diff --git a/docs/source/byo/data.rst b/docs/source/byo/data.rst
index a01e43c34b..e13772ff9f 100644
--- a/docs/source/byo/data.rst
+++ b/docs/source/byo/data.rst
@@ -47,14 +47,14 @@ The remainder of the examples will be for :func:`pykeen.pipeline.pipeline`, but
for :func:`pykeen.hpo.hpo_pipeline`.
If you want to add dataset-wide arguments, you can use the ``dataset_kwargs`` argument
-to the :class:`pykeen.pipeline.pipeline` to enable options like ``create_inverse_triples=True``.
+to the :class:`pykeen.pipeline.pipeline` to enable options like ``use_inverse_relations=True``.
>>> from pykeen.pipeline import pipeline
>>> from pykeen.datasets.nations import NATIONS_TRAIN_PATH, NATIONS_TEST_PATH
>>> result = pipeline(
... training=NATIONS_TRAIN_PATH,
... testing=NATIONS_TEST_PATH,
-... dataset_kwargs={'create_inverse_triples': True},
+... dataset_kwargs={'use_inverse_relations': True},
... model='TransE',
... epochs=5, # short epochs for testing - you should go higher
... )
@@ -89,7 +89,7 @@ TSV files, you can use the :class:`pykeen.triples.TriplesFactory` interface.
the wrong identifiers in the training set during evaluation, and we'd get nonsense results.
The ``dataset_kwargs`` argument is ignored when passing your own :class:`pykeen.triples.TriplesFactory`, so be
-sure to include the ``create_inverse_triples=True`` in the instantiation of those classes if that's your
+sure to include the ``use_inverse_relations=True`` in the instantiation of those classes if that's your
desired behavior as in:
>>> from pykeen.triples import TriplesFactory
@@ -97,13 +97,13 @@ desired behavior as in:
>>> from pykeen.datasets.nations import NATIONS_TRAIN_PATH, NATIONS_TEST_PATH
>>> training = TriplesFactory.from_path(
... NATIONS_TRAIN_PATH,
-... create_inverse_triples=True,
+... use_inverse_relations=True,
... )
>>> testing = TriplesFactory.from_path(
... NATIONS_TEST_PATH,
... entity_to_id=training.entity_to_id,
... relation_to_id=training.relation_to_id,
-... create_inverse_triples=True,
+... use_inverse_relations=True,
... )
>>> result = pipeline(
... training=training,
diff --git a/docs/source/tutorial/inductive_lp.rst b/docs/source/tutorial/inductive_lp.rst
index be88880fda..7b67a49e23 100644
--- a/docs/source/tutorial/inductive_lp.rst
+++ b/docs/source/tutorial/inductive_lp.rst
@@ -91,7 +91,7 @@ Let's create a basic `InductiveNodePiece` using one of the `InductiveFB15k237` d
from pykeen.models.inductive import InductiveNodePiece
from pykeen.losses import NSSALoss
- dataset = InductiveFB15k237(version="v1", create_inverse_triples=True)
+ dataset = InductiveFB15k237(version="v1", use_inverse_relations=True)
model = InductiveNodePiece(
triples_factory=dataset.transductive_training, # training factory, used to tokenize training nodes
@@ -110,7 +110,7 @@ Creating a message-passing version of NodePiece is pretty much the same:
from pykeen.models.inductive import InductiveNodePieceGNN
from pykeen.losses import NSSALoss
- dataset = InductiveFB15k237(version="v1", create_inverse_triples=True)
+ dataset = InductiveFB15k237(version="v1", use_inverse_relations=True)
model = InductiveNodePieceGNN(
triples_factory=dataset.transductive_training, # training factory, will be also used for a GNN
@@ -166,7 +166,7 @@ Let's create a training loop and validation / test evaluators:
from pykeen.evaluation.rank_based_evaluator import SampledRankBasedEvaluator
from pykeen.losses import NSSALoss
- dataset = InductiveFB15k237(version="v1", create_inverse_triples=True)
+ dataset = InductiveFB15k237(version="v1", use_inverse_relations=True)
model = ... # model init here, one of InductiveNodePiece
optimizer = ... # some optimizer
@@ -207,7 +207,7 @@ in the sLCWA mode with 32 negative samples per positive, with NSSALoss, and Samp
from torch.optim import Adam
- dataset = InductiveFB15k237(version="v1", create_inverse_triples=True)
+ dataset = InductiveFB15k237(version="v1", use_inverse_relations=True)
model = InductiveNodePieceGNN(
triples_factory=dataset.transductive_training, # training factory, will be also used for a GNN
diff --git a/docs/source/tutorial/node_piece.rst b/docs/source/tutorial/node_piece.rst
index 7e6b8e9447..5d7284c5c7 100644
--- a/docs/source/tutorial/node_piece.rst
+++ b/docs/source/tutorial/node_piece.rst
@@ -18,7 +18,7 @@ throughout the following examples.
from pykeen.datasets import FB15k237
# inverses are necessary for the current version of NodePiece
- dataset = FB15k237(create_inverse_triples=True)
+ dataset = FB15k237(use_inverse_relations=True)
In the simplest usage of :class:`pykeen.models.NodePiece`, we'll only
use relations for tokenization. We can do this by with the following
@@ -286,7 +286,7 @@ Let's pack the last NodePiece model into the pipeline:
result = pipeline(
dataset="fb15k237",
dataset_kwargs=dict(
- create_inverse_triples=True,
+ use_inverse_relations=True,
),
model=NodePiece,
model_kwargs=dict(
@@ -498,7 +498,7 @@ pipeline:
result = pipeline(
dataset="fb15k237",
dataset_kwargs=dict(
- create_inverse_triples=True,
+ use_inverse_relations=True,
),
model=NodePiece,
model_kwargs=dict(
@@ -590,7 +590,7 @@ Let's use the new tokenizer for the Wikidata5M graph of 5M nodes and 20M edges.
from pykeen.datasets import Wikidata5M
- dataset = Wikidata5M(create_inverse_triples=True)
+ dataset = Wikidata5M(use_inverse_relations=True)
model = NodePiece(
triples_factory=dataset.training,
diff --git a/docs/source/tutorial/running_ablation.rst b/docs/source/tutorial/running_ablation.rst
index e3df41fe4e..f73dbe5ef0 100644
--- a/docs/source/tutorial/running_ablation.rst
+++ b/docs/source/tutorial/running_ablation.rst
@@ -68,7 +68,7 @@ as ``title`` are special and used by PyKEEN and :mod:`optuna`.
