add the QuatE model and the OctonionE model

wovenmind-workspaces · Nov 9, 2020 · 3aeca22 · 3aeca22
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Showing 9 changed files with 566 additions and 6 deletions.
diff --git a/README.md b/README.md
@@ -59,8 +59,9 @@ With pykg2vec command-line interface, you can
     (pykg2vec) $ pykg2vec-train -mn TransE
 
     # Train using different KGE methods.
-    (pykg2vec) $ pykg2vec-train -mn [TransE|TransD|TransH|TransG|TransM|TransR|Complex|ComplexN3|CP|RotatE|Analogy|
-                           DistMult|KG2E|KG2E_EL|NTN|Rescal|SLM|SME|SME_BL|HoLE|ConvE|ConvKB|Proje_pointwise]
+    (pykg2vec) $ pykg2vec-train -mn [TransE|TransD|TransH|TransG|TransM|TransR|Complex|ComplexN3|
+                        CP|RotatE|Analogy|DistMult|KG2E|KG2E_EL|NTN|Rescal|SLM|SME|SME_BL|HoLE|
+                        ConvE|ConvKB|Proje_pointwise|MuRP|QuatE|OctonionE]
 
     # For KGE using projection-based loss function, use more processes for batch generation.
     (pykg2vec) $ pykg2vec-train -mn [ConvE|ConvKB|Proje_pointwise] -npg [the number of processes, 4 or 6]

diff --git a/examples/train.py b/examples/train.py
@@ -14,8 +14,9 @@
 
 - Train using different KGE methods. Check `Implemented KGE Algorithms`__ for more details: ::
 
-    $ python train.py -mn [TransE|TransD|TransH|TransG|TransM|TransR|Complex|ComplexN3|CP|RotatE|Analogy|
-                        DistMult|KG2E|KG2E_EL|NTN|Rescal|SLM|SME|SME_BL|HoLE|ConvE|ConvKB|Proje_pointwise]
+    $ python train.py -mn [TransE|TransD|TransH|TransG|TransM|TransR|Complex|ComplexN3|
+                        CP|RotatE|Analogy|DistMult|KG2E|KG2E_EL|NTN|Rescal|SLM|SME|SME_BL|HoLE|
+                        ConvE|ConvKB|Proje_pointwise|MuRP|QuatE|OctonionE]
 
 - For KGE using projection-based loss function, use more processes for batch generation: ::
 

diff --git a/pykg2vec/common.py b/pykg2vec/common.py
@@ -264,8 +264,11 @@ def __init__(self):
                          "hole": "pairwise.HoLE",
                          "distmult": "pointwise.DistMult",
                          "kg2e": "pairwise.KG2E",
+                         "murp": "hyperbolic.MuRP",
                          "ntn": "pairwise.NTN",
+                         "octonione": "pointwise.OctonionE",
                          "proje_pointwise": "projection.ProjE_pointwise",
+                         "quate": "pointwise.QuatE",
                          "rescal": "pairwise.Rescal",
                          "rotate": "pairwise.RotatE",
                          "simple": "pointwise.SimplE",
@@ -279,7 +282,7 @@ def __init__(self):
                          "transm": "pairwise.TransM",
                          "transr": "pairwise.TransR",
                          "tucker": "projection.TuckER",
-                         "murp": "hyperbolic.MuRP"}
+                         }
 
     def import_model_config(self, name):
         """This function imports models and configuration.

diff --git a/pykg2vec/hyperparams/OctonionE.yaml b/pykg2vec/hyperparams/OctonionE.yaml
@@ -0,0 +1,15 @@
+model_name: "OctonionE"
+datasets:
+  - dataset: "freebase15k_237"
+    parameters:
+      learning_rate: 0.1
+      l1_flag: True
+      hidden_size: 50
+      batch_size: 100
+      epochs: 10000
+      margin: 1.0
+      optimizer: "adagrad"
+      sampling: "uniform"
+      neg_rate: 1
+      lmbda: 0.2
+      alpha: 0.1
diff --git a/pykg2vec/hyperparams/QuatE.yaml b/pykg2vec/hyperparams/QuatE.yaml
@@ -0,0 +1,57 @@
+model_name: "QuatE"
+datasets:
+  - dataset: "freebase15k_237"
+    parameters:
+      learning_rate: 0.1
+      l1_flag: True
+      hidden_size: 100
+      batch_size: 100
+      epochs: 15000
+      margin: 1.0
+      optimizer: "adagrad"
+      sampling: "uniform"
+      neg_rate: 1
+      lmbda: 0.2
+      alpha: 0.1
+
+  - dataset: "freebase15k"
+    parameters:
+      learning_rate: 0.1
+      l1_flag: True
+      hidden_size: 200
+      batch_size: 100
+      epochs: 5000
+      margin: 1.0
+      optimizer: "adagrad"
+      sampling: "uniform"
+      neg_rate: 1
+      lmbda: 0.1
+      alpha: 0.1
+
+  - dataset: "wordnet18_rr"
+    parameters:
+      learning_rate: 0.1
+      l1_flag: True
+      hidden_size: 100
+      batch_size: 100
+      epochs: 40000
+      margin: 1.0
+      optimizer: "adagrad"
+      sampling: "bern"
+      neg_rate: 1
+      lmbda: 0.1
+      alpha: 0.1
+
+  - dataset: "wordnet18"
+    parameters:
+      learning_rate: 0.1
+      l1_flag: True
+      hidden_size: 300
+      batch_size: 100
+      epochs: 3000
+      margin: 1.0
+      optimizer: "adagrad"
+      sampling: "bern"
+      neg_rate: 1
+      lmbda: 0.05
+      alpha: 0.1