initial commit

Author: migalkin

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 MilaGraph
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -0,0 +1,46 @@
+output_dir: ~/git/ultra_pyg_dev/output
+
+dataset:
+  class: {{ dataset }}
+  root: ~/git/ultra_pyg_dev/kg-datasets/
+  version: {{ version }}
+
+model:
+  class: Ultra
+  relation_model:
+    class: NBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+  entity_model:
+    class: IndNBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+
+task:
+  name: InductiveInference
+  num_negative: 256
+  strict_negative: yes
+  adversarial_temperature: 1
+  metric: [mr, mrr, hits@1, hits@3, hits@10, hits@10_50]
+
+optimizer:
+  class: AdamW
+  lr: 5.0e-4
+
+train:
+  gpus: {{ gpus }}
+  batch_size: 16
+  num_epoch: {{ epochs }}
+  log_interval: 100
+  batch_per_epoch: {{ bpe }}
+  #logger: wandb
+
+checkpoint: {{ ckpt }}

asset/ultra_logo.png

@@ -0,0 +1,44 @@
+output_dir: ~/git/ultra_pyg_dev/output
+
+dataset:
+  class: {{ dataset }}
+  root: ~/git/ultra_pyg_dev/kg-datasets/
+
+model:
+  class: Ultra
+  relation_model:
+    class: NBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+  entity_model:
+    class: IndNBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+
+task:
+  name: TransductiveInference
+  num_negative: 256
+  strict_negative: yes
+  adversarial_temperature: 1
+  metric: [mr, mrr, hits@1, hits@3, hits@10]
+
+optimizer:
+  class: AdamW
+  lr: 5.0e-4
+
+train:
+  gpus: {{ gpus }}
+  batch_size: 8
+  num_epoch: {{ epochs }}
+  log_interval: 100
+  batch_per_epoch: {{ bpe }}
+
+checkpoint: {{ ckpt }}

ckpts/ultra_3g.pth

@@ -0,0 +1,45 @@
+output_dir: ~/nosnap/ultra_outputs/
+
+dataset:
+  class: JointDataset
+  graphs: [FB15k237, WN18RR, CoDExMedium]
+  root: ~/nosnap/ultra_datasets/
+
+model:
+  class: Ultra
+  relation_model:
+    class: NBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+  entity_model:
+    class: IndNBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+
+task:
+  name: MultiGraphPretraining
+  num_negative: 512
+  strict_negative: yes
+  adversarial_temperature: 1
+  metric: [mr, mrr, hits@1, hits@3, hits@10]
+
+optimizer:
+  class: AdamW
+  lr: 5.0e-4
+
+train:
+  gpus: {{ gpus }}
+  batch_size: 64
+  num_epoch: 10
+  log_interval: 800
+  batch_per_epoch: 80000
+  fast_test: 500
+  #logger: wandb

ckpts/ultra_4g.pth

@@ -0,0 +1,45 @@
+output_dir: ~/nosnap/ultra_outputs/
+
+dataset:
+  class: JointDataset
+  graphs: [FB15k237, WN18RR, CoDExMedium, NELL995]
+  root: ~/nosnap/ultra_datasets/
+
+model:
+  class: Ultra
+  relation_model:
+    class: NBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+  entity_model:
+    class: IndNBFNet
+    input_dim: 64
+    hidden_dims: [64, 64, 64, 64, 64, 64]
+    message_func: distmult
+    aggregate_func: sum
+    short_cut: yes
+    layer_norm: yes
+
+task:
+  name: MultiGraphPretraining
+  num_negative: 512
+  strict_negative: yes
+  adversarial_temperature: 1
+  metric: [mr, mrr, hits@1, hits@3, hits@10]
+
+optimizer:
+  class: AdamW
+  lr: 5.0e-4
+
+train:
+  gpus: {{ gpus }}
+  batch_size: 64
+  num_epoch: 10
+  log_interval: 400
+  batch_per_epoch: 40000
+  fast_test: 500
+  #logger: wandb

config/inductive/inference.yaml

@@ -0,0 +1,7 @@
+torch>=2.1.0
+torch-scatter>=2.1.2
+#torch-sparse>=0.6.18
+torch-geometric>=2.4.0
+ninja
+easydict
+pyyaml