... )
As mentioned above, we also want to measure the effect of explicitly modeling inverse relations on the model's
-performance. Therefore, we extend the ablation study by including the ``create_inverse_triples`` argument:
+performance. Therefore, we extend the ablation study by including the ``use_inverse_relations`` argument:
.. code-block:: python
@@ -82,7 +82,7 @@ performance. Therefore, we extend the ablation study by including the ``create_i
... training_loops=["LCWA"],
... optimizers=["Adam"],
... # Add inverse triples with
- ... create_inverse_triples=[True, False],
+ ... use_inverse_relations=[True, False],
... # Fast testing configuration, make bigger in prod
... epochs=1,
... n_trials=1,
@@ -91,10 +91,10 @@ performance. Therefore, we extend the ablation study by including the ``create_i
.. note::
Unlike ``models``, ``datasets``, ``losses``, ``training_loops``, and ``optimizers``,
- ``create_inverse_triples`` has a default value, which is ``False``.
+ ``use_inverse_relations`` has a default value, which is ``False``.
If there is only one value for either the ``models``, ``datasets``, ``losses``, ``training_loops``, ``optimizers``,
-or ``create_inverse_triples`` argument, it can be given as a single value instead of the list.
+or ``use_inverse_relations`` argument, it can be given as a single value instead of the list.
.. code-block:: python
@@ -107,7 +107,7 @@ or ``create_inverse_triples`` argument, it can be given as a single value instea
... losses=["BCEAfterSigmoidLoss", "MarginRankingLoss"],
... training_loops="LCWA",
... optimizers="Adam",
- ... create_inverse_triples=[True, False],
+ ... use_inverse_relations=[True, False],
... # Fast testing configuration, make bigger in prod
... epochs=1,
... n_trials=1,
@@ -200,7 +200,7 @@ the best model of each ablation-experiment using the argument ``best_replicates`
... losses=["BCEAfterSigmoidLoss", "MarginRankingLoss"],
... training_loops=["LCWA"],
... optimizers=["Adam"],
- ... create_inverse_triples=[True, False],
+ ... use_inverse_relations=[True, False],
... stopper="early",
... stopper_kwargs={
... "frequency": 5,
@@ -384,7 +384,7 @@ Now that we defined our own hyper-parameter values/ranges, let's have a look at
>>> losses = ["BCEAfterSigmoidLoss"]
>>> training_loops = ["lcwa"]
>>> optimizers = ["adam"]
- >>> create_inverse_triples= [True, False]
+ >>> use_inverse_relations= [True, False]
>>> stopper = "early"
>>> stopper_kwargs = {
... "frequency": 5,
@@ -513,7 +513,7 @@ defined within our program would look as follows:
"losses": ["BCEAfterSigmoidLoss", "CrossEntropyLoss"]
"training_loops": ["lcwa"],
"optimizers": ["adam"],
- "create_inverse_triples": [true,false],
+ "use_inverse_relations": [true,false],
"stopper": "early"
"stopper_kwargs": {
"frequency": 5,
diff --git a/notebooks/hello_world/hello_world.ipynb b/notebooks/hello_world/hello_world.ipynb
index fbf62b6bb1..3d3e890293 100644
--- a/notebooks/hello_world/hello_world.ipynb
+++ b/notebooks/hello_world/hello_world.ipynb
@@ -1,2558 +1,2558 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "\n",
- "\n",
- "Key Value \n",
- "\n",
- "OS posix Platform Darwin Release 21.5.0 Time Fri Aug 19 15:10:28 2022 Python 3.10.4 PyKEEN 1.9.1-dev PyKEEN Hash e7851f61 PyKEEN Branch fix-word-cloud PyTorch 1.11.0 CUDA Available? false CUDA Version N/A cuDNN Version N/A \n",
- "
"
- ],
- "text/plain": [
- ""
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "pykeen.env()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Train a Model\n",
- "\n",
- "More tutorials on training your first model can be found [here](https://pykeen.readthedocs.io/en/latest/first_steps.html).\n",
- "\n",
- "You can try switching out the model, add a `loss`, a `regularizer`, or switch the training assumption from `sLCWA` to `LCWA`. Each also has their own hyper-parameters, though PyKEEN tries to have reasonable defaults for you. The most useful one to change is the `num_epochs` in the `training_kwargs`, which is already below."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/json": {
- "ascii": false,
- "bar_format": null,
- "colour": null,
- "elapsed": 0.027060985565185547,
- "initial": 0,
- "n": 0,
- "ncols": null,
- "nrows": 25,
- "postfix": null,
- "prefix": "Training epochs on cpu",
- "rate": null,
- "total": 200,
- "unit": "epoch",
- "unit_divisor": 1000,
- "unit_scale": false
- },
- "application/vnd.jupyter.widget-view+json": {
- "model_id": "280875a095554c668513e99e147e1396",
- "version_major": 2,
- "version_minor": 0
- },
- "text/plain": [
- "Training epochs on cpu: 0%| | 0/200 [00:00\n",
+ "\n",
+ "Key Value \n",
+ "\n",
+ "OS posix Platform Darwin Release 21.5.0 Time Fri Aug 19 15:10:28 2022 Python 3.10.4 PyKEEN 1.9.1-dev PyKEEN Hash e7851f61 PyKEEN Branch fix-word-cloud PyTorch 1.11.0 CUDA Available? false CUDA Version N/A cuDNN Version N/A \n",
+ "
"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pykeen.env()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Train a Model\n",
+ "\n",
+ "More tutorials on training your first model can be found [here](https://pykeen.readthedocs.io/en/latest/first_steps.html).\n",
+ "\n",
