Changelog

January 28, 2025 ยท View on GitHub

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

  • Removed MOOC dataset.

  • Remove random split from citeseer and cora.

[0.1.64] - 2025-01-06

  • Make DeepGNN snark server temporal loading skippable

[0.1.64] - 2024-08-13

Added

  • Make DeepGNN snark server feature loading skippable

[0.1.63] - 2024-05-10

Fixed

  • Fixes temporal sampling bug, in graphs with multiple edge types that were not deleted, neighbors will be repeated with uniform sampling.

[0.1.62] - 2024-01-19

Fixed

  • Fixes edge feature fetching when edges are not sorted by destination id.

[0.1.61] - 2022-10-12

Added

  • Add return_edge_created_ts argument to neighbor sampling methods to return timestamps when edges connecting nodes were created.

  • MOOC temporal dataset.

  • TGN example.

  • GCN example.

  • Add PyG remote backend example.

Fixed

  • Uniform sampling works in temporal graphs.
  • ADL path parsing to download graph data.

Changed

  • Changed pytorch examples to be self contained and use Ray for distributed training.

Removed

  • link prediction and knowledgegraph examples
  • deepgnn-torch/tf are no longer published

[0.1.60] - 2022-04-18

Added

  • Breaking. Temporal graph support. Custom decoders must add 2 optional integers in returned tuple in decode method, representing created_at and removed_at fields. Metadata file must have a watermark field.

  • Last N created neighbors sampling method for temporal graphs.

Changed

  • Change generated file meta.txt to meta.json in json format.

[0.1.59] - 2022-03-29

Added

  • All DistributedGraph config options (e.g. grpc_options, num_threads, ...) are exposed to DistributedClient and BackendOptions

[0.1.58] - 2022-02-15

Added

  • Add usage example for Ray Train, see docs/torch/ray_usage.rst.

  • Add documentation for Ray Data usage, see tutorial and example

  • Add Reddit dataset download tool at deepgnn.graph_engine.data.reddit.

  • Added grpc_options to distributed client to control service config.

  • Added ppr-go neighbor sampling strategy.

Fixed

  • Implement del method to release C++ client and server. Important for ray actors, because they create numerous clients during training.

  • If sparse feature values present on multiple servers, then only one will be returned with source picked randomly.

Removed

  • Remove ALL_NODE_TYPE, ALL_EDGE_TYPE, len and iter from Graph API.

[0.1.57] - 2022-12-15

Changed

  • Breaking. Rename get_feature_type -> get_python_type.

[0.1.56] - 2022-11-02

Added

  • Add new converter input format "EdgeList" with EdgeListDecoder. Format has nodes and edges on separate lines, is smaller and faster to convert.

  • Breaking. Added version checks for binary data. Requires to convert graph data or add v1 at the top of meta files.

  • Add migrate script to pull to new version of deepgnn.

  • Add debug mode to MultiWorkersConverter, using debug=True will now disable multiprocessing and show error messages.

  • Load graph partitions from separate folders.

Changed

  • Breaking. Remove FeatureType enum, replace with np.dtype. FeatureType.BINARY -> np.uint8, FeatureType.FLOAT -> np.float32, FeatureType.INT64 -> np.int64.

  • Rename function deepgnn.graph_engine.data.to_json_node -> deepgnn.graph_engine.data.to_edge_list_node and update functionality accordingly.

[0.1.55] - 2022-08-26

Added

  • Support nodes and their outgoing edges on different partitions.

  • Adds neighbor count method to graph.

Fixed

  • Return empty indices and values for missing sparse features.

[0.1.54] - 2022-08-04

Fixed

  • Don't record empty sparse features and log warning if sparse features were requested, but dense features are stored.

[0.1.53] - 2022-08-02

Fixed

  • JSON/TSV converter didn't sort edges by types resulted in incorrect sampling.

[0.1.52] - 2022-07-27

Changed

  • Rename and move convert.output to converter.process.converter_process. Dispatchers make argument 'process' default to converter.process.converter_process. Dispatchers move process argument after decoder_type.

  • Replace converter and dispatcher's argument "decoder_type" -> "decoder" that accepts Decoder object directly instead of DecoderType enum. Replace DecoderType enum with type hint.

  • Make Decoder.decode a generator that yields a node then its outgoing edges in order. The yield format for nodes/edges is (node_id/src, -1/dst, type, weight, features), with features being a list of dense features as ndarrays and sparse features as 2 tuples, coordinates and values.

Added

  • Add BinaryWriter as new entry point for NodeWriter, EdgeWriter and alias writers.

Removed

  • Meta.json files are no longer needed by the converter. Remove meta path argument from MultiWorkerConverter and Dispatchers.

Fixed

  • Fill dimensions with 0 for missing features.