmelCase_=None		, UpperCAmelCase_="pt"					)		->							Optional[Any]:
			lowerCamelCase     :			Optional[int]		=    np.take(self.block_records		, indices=UpperCAmelCase_		, axis=0					)

			lowerCamelCase     :			Any		=    self.tokenizer.decode(question_input_ids[0]		, skip_special_tokens=UpperCAmelCase_					)

			lowerCamelCase     :			int		=    []
			lowerCamelCase     :			Tuple		=    []
			for retrieved_block in retrieved_blocks:
					text.append(UpperCAmelCase_					)
					text_pair.append(retrieved_block.decode()					)

			lowerCamelCase     :			Dict		=    self.tokenizer(
			    UpperCAmelCase_		, UpperCAmelCase_		, padding=UpperCAmelCase_		, truncation=UpperCAmelCase_		, return_special_tokens_mask=UpperCAmelCase_		, max_length=UpperCAmelCase_					)
			lowerCamelCase     :			Union[str, Any]		=    concat_inputs.convert_to_tensors(UpperCAmelCase_					)

			if answer_ids is not None:
					return self.block_has_answer(UpperCAmelCase_		, UpperCAmelCase_					) + (concat_inputs_tensors,)
			else:
					return (None, None, None, concat_inputs_tensors)




	@classmethod
	def 			_UpperCamelCase    ( cls		, UpperCAmelCase_		, *UpperCAmelCase_		, **UpperCAmelCase_					)		->							Tuple:
			if os.path.isdir(UpperCAmelCase_					):
					lowerCamelCase     :			Optional[Any]		=    os.path.join(UpperCAmelCase_		, _REALM_BLOCK_RECORDS_FILENAME					)
			else:
					lowerCamelCase     :			int		=    hf_hub_download(
					    repo_id=UpperCAmelCase_		, filename=_REALM_BLOCK_RECORDS_FILENAME		, **UpperCAmelCase_					)
			lowerCamelCase     :			Optional[int]		=    np.load(UpperCAmelCase_		, allow_pickle=UpperCAmelCase_					)

			lowerCamelCase     :			int		=    AutoTokenizer.from_pretrained(UpperCAmelCase_		, *UpperCAmelCase_		, **UpperCAmelCase_					)

			return cls(UpperCAmelCase_		, UpperCAmelCase_					)




	def 			_UpperCamelCase    ( self		, UpperCAmelCase_					)		->							Optional[int]:
			# save block records
			np.save(os.path.join(UpperCAmelCase_		, _REALM_BLOCK_RECORDS_FILENAME					)		, self.block_records					)
			# save tokenizer
			self.tokenizer.save_pretrained(UpperCAmelCase_					)




	def 			_UpperCamelCase    ( self		, UpperCAmelCase_		, UpperCAmelCase_					)		->							Optional[int]:
			lowerCamelCase     :			Optional[Any]		=    []
			lowerCamelCase     :			Dict		=    []
			lowerCamelCase     :			str		=    []
			lowerCamelCase     :			List[Any]		=    0

			for input_id in concat_inputs.input_ids:
					lowerCamelCase     :			Union[str, Any]		=    input_id.tolist()
					# Check answers between two [SEP] tokens
					lowerCamelCase     :			List[Any]		=    input_id_list.index(self.tokenizer.sep_token_id					)
					lowerCamelCase     :			Tuple		=    first_sep_idx + 1 + input_id_list[first_sep_idx + 1 :].index(self.tokenizer.sep_token_id					)

					start_pos.append([]					)
					end_pos.append([]					)
					for answer in answer_ids:
							for idx in range(first_sep_idx + 1		, UpperCAmelCase_					):
									if answer[0] == input_id_list[idx]:
											if input_id_list[idx : idx + len(UpperCAmelCase_					)] == answer:
													start_pos[-1].append(UpperCAmelCase_					)
													end_pos[-1].append(idx + len(UpperCAmelCase_					) - 1					)

					if len(start_pos[-1]					) == 0:
							has_answers.append(UpperCAmelCase_					)
					else:
							has_answers.append(UpperCAmelCase_					)
							if len(start_pos[-1]					) > max_answers:
									lowerCamelCase     :			List[Any]		=    len(start_pos[-1]					)