+ "You can try switching out the model, add a `loss`, a `regularizer`, or switch the training assumption from `sLCWA` to `LCWA`. Each also has their own hyper-parameters, though PyKEEN tries to have reasonable defaults for you. The most useful one to change is the `num_epochs` in the `training_kwargs`, which is already below."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/json": {
+ "ascii": false,
+ "bar_format": null,
+ "colour": null,
+ "elapsed": 0.027060985565185547,
+ "initial": 0,
+ "n": 0,
+ "ncols": null,
+ "nrows": 25,
+ "postfix": null,
+ "prefix": "Training epochs on cpu",
+ "rate": null,
+ "total": 200,
+ "unit": "epoch",
+ "unit_divisor": 1000,
+ "unit_scale": false
+ },
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "280875a095554c668513e99e147e1396",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "Training epochs on cpu: 0%| | 0/200 [00:00\n",
+ "\n",
+ "\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " 2022-08-19T15:10:47.381847 \n",
+ " image/svg+xml \n",
+ " \n",
+ " \n",
+ " Matplotlib v3.5.2, https://matplotlib.org/ \n",
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+ ""
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+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "result.plot_losses()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Look at the result. These are pretty tricky to interpret, so remember:\n",
+ "\n",
+ "- adjusted mean rank is between [0, 2]. Closer to 0 is better!\n",
+ "- mean rank is a positive integer, with a bound based on the number of entities. Closer to 0 is better!\n",
+ "- hits@k is reported between [0, 1] and interpreted as a percentage. Closer to 1 is better!"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
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\n",
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\n",
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\n",
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\n",
+ "\n",
+ "usa \n",
+ "uk \n",
+ "ussr \n",
+ "netherlands \n",
+ "india \n",
+ "poland \n",
+ "egypt \n",
+ "brazil \n",
+ "israel \n",
+ "china \n",
+ "cuba \n",
+ "indonesia \n",
+ "jordan \n",
+ "burma \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "tf.entity_word_cloud()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/svg+xml": [
+ "\n",
+ "\n",
+ "embassy \n",
+ "commonbloc1 \n",
+ "relngo \n",
+ "relintergovorgs \n",
+ "intergovorgs3 \n",
+ "timesinceally \n",
+ "ngoorgs3 \n",
+ "intergovorgs \n",
+ "reldiplomacy \n",
+ "independence \n",
+ "conferences \n",
+ "ngo \n",
+ "weightedunvote \n",
+ "blockpositionindex \n",
+ "commonbloc2 \n",
+ "treaties \n",
+ "reltreaties \n",
+ "unweightedunvote \n",
+ "relexports \n",
+ "negativebehavior \n",
+ "exports3 \n",
+ "commonbloc0 \n",
+ "booktranslations \n",
+ "officialvisits \n",
+ "relbooktranslations \n",
+ "tourism \n",
+ "accusation \n",
+ "timesincewar \n",
+ "reltourism \n",
+ "pprotests \n",
+ "militaryalliance \n",
+ "nonviolentbehavior \n",
+ "negativecomm \n",
+ "tourism3 \n",
+ "students \n",
+ "exportbooks \n",
+ "relexportbooks \n",
+ "releconomicaid \n",
+ "relstudents \n",
+ "economicaid \n",
+ "eemigrants \n",
+ "boycottembargo \n",
+ "emigrants3 \n",
+ "duration \n",
+ "militaryactions \n",
+ "violentactions \n",
+ "relemigrants \n",
+ "dependent \n",
+ "expeldiplomats \n",
+ "unoffialacts \n",
+ "warning \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 12,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "tf.relation_word_cloud()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "testing_mapped_triples = Nations().testing.mapped_triples.to(model.device)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {},
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+ " 12 \n",
+ " usa \n",
+ " -1.294233 \n",
+ " True \n",
+ " False \n",
+ " \n",
+ " \n",
+ " ... \n",
+ " ... \n",
+ " ... \n",
+ " ... \n",
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+ " \n",
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+ " eemigrants \n",
+ " 1 \n",
+ " burma \n",
+ " -4.371924 \n",
+ " False \n",
+ " False \n",
+ " \n",
+ " \n",
+ " 10776 \n",
+ " 5 \n",
+ " india \n",
+ " 19 \n",
+ " independence \n",
+ " 5 \n",
+ " india \n",
+ " -4.388505 \n",
+ " False \n",
+ " False \n",
+ " \n",
+ " \n",
+ " 10777 \n",
+ " 2 \n",
+ " china \n",
+ " 27 \n",
+ " ngo \n",
+ " 2 \n",
+ " china \n",
+ " -4.428998 \n",
+ " False \n",
+ " False \n",
+ " \n",
+ " \n",
+ " 10778 \n",
+ " 0 \n",
+ " brazil \n",
+ " 12 \n",
+ " economicaid \n",
+ " 13 \n",
+ " ussr \n",
+ " -4.489155 \n",
+ " False \n",
+ " False \n",
+ " \n",
+ " \n",
+ " 10779 \n",
+ " 1 \n",
+ " burma \n",
+ " 19 \n",
+ " independence \n",
+ " 1 \n",
+ " burma \n",
+ " -4.633777 \n",
+ " False \n",
+ " False \n",
+ " \n",
+ " \n",
+ "
\n",
+ "10780 rows × 9 columns
\n",
+ ""
+ ],
+ "text/plain": [
+ " head_id head_label relation_id relation_label tail_id \\\n",
+ "0 5 india 2 attackembassy 6 \n",
+ "1 11 uk 24 militaryalliance 9 \n",
+ "2 7 israel 22 lostterritory 8 \n",
+ "3 10 poland 22 lostterritory 13 \n",
+ "4 13 ussr 6 commonbloc0 12 \n",
+ "... ... ... ... ... ... \n",
+ "10775 12 usa 13 eemigrants 1 \n",
+ "10776 5 india 19 independence 5 \n",
+ "10777 2 china 27 ngo 2 \n",
+ "10778 0 brazil 12 economicaid 13 \n",
+ "10779 1 burma 19 independence 1 \n",
+ "\n",
+ " tail_label score in_training in_testing \n",
+ "0 indonesia -1.138494 True False \n",
+ "1 netherlands -1.231564 True False \n",
+ "2 jordan -1.267689 True False \n",
+ "3 ussr -1.276796 True False \n",
+ "4 usa -1.294233 True False \n",
+ "... ... ... ... ... \n",
+ "10775 burma -4.371924 False False \n",
+ "10776 india -4.388505 False False \n",
+ "10777 china -4.428998 False False \n",
+ "10778 ussr -4.489155 False False \n",
+ "10779 burma -4.633777 False False \n",
+ "\n",
+ "[10780 rows x 9 columns]"
+ ]
+ },
+ "execution_count": 17,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Score all triples\n",
+ "model.get_all_prediction_df(triples_factory=tf, testing=testing_mapped_triples)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.4"
+ }
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- "Evaluating on cpu: 0%| | 0.00/201 [00:00\n",
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- "metadata": {},
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- ],
- "source": [
- "result.plot_losses()\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Look at the result. These are pretty tricky to interpret, so remember:\n",
- "\n",
- "- adjusted mean rank is between [0, 2]. Closer to 0 is better!\n",
- "- mean rank is a positive integer, with a bound based on the number of entities. Closer to 0 is better!\n",
- "- hits@k is reported between [0, 1] and interpreted as a percentage. Closer to 1 is better!"
- ]
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- ]
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- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
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- "\n",
- "embassy \n",
- "commonbloc1 \n",
- "relngo \n",
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- "relexportbooks \n",
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- "relstudents \n",
- "economicaid \n",
- "eemigrants \n",
- "boycottembargo \n",
- "emigrants3 \n",
- "duration \n",
- "militaryactions \n",
- "violentactions \n",
- "relemigrants \n",
- "dependent \n",
- "expeldiplomats \n",
- "unoffialacts \n",
- "warning \n",
- " "
- ],
- "text/plain": [
- ""
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "tf.relation_word_cloud()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [],
- "source": [
- "testing_mapped_triples = Nations().testing.mapped_triples.to(model.device)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "data": {
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- " 6 \n",
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- " 1 \n",
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- " -3.261366 \n",
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- " jordan \n",
- " -3.528769 \n",
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- "
\n",
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- "
\n",
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- " \n",
- " head_id \n",
- " head_label \n",
- " score \n",
- " in_training \n",
- " in_testing \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " 10 \n",
- " 10 \n",
- " poland \n",
- " -2.129169 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 3 \n",
- " 3 \n",
- " cuba \n",
- " -2.224976 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 13 \n",
- " 13 \n",
- " ussr \n",
- " -2.242457 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 12 \n",
- " 12 \n",
- " usa \n",
- " -2.284824 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 5 \n",
- " 5 \n",
- " india \n",
- " -2.410077 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 11 \n",
- " 11 \n",
- " uk \n",
- " -2.813856 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 6 \n",
- " 6 \n",
- " indonesia \n",
- " -2.837616 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 2 \n",
- " 2 \n",
- " china \n",
- " -2.893122 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 4 \n",
- " 4 \n",
- " egypt \n",
- " -2.944993 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 9 \n",
- " 9 \n",
- " netherlands \n",
- " -2.984741 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 7 \n",
- " 7 \n",
- " israel \n",
- " -3.278340 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 1 \n",
- " 1 \n",
- " burma \n",
- " -3.328085 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 8 \n",
- " 8 \n",
- " jordan \n",
- " -3.355240 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 0 \n",
- " 0 \n",
- " brazil \n",
- " -3.428868 \n",
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- " \n",
- "
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- "
\n",
- " \n",
- " \n",
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- " head_label \n",
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- " score \n",
- " in_training \n",
- " in_testing \n",
- " \n",
- " \n",
- " \n",
- " \n",
- " 0 \n",
- " 5 \n",
- " india \n",
- " 2 \n",
- " attackembassy \n",
- " 6 \n",
- " indonesia \n",
- " -1.138494 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 1 \n",
- " 11 \n",
- " uk \n",
- " 24 \n",
- " militaryalliance \n",
- " 9 \n",
- " netherlands \n",
- " -1.231564 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 2 \n",
- " 7 \n",
- " israel \n",
- " 22 \n",
- " lostterritory \n",
- " 8 \n",
- " jordan \n",
- " -1.267689 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 3 \n",
- " 10 \n",
- " poland \n",
- " 22 \n",
- " lostterritory \n",
- " 13 \n",
- " ussr \n",
- " -1.276796 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " 4 \n",
- " 13 \n",
- " ussr \n",
- " 6 \n",
- " commonbloc0 \n",
- " 12 \n",
- " usa \n",
- " -1.294233 \n",
- " True \n",
- " False \n",
- " \n",
- " \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " ... \n",
- " \n",
- " \n",
- " 10775 \n",
- " 12 \n",
- " usa \n",
- " 13 \n",
- " eemigrants \n",
- " 1 \n",
- " burma \n",
- " -4.371924 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 10776 \n",
- " 5 \n",
- " india \n",
- " 19 \n",
- " independence \n",
- " 5 \n",
- " india \n",
- " -4.388505 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 10777 \n",
- " 2 \n",
- " china \n",
- " 27 \n",
- " ngo \n",
- " 2 \n",
- " china \n",
- " -4.428998 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 10778 \n",
- " 0 \n",
- " brazil \n",
- " 12 \n",
- " economicaid \n",
- " 13 \n",
- " ussr \n",
- " -4.489155 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- " 10779 \n",
- " 1 \n",
- " burma \n",
- " 19 \n",
- " independence \n",
- " 1 \n",
- " burma \n",
- " -4.633777 \n",
- " False \n",
- " False \n",
- " \n",
- " \n",
- "
\n",
- "10780 rows × 9 columns
\n",
- ""
- ],
- "text/plain": [
- " head_id head_label relation_id relation_label tail_id \\\n",
- "0 5 india 2 attackembassy 6 \n",
- "1 11 uk 24 militaryalliance 9 \n",
- "2 7 israel 22 lostterritory 8 \n",
- "3 10 poland 22 lostterritory 13 \n",
- "4 13 ussr 6 commonbloc0 12 \n",
- "... ... ... ... ... ... \n",
- "10775 12 usa 13 eemigrants 1 \n",
- "10776 5 india 19 independence 5 \n",
- "10777 2 china 27 ngo 2 \n",
- "10778 0 brazil 12 economicaid 13 \n",
- "10779 1 burma 19 independence 1 \n",
- "\n",
- " tail_label score in_training in_testing \n",
- "0 indonesia -1.138494 True False \n",
- "1 netherlands -1.231564 True False \n",
- "2 jordan -1.267689 True False \n",
- "3 ussr -1.276796 True False \n",
- "4 usa -1.294233 True False \n",
- "... ... ... ... ... \n",
- "10775 burma -4.371924 False False \n",
- "10776 india -4.388505 False False \n",
- "10777 china -4.428998 False False \n",
- "10778 ussr -4.489155 False False \n",
- "10779 burma -4.633777 False False \n",
- "\n",
- "[10780 rows x 9 columns]"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Score all triples\n",
- "model.get_all_prediction_df(triples_factory=tf, testing=testing_mapped_triples)"
- ]
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3 (ipykernel)",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.10.4"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
\ No newline at end of file
diff --git a/src/pykeen/ablation/ablation.py b/src/pykeen/ablation/ablation.py
index 4272062ac3..94310f9537 100644
--- a/src/pykeen/ablation/ablation.py
+++ b/src/pykeen/ablation/ablation.py
@@ -36,7 +36,7 @@ def ablation_pipeline(
training_loops: Union[str, List[str]],
*,
epochs: Optional[int] = None,
- create_inverse_triples: Union[bool, List[bool]] = False,
+ use_inverse_relations: Union[bool, List[bool]] = False,
regularizers: Union[None, str, List[str]] = None,
negative_sampler: Union[str, None] = None,
evaluator: Optional[str] = None,
@@ -80,7 +80,7 @@ def ablation_pipeline(
:param optimizers: An optimizer name or list of optimizer names.
:param training_loops: A training loop name or list of training loop names.
:param epochs: A quick way to set the ``num_epochs`` in the training kwargs.
- :param create_inverse_triples: Either a boolean for a single entry or a list of booleans.
+ :param use_inverse_relations: Either a boolean for a single entry or a list of booleans.
:param regularizers: A regularizer name, list of regularizer names, or None if no regularizer is desired.
:param negative_sampler: A negative sampler name, list of regularizer names, or None if no negative sampler
is desired. Negative sampling is used only in combination with :class:`pykeen.training.SLCWATrainingLoop`.
@@ -148,7 +148,7 @@ def ablation_pipeline(
optimizers=optimizers,
training_loops=training_loops,
epochs=epochs,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
regularizers=regularizers,
model_to_model_kwargs=model_to_model_kwargs,
model_to_model_kwargs_ranges=model_to_model_kwargs_ranges,
@@ -324,7 +324,7 @@ def prepare_ablation( # noqa:C901
directory: Union[str, pathlib.Path],
*,
epochs: Optional[int] = None,
- create_inverse_triples: Union[bool, List[bool]] = False,
+ use_inverse_relations: Union[bool, List[bool]] = False,
regularizers: Union[None, str, List[str], List[None]] = None,
negative_sampler: Optional[str] = None,
evaluator: Optional[str] = None,
@@ -362,7 +362,7 @@ def prepare_ablation( # noqa:C901
:param optimizers: An optimizer name or list of optimizer names.
:param training_loops: A training loop name or list of training loop names.
:param epochs: A quick way to set the ``num_epochs`` in the training kwargs.
- :param create_inverse_triples: Either a boolean for a single entry or a list of booleans.
+ :param use_inverse_relations: Either a boolean for a single entry or a list of booleans.
:param regularizers: A regularizer name, list of regularizer names, or None if no regularizer is desired.
:param negative_sampler: A negative sampler name, list of regularizer names, or None if no negative sampler
is desired. Negative sampling is used only in combination with the pykeen.training.sclwa training loop.
@@ -423,8 +423,8 @@ def prepare_ablation( # noqa:C901
directory = normalize_path(path=directory)
if isinstance(datasets, str):
datasets = [datasets]
- if isinstance(create_inverse_triples, bool):
- create_inverse_triples = [create_inverse_triples]
+ if isinstance(use_inverse_relations, bool):
+ use_inverse_relations = [use_inverse_relations]
if isinstance(models, str):
models = [models]
if isinstance(losses, str):
@@ -440,7 +440,7 @@ def prepare_ablation( # noqa:C901
it = itt.product(
datasets,
- create_inverse_triples,
+ use_inverse_relations,
models,
losses,
regularizers,
@@ -456,7 +456,7 @@ def prepare_ablation( # noqa:C901
directories = []
for counter, (
dataset,
- create_inverse_triples,
+ use_inverse_relations,
model,
loss,
regularizer,
@@ -515,8 +515,8 @@ def _set_arguments(config: Optional[Mapping3D], key: str, value: str) -> None:
"the paths to the training, testing, and validation data.",
)
logger.info(f"Dataset: {dataset}")
- hpo_config["dataset_kwargs"] = dict(create_inverse_triples=create_inverse_triples)
- logger.info(f"Add inverse triples: {create_inverse_triples}")
+ hpo_config["dataset_kwargs"] = dict(use_inverse_relations=use_inverse_relations)
+ logger.info(f"Add inverse triples: {use_inverse_relations}")
hpo_config["model"] = model
hpo_config["model_kwargs"] = model_to_model_kwargs.get(model, {})
diff --git a/src/pykeen/contrib/lightning.py b/src/pykeen/contrib/lightning.py
index f6cc2bf22e..3c3228bd3e 100644
--- a/src/pykeen/contrib/lightning.py
+++ b/src/pykeen/contrib/lightning.py
@@ -13,7 +13,7 @@
model = LitLCWAModule(
dataset="fb15k237",
- dataset_kwargs=dict(create_inverse_triples=True),
+ dataset_kwargs=dict(use_inverse_relations=True),
model="mure",
model_kwargs=dict(embedding_dim=128, loss="bcewithlogits"),
batch_size=128,
@@ -306,7 +306,7 @@ def lit_pipeline(
@click.command()
@lit_module_resolver.get_option("-tl", "--training-loop")
@dataset_resolver.get_option("--dataset", default="nations")
-@options.inverse_triples_option
+@options.use_inverse_relations_option
@model_resolver.get_option("-m", "--model", default="mure")
@loss_resolver.get_option("-l", "--loss", default="bcewithlogits")
@options.batch_size_option
@@ -317,7 +317,7 @@ def lit_pipeline(
def _main(
training_loop: HintOrType[LitModule],
dataset: HintOrType[Dataset],
- create_inverse_triples: bool,
+ use_inverse_relations: bool,
model: HintOrType[Model],
loss: HintOrType[Loss],
batch_size: int,
@@ -330,9 +330,8 @@ def _main(
training_loop=training_loop,
training_loop_kwargs=dict(
dataset=dataset,
- dataset_kwargs=dict(create_inverse_triples=create_inverse_triples),
model=model,
- model_kwargs=dict(embedding_dim=embedding_dim, loss=loss),
+ model_kwargs=dict(embedding_dim=embedding_dim, loss=loss, use_inverse_relations=use_inverse_relations),
batch_size=batch_size,
),
trainer_kwargs=dict(
diff --git a/src/pykeen/datasets/base.py b/src/pykeen/datasets/base.py
index a986dce58a..0418eb6c00 100644
--- a/src/pykeen/datasets/base.py
+++ b/src/pykeen/datasets/base.py
@@ -90,7 +90,7 @@ def __eq__(self, __o: object) -> bool: # noqa: D105
and (self.training == __o.training)
and (self.testing == __o.testing)
and ((self.validation is None and __o.validation is None) or (self.validation == __o.validation))
- and (self.create_inverse_triples == __o.create_inverse_triples)
+ and (self.use_inverse_relations == __o.use_inverse_relations)
)
@property
@@ -129,9 +129,9 @@ def num_relations(self): # noqa: D401
return self.training.num_relations
@property
- def create_inverse_triples(self):
+ def use_inverse_relations(self):
"""Return whether inverse triples are created *for the training factory*."""
- return self.training.create_inverse_triples
+ return self.training.use_inverse_relations
@classmethod
def docdata(cls, *parts: str) -> Any:
@@ -165,7 +165,7 @@ def summary_str(self, title: Optional[str] = None, show_examples: Optional[int]
n_triples = sum(count for *_, count in rows)
rows.append(("Total", "-", "-", n_triples))
t = tabulate(rows, headers=["Name", "Entities", "Relations", "Triples"])
- rv = f"{title or self.__class__.__name__} (create_inverse_triples={self.create_inverse_triples})\n{t}"
+ rv = f"{title or self.__class__.__name__} (use_inverse_relations={self.use_inverse_relations})\n{t}"
if show_examples:
if not isinstance(self.training, TriplesFactory):
raise AttributeError(f"{self.training.__class__} does not have labeling information.")
@@ -184,7 +184,7 @@ def iter_extra_repr(self) -> Iterable[str]:
"""Yield extra entries for the instance's string representation."""
yield f"num_entities={self.num_entities}"
yield f"num_relations={self.num_relations}"
- yield f"create_inverse_triples={self.create_inverse_triples}"
+ yield f"use_inverse_relations={self.use_inverse_relations}"
@classmethod
def from_path(cls, path: Union[str, pathlib.Path], ratios: Optional[List[float]] = None) -> "Dataset":
@@ -394,7 +394,7 @@ def __init__(
testing_path: Union[str, pathlib.Path],
validation_path: Union[None, str, pathlib.Path],
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
load_triples_kwargs: Optional[Mapping[str, Any]] = None,
) -> None:
"""Initialize the dataset.
@@ -403,7 +403,7 @@ def __init__(
:param testing_path: Path to the testing triples file or testing triples file.
:param validation_path: Path to the validation triples file or validation triples file.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param load_triples_kwargs: Arguments to pass through to :func:`TriplesFactory.from_path`
and ultimately through to :func:`pykeen.triples.utils.load_triples`.
