# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from paddle.fluid import core __all__ = [] class Index: def __init__(self, name): self._name = name class TreeIndex(Index): def __init__(self, name, path): super().__init__(name) self._wrapper = core.IndexWrapper() self._wrapper.insert_tree_index(name, path) self._tree = self._wrapper.get_tree_index(name) self._height = self._tree.height() self._branch = self._tree.branch() self._total_node_nums = self._tree.total_node_nums() self._emb_size = self._tree.emb_size() self._layerwise_sampler = None def height(self): return self._height def branch(self): return self._branch def total_node_nums(self): return self._total_node_nums def emb_size(self): return self._emb_size def get_all_leafs(self): return self._tree.get_all_leafs() def get_nodes(self, codes): return self._tree.get_nodes(codes) def get_layer_codes(self, level): return self._tree.get_layer_codes(level) def get_travel_codes(self, id, start_level=0): return self._tree.get_travel_codes(id, start_level) def get_ancestor_codes(self, ids, level): return self._tree.get_ancestor_codes(ids, level) def get_children_codes(self, ancestor, level): return self._tree.get_children_codes(ancestor, level) def get_travel_path(self, child, ancestor): res = [] while child > ancestor: res.append(child) child = int((child - 1) / self._branch) return res def get_pi_relation(self, ids, level): codes = self.get_ancestor_codes(ids, level) return dict(zip(ids, codes)) def init_layerwise_sampler( self, layer_sample_counts, start_sample_layer=1, seed=0 ): assert self._layerwise_sampler is None self._layerwise_sampler = core.IndexSampler("by_layerwise", self._name) self._layerwise_sampler.init_layerwise_conf( layer_sample_counts, start_sample_layer, seed ) def layerwise_sample(self, user_input, index_input, with_hierarchy=False): if self._layerwise_sampler is None: raise ValueError("please init layerwise_sampler first.") return self._layerwise_sampler.sample( user_input, index_input, with_hierarchy )