        # Pad -1 to max_answers
			for start_pos_, end_pos_ in zip(UpperCAmelCase_		, UpperCAmelCase_					):
					if len(start_pos_					) < max_answers:
							lowerCamelCase     :			str		=    [-1] * (max_answers - len(start_pos_					))
							start_pos_ += padded
							end_pos_ += padded
			return has_answers, start_pos, end_pos













'''simple docstring'''



class 							__lowercase				:







	'''simple docstring'''

	def __init__(self   ,_lowerCamelCase       )							->							Optional[Any]:







				'''simple docstring'''





				__lowercase   =							val
				# Number of nodes in left subtree
				__lowercase   =							0
				__lowercase   =							None
				__lowercase   =							None
				__lowercase   =							None


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

				if self.val < other.val:
							__lowercase   =							self.right
							__lowercase   =							None
							if self.right:
										__lowercase   =							other
							__lowercase   =							other
							__lowercase   =							self.left_tree_size * 2 + 1
							return self
				else:
							__lowercase   =							other.right
							__lowercase   =							None
							if other.right:
										__lowercase   =							self
							__lowercase   =							self
							__lowercase   =							other.left_tree_size * 2 + 1
							return other






class 							__lowercase				:







	'''simple docstring'''

	def __init__(self   ,_lowerCamelCase=None   ,_lowerCamelCase=None   ,_lowerCamelCase=0       )							->							int:







				'''simple docstring'''





				__lowercase   =							heap_size
				__lowercase   =							bottom_root
				__lowercase   =							min_node


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				if other.size == 0:
							return None
				if self.size == 0:
							__lowercase   =							other.size
							__lowercase   =							other.bottom_root
							__lowercase   =							other.min_node
							return None
				# Update size
				__lowercase   =							self.size + other.size

				# Update min.node
				if self.min_node.val > other.min_node.val:
							__lowercase   =							other.min_node
				# Merge

				# Order roots by left_subtree_size
				__lowercase   =							[]
				__lowercase  ,						__lowercase   =							self.bottom_root, other.bottom_root
				while i or j:
							if i and ((not j) or i.left_tree_size < j.left_tree_size):
										combined_roots_list.append((i, True)       )
										__lowercase   =							i.parent
							else:
										combined_roots_list.append((j, False)       )
										__lowercase   =							j.parent
        # Insert links between them
				for i in range(len(_lowerCamelCase       ) - 1       ):
							if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
										__lowercase   =							combined_roots_list[i + 1][0]
										__lowercase   =							combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
				__lowercase   =							combined_roots_list[0][0]
				while i.parent:
							if (
							    (i.left_tree_size == i.parent.left_tree_size) and (not i.parent.parent)
							) or (
							    i.left_tree_size == i.parent.left_tree_size
							    and i.left_tree_size != i.parent.parent.left_tree_size
							):
										# Neighbouring Nodes
										__lowercase   =							i.left
										__lowercase   =							i.parent.parent

										# Merging trees
										__lowercase   =							i.merge_trees(i.parent       )

										# Updating links
										__lowercase   =							previous_node
										__lowercase   =							next_node
										if previous_node:
													__lowercase   =							i
										if next_node:
													__lowercase   =							i
							else:
										__lowercase   =							i.parent
        # Updating self.bottom_root
				while i.left:
							__lowercase   =							i.left
				__lowercase   =							i

				# Update other
				__lowercase   =							self.size
				__lowercase   =							self.bottom_root
				__lowercase   =							self.min_node

				# Return the merged heap
				return self


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Dict:







				'''simple docstring'''





				if self.size == 0:
							__lowercase   =							Node(_lowerCamelCase       )
							__lowercase   =							1
							__lowercase   =							self.bottom_root
				else:
							# Create new node
							__lowercase   =							Node(_lowerCamelCase       )

							# Update size
							self.size += 1

							# update min_node
							if val < self.min_node.val:
										__lowercase   =							new_node
							# Put new_node as a bottom_root in heap
							__lowercase   =							new_node
							__lowercase   =							self.bottom_root
							__lowercase   =							new_node

							# Consecutively merge roots with same left_tree_size
							while (
							    self.bottom_root.parent
							    and self.bottom_root.left_tree_size
							    == self.bottom_root.parent.left_tree_size
							):
										# Next node
										__lowercase   =							self.bottom_root.parent.parent

										# Merge
										__lowercase   =							self.bottom_root.merge_trees(self.bottom_root.parent       )

										# Update Links
										__lowercase   =							next_node
										__lowercase   =							None
										if next_node:
													__lowercase   =							self.bottom_root


	def   _UpperCAmelCase   (self       )							->							Union[str, Any]:







				'''simple docstring'''





				return self.min_node.val


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







				'''simple docstring'''





				return self.size == 0


	def   _UpperCAmelCase   (self       )							->							Union[str, Any]:







				'''simple docstring'''





				__lowercase   =							self.min_node.val

				# Last element in heap corner case
				if self.size == 1:
							# Update size
							__lowercase   =							0

							# Update bottom root
							__lowercase   =							None

							# Update min_node
							__lowercase   =							None

							return min_value
				# No right subtree corner case
				# The structure of the tree implies that this should be the bottom root
				# and there is at least one other root
				if self.min_node.right is None:
							# Update size
							self.size -= 1

							# Update bottom root
							__lowercase   =							self.bottom_root.parent
							__lowercase   =							None

							# Update min_node
							__lowercase   =							self.bottom_root
							__lowercase   =							self.bottom_root.parent
							while i:
										if i.val < self.min_node.val:
													__lowercase   =							i
										__lowercase   =							i.parent
							return min_value
				# General case
				# Find the BinomialHeap of the right subtree of min_node
				__lowercase   =							self.min_node.right
				__lowercase   =							None
				__lowercase   =							bottom_of_new
				__lowercase   =							1

				# Size, min_node and bottom_root
				while bottom_of_new.left:
							__lowercase   =							size_of_new * 2 + 1
							__lowercase   =							bottom_of_new.left
							if bottom_of_new.val < min_of_new.val:
										__lowercase   =							bottom_of_new
        # Corner case of single root on top left path
				if (not self.min_node.left) and (not self.min_node.parent):
							__lowercase   =							size_of_new
							__lowercase   =							bottom_of_new
							__lowercase   =							min_of_new
							# print("Single root, multiple nodes case")
							return min_value
				# Remaining cases
				# Construct heap of right subtree
				__lowercase   =							BinomialHeap(
				    bottom_root=_lowerCamelCase   ,min_node=_lowerCamelCase   ,heap_size=_lowerCamelCase       )

				# Update size
				__lowercase   =							self.size - 1 - size_of_new

				# Neighbour nodes
				__lowercase   =							self.min_node.left
				__lowercase   =							self.min_node.parent

				# Initialize new bottom_root and min_node
				__lowercase   =							previous_node or next_node
				__lowercase   =							next_node

				# Update links of previous_node and search below for new min_node and
				# bottom_root
				if previous_node:
							__lowercase   =							next_node

							# Update bottom_root and search for min_node below
							__lowercase   =							previous_node
							__lowercase   =							previous_node
							while self.bottom_root.left:
										__lowercase   =							self.bottom_root.left
										if self.bottom_root.val < self.min_node.val:
													__lowercase   =							self.bottom_root
				if next_node:
							__lowercase   =							previous_node

							# Search for new min_node above min_node
							__lowercase   =							next_node
							while i:
										if i.val < self.min_node.val:
													__lowercase   =							i
										__lowercase   =							i.parent
        # Merge heaps
				self.merge_heaps(_lowerCamelCase       )

				return min_value


	def   _UpperCAmelCase   (self       )							->							str:







				'''simple docstring'''





				__lowercase   =							self.bottom_root
				while top_root.parent:
							__lowercase   =							top_root.parent
				# preorder
				__lowercase   =							[]
				self.__traversal(_lowerCamelCase   ,_lowerCamelCase       )
				return heap_pre_order


	def   _UpperCAmelCase   (self   ,_lowerCamelCase   ,_lowerCamelCase   ,_lowerCamelCase=0       )							->							str:







				'''simple docstring'''





				if curr_node:
							preorder.append((curr_node.val, level)       )
							self.__traversal(curr_node.left   ,_lowerCamelCase   ,level + 1       )
							self.__traversal(curr_node.right   ,_lowerCamelCase   ,level + 1       )
				else:
							preorder.append(('''#''', level)       )


	def __str__(self       )							->							List[str]:







				'''simple docstring'''





				if self.is_empty():
							return ""
				__lowercase   =							self.pre_order()

				return "\n".join(('''-''' * level + str(_lowerCamelCase       )) for value, level in preorder_heap       )


# Unit Tests
if __name__ == "__main__":
	import doctest

	doctest.testmod()