"""
@@ -411,7 +411,7 @@ def __init__(
self.testing_path = pathlib.Path(testing_path)
self.validation_path = pathlib.Path(validation_path) if validation_path else None
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
self.load_triples_kwargs = load_triples_kwargs
if eager:
@@ -421,7 +421,7 @@ def __init__(
def _load(self) -> None:
self._training = TriplesFactory.from_path(
path=self.training_path,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
load_triples_kwargs=self.load_triples_kwargs,
)
self._testing = TriplesFactory.from_path(
@@ -429,7 +429,7 @@ def _load(self) -> None:
entity_to_id=self._training.entity_to_id, # share entity index with training
relation_to_id=self._training.relation_to_id, # share relation index with training
# do not explicitly create inverse triples for testing; this is handled by the evaluation code
- create_inverse_triples=False,
+ use_inverse_relations=False,
load_triples_kwargs=self.load_triples_kwargs,
)
@@ -445,7 +445,7 @@ def _load_validation(self) -> None:
entity_to_id=self._training.entity_to_id, # share entity index with training
relation_to_id=self._training.relation_to_id, # share relation index with training
# do not explicitly create inverse triples for testing; this is handled by the evaluation code
- create_inverse_triples=False,
+ use_inverse_relations=False,
load_triples_kwargs=self.load_triples_kwargs,
)
@@ -467,7 +467,7 @@ def __init__(
cache_root: Optional[str] = None,
force: bool = False,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
load_triples_kwargs: Optional[Mapping[str, Any]] = None,
download_kwargs: Optional[Mapping[str, Any]] = None,
):
@@ -481,7 +481,7 @@ def __init__(
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.data/pykeen``.
:param force: If true, redownload any cached files
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param load_triples_kwargs: Arguments to pass through to :func:`TriplesFactory.from_path`
and ultimately through to :func:`pykeen.triples.utils.load_triples`.
:param download_kwargs: Keyword arguments to pass to :func:`pystow.utils.download`
@@ -512,7 +512,7 @@ def __init__(
testing_path=testing_path,
validation_path=validation_path,
eager=eager,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
load_triples_kwargs=load_triples_kwargs,
)
@@ -528,7 +528,7 @@ def __init__(
relative_validation_path: Union[str, pathlib.PurePath],
cache_root: Optional[str] = None,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
):
"""Initialize dataset.
@@ -541,7 +541,7 @@ def __init__(
An optional directory to store the extracted files. Is none is given, the default PyKEEN directory is used.
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.data/pykeen``.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
"""
self.cache_root = self._help_cache(cache_root)
@@ -556,7 +556,7 @@ def __init__(
testing_path=testing_path,
validation_path=validation_path,
eager=eager,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
)
def _get_paths(self) -> Tuple[pathlib.Path, pathlib.Path, pathlib.Path]: # noqa: D401
@@ -617,7 +617,7 @@ def __init__(
name: Optional[str] = None,
cache_root: Optional[str] = None,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
):
"""Initialize dataset.
@@ -632,7 +632,7 @@ def __init__(
An optional directory to store the extracted files. Is none is given, the default PyKEEN directory is used.
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.pykeen``.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:raises ValueError: if there's no URL specified and there is no data already at the calculated path
"""
@@ -649,7 +649,7 @@ def __init__(
self.relative_training_path = pathlib.PurePath(relative_training_path)
self.relative_testing_path = pathlib.PurePath(relative_testing_path)
self.relative_validation_path = pathlib.PurePath(relative_validation_path)
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
if eager:
self._load()
self._load_validation()
@@ -695,7 +695,7 @@ def _load_helper(
)
return TriplesFactory.from_labeled_triples(
triples=df.values,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
metadata={"path": relative_path},
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
@@ -714,7 +714,7 @@ def __init__(
name: Optional[str] = None,
cache_root: Optional[str] = None,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
delimiter: Optional[str] = None,
random_state: TorchRandomHint = None,
):
@@ -729,7 +729,7 @@ def __init__(
:param cache_root:
An optional directory to store the extracted files. Is none is given, the default PyKEEN directory is used.
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.pykeen``.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param eager: Should the data be loaded eagerly? Defaults to false.
:param random_state: An optional random state to make the training/testing/validation split reproducible.
:param delimiter:
@@ -741,7 +741,7 @@ def __init__(
self.random_state = random_state
self.delimiter = delimiter or "\t"
self.url = url
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
self._relative_path = pathlib.PurePosixPath(relative_path)
if eager:
@@ -755,7 +755,7 @@ def _load(self) -> None:
tf_path = self._get_path()
tf = TriplesFactory.from_labeled_triples(
triples=df.values,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
metadata={"path": tf_path},
)
self._training, self._testing, self._validation = cast(
@@ -822,7 +822,7 @@ def __init__(
self,
cache_root: Optional[str] = None,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
random_state: TorchRandomHint = None,
):
"""Initialize dataset.
@@ -831,14 +831,14 @@ def __init__(
An optional directory to store the extracted files. Is none is given, the default PyKEEN directory is used.
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.pykeen``.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param random_state: An optional random state to make the training/testing/validation split reproducible.
"""
self.cache_root = self._help_cache(cache_root)
self._triples_factory = None
self.random_state = random_state
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
self._training = None
self._testing = None
self._validation = None
@@ -857,7 +857,7 @@ def _load(self) -> None:
path = self._get_path()
tf = TriplesFactory.from_labeled_triples(
triples=df.values,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
metadata=dict(path=path) if path else None,
)
self._training, self._testing, self._validation = cast(
@@ -887,7 +887,7 @@ def __init__(
name: Optional[str] = None,
cache_root: Optional[str] = None,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
random_state: TorchRandomHint = None,
download_kwargs: Optional[Dict[str, Any]] = None,
read_csv_kwargs: Optional[Dict[str, Any]] = None,
@@ -902,7 +902,7 @@ def __init__(
An optional directory to store the extracted files. Is none is given, the default PyKEEN directory is used.
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.pykeen``.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param random_state: An optional random state to make the training/testing/validation split reproducible.
:param download_kwargs: Keyword arguments to pass through to :func:`pystow.utils.download`.
:param read_csv_kwargs: Keyword arguments to pass through to :func:`pandas.read_csv`.
