目錄
圖嵌入是一種從圖中生成無監督節點特征（node features）的方法，生成的特征可以應用在各類機器學習任務上。現代的圖網絡，尤其是在工業應用中，通常會包含數十億的節點（node）和數萬億的邊（edge）。這已經超出了已知嵌入系統的處理能力。Facebook開源了一種嵌入系統，PyTorch-BigGraph（PBG），系統對傳統的多關系嵌入系統做了幾處修改讓系統能擴展到能處理數十億節點和數萬億條邊的圖形。
本系列為翻譯的pytouch的官方手冊，希望能幫助大家快速入門GNN及其使用，全文十五篇，文中如果有勘誤請隨時聯系。
（一）Facebook開源圖神經網絡-Pytorch Biggraph
（二）Facebook：BigGraph 中文文檔-數據模型（PyTorch）
（三）Facebook：BigGraph 中文文檔-從實體嵌入到邊分值（PyTorch）
（四）Facebook：BigGraph 中文文檔-I/O格式化（PyTorch）
（五）Facebook：BigGraph 中文文檔-批預處理
（六）Facebook：BigGraph 中文文檔-分布式模式（PyTorch）
（七）Facebook：BigGraph 中文文檔-損失計算（PyTorch）
（八）Facebook：BigGraph 中文文檔-評估（PyTorch）
（九）Facebook：BigGraph 中文文檔-動態關系（PyTorch）
Dynamic relations 動態關系
Caution 注意
This is an advanced topic! 這是升級教程！
Enabling the?dynamic_relations?flag in the configuration activates an alternative mode to be used for graphs with a large number of relations (more than ~100 relations). In dynamic relation mode, PBG runs with several modifications to its “standard” operation in order to support the large number of relations.?
在配置中啟動dynamic_relations配置將激活另一種模式，用于具有大量關系（超過~100）的圖。在動態關系模式下，PBG運行時對其“標準”操作進行了一些修改用于支持大量的關系。
The differences are:
相比不同有：
The?number?of relations isn’t provided in the config but is instead found in the input data, namely in the entity path, inside a?dynamic_rel_count.txt?file. The settings of the relations, however, are still provided in the config file. This happens by providing a single relation config which will act as a “template” for all other ones, by being duplicated an appropriate number of times. One can think of this as the one relation in the config being “broadcasted” to the size of the relation list found in the?dynamic_rel_count.txt?file.
配置中不需要提供number數量，替代的是在輸入數據的整個實體路徑中來查找，即dynamic_rel_count.txt文件，但關系的設置，仍然需要在配置文件中配置。這是通過提供一個單獨的關系配置來實現的，該配置將充當當所有其他關系的“模板”，并且被復制合適的次數。我們將其看做是配置中的一個關系被“廣播”到dynamic_rel_count.txt文件中的關系列表的大小。
The batches of positive edges that are passed from the training loop into the model contain edges for multiple relation types at the same time (instead of each batch coming entirely from the same relation type). This introduces some performance challenges in how the operators are applied to the embeddings, as instead of a single operator with a single set of parameters applied to all edges, there might be a different one for each edge. The previous property ensures that all the operators are of the same type, so just their parameters might differ from one row to another. To account for this, the operators for dynamic relations are implemented differently, with a single operator object containing the parameters for all relation types. This implementation detail should be transparent as for how the operators are applied to the embeddings, but might come up when retrieving the parameters at the end of training.
在訓練循環中包含正邊的批次，傳入模型中同時包含多個關系類型的邊（不是每個批次完全來自同一關系類型）。這讓如何將運算符應用于嵌入上帶來了一些性能挑戰，因為對于每個邊，可能會有一個不同的運算符，而不是對所有邊應用一組參數的單個運算符。previous屬性確保所有運算符都是同一類型的，因此這些參數可能會不同的行不一樣。為了匹配，動態關系的運算符以不同方式實現，單個運算符對象包含所有關系類型的參數。對于如何向運算符應用到嵌入中，整個實現細節應該是透明的，但在訓練結束時檢索參數是可能會出現。
With non-dynamic relations, the operator is applied to the embedding of the right-hand side entity of the edge, whereas the embedding of the left-hand side entity is left unchanged. In a given batch, denote the???i-th positive edge by?(????,??,????) (???? and?????yi?being the left- and right-hand side entities,??? being the relation type). For each of the positive edges, denote its???-th negative sample?(????,??,??′??,??). Due to?same-batch negative sampling?it may occur that the same right-hand side entity is used as a negative for several positives, that is, that???′??1,??1=??′??2,??2 . for???1≠??2. However, since it’s the same relation type???rfor all negatives, all the right-hand side entities will be transformed in the same way (i.e., passed through???’s operator) no matter what positive edge they are a negative for. we need to apply the operator of???r?to all of them, hence the total number of operator evaluations is equal to the number of positives and negatives.
對于非動態關系，算子應用在右側實體的嵌入上，同事左側試題的嵌入保持不變。在給定的批次中，用(????,??,????)來表示第i個正邊（xi和yi為左側和右側的實體，r是關系類型）。對每一個正邊，用(????,??,??′??,??)來表示對應的第j個負樣本。由于同一批負采樣可能會出現同一個右側實體被抽樣為復變，如：??′??1,??1=??′??2,??2? 并且 i1≠??2.?