@@ -911,7 +911,7 @@ def __init__(
"""
super().__init__(
cache_root=cache_root,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
random_state=random_state,
eager=False, # because it gets hooked below
)
diff --git a/src/pykeen/datasets/ea/base.py b/src/pykeen/datasets/ea/base.py
index b40e04af2e..ae2c0571a5 100644
--- a/src/pykeen/datasets/ea/base.py
+++ b/src/pykeen/datasets/ea/base.py
@@ -30,7 +30,7 @@ def __init__(
self,
*,
side: Optional[EASide] = EA_SIDE_LEFT,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
random_state: TorchRandomHint = 0,
split_ratios: Tuple[float, float, float] = (0.8, 0.1, 0.1),
combination: HintOrType[GraphPairCombinator] = None,
@@ -43,7 +43,7 @@ def __init__(
:param side:
the side, if only a single graph should be considered, or `None` to combine the two graphs into a
single one, using `combination`.
- :param create_inverse_triples:
+ :param use_inverse_relations:
whether to create inverse triples.
:param random_state:
the random state to use for reproducible splits
@@ -86,7 +86,7 @@ def __init__(
# split
training, testing, validation = tf.split(ratios=split_ratios, random_state=random_state)
# create inverse triples only for training
- training.create_inverse_triples = create_inverse_triples
+ training.use_inverse_relations = use_inverse_relations
super().__init__(training=training, testing=testing, validation=validation, **kwargs)
@abstractmethod
diff --git a/src/pykeen/datasets/inductive/base.py b/src/pykeen/datasets/inductive/base.py
index 1cf11eb661..83dd77886b 100644
--- a/src/pykeen/datasets/inductive/base.py
+++ b/src/pykeen/datasets/inductive/base.py
@@ -42,7 +42,7 @@ class InductiveDataset:
#: A factory wrapping the validation triples, that share indices with the INDUCTIVE INFERENCE triples
inductive_validation: Optional[CoreTriplesFactory] = None
#: All datasets should take care of inverse triple creation
- create_inverse_triples: bool = True
+ use_inverse_relations: bool = True
def _summary_rows(self):
return [
@@ -64,7 +64,7 @@ def summary_str(self, title: Optional[str] = None, show_examples: Optional[int]
n_triples = sum(count for *_, count in rows)
rows.append(("Total", "-", "-", n_triples))
t = tabulate(rows, headers=["Name", "Entities", "Relations", "Triples"])
- rv = f"{title or self.__class__.__name__} (create_inverse_triples={self.create_inverse_triples})\n{t}"
+ rv = f"{title or self.__class__.__name__} (use_inverse_relations={self.use_inverse_relations})\n{t}"
if show_examples:
if not isinstance(self.transductive_training, TriplesFactory):
raise AttributeError(f"{self.transductive_training.__class__} does not have labeling information.")
@@ -94,7 +94,7 @@ class EagerInductiveDataset(InductiveDataset):
inductive_inference: CoreTriplesFactory
inductive_testing: CoreTriplesFactory
inductive_validation: Optional[CoreTriplesFactory] = None
- create_inverse_triples: bool = True
+ use_inverse_relations: bool = True
class LazyInductiveDataset(InductiveDataset):
@@ -203,7 +203,7 @@ def __init__(
inductive_testing_path: Union[str, pathlib.Path],
inductive_validation_path: Union[str, str, pathlib.Path],
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
load_triples_kwargs: Optional[Mapping[str, Any]] = None,
) -> None:
"""Initialize the dataset.
@@ -213,7 +213,7 @@ def __init__(
:param inductive_testing_path: Path to the testing triples file or testing triples file.
:param inductive_validation_path: Path to the validation triples file or validation triples file.
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param load_triples_kwargs: Arguments to pass through to :func:`TriplesFactory.from_path`
and ultimately through to :func:`pykeen.triples.utils.load_triples`.
"""
@@ -222,7 +222,7 @@ def __init__(
self.inductive_testing_path = pathlib.Path(inductive_testing_path)
self.inductive_validation_path = pathlib.Path(inductive_validation_path)
- self.create_inverse_triples = create_inverse_triples
+ self.use_inverse_relations = use_inverse_relations
self.load_triples_kwargs = load_triples_kwargs
if eager:
@@ -231,14 +231,14 @@ def __init__(
def _load(self) -> None:
self._transductive_training = TriplesFactory.from_path(
path=self.transductive_training_path,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
load_triples_kwargs=self.load_triples_kwargs,
)
# important: inductive_inference shares the same RELATIONS with the transductive training graph
self._inductive_inference = TriplesFactory.from_path(
path=self.inductive_inference_path,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
relation_to_id=self._transductive_training.relation_to_id,
load_triples_kwargs=self.load_triples_kwargs,
)
@@ -249,7 +249,7 @@ def _load(self) -> None:
entity_to_id=self._inductive_inference.entity_to_id, # shares entity index with inductive inference
relation_to_id=self._inductive_inference.relation_to_id, # shares relation index with inductive inference
# do not explicitly create inverse triples for testing; this is handled by the evaluation code
- create_inverse_triples=False,
+ use_inverse_relations=False,
load_triples_kwargs=self.load_triples_kwargs,
)
@@ -259,7 +259,7 @@ def _load(self) -> None:
entity_to_id=self._inductive_inference.entity_to_id, # share entity index with inductive inference
relation_to_id=self._inductive_inference.relation_to_id, # share relation index with inductive inference
# do not explicitly create inverse triples for testing; this is handled by the evaluation code
- create_inverse_triples=False,
+ use_inverse_relations=False,
load_triples_kwargs=self.load_triples_kwargs,
)
@@ -284,7 +284,7 @@ def __init__(
cache_root: Optional[str] = None,
force: bool = False,
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
load_triples_kwargs: Optional[Mapping[str, Any]] = None,
download_kwargs: Optional[Mapping[str, Any]] = None,
version: Optional[str] = None,
@@ -300,7 +300,7 @@ def __init__(
This is defined either by the environment variable ``PYKEEN_HOME`` or defaults to ``~/.data/pykeen``.
:param force: If true, redownload any cached files
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
:param load_triples_kwargs: Arguments to pass through to :func:`TriplesFactory.from_path`
and ultimately through to :func:`pykeen.triples.utils.load_triples`.
:param download_kwargs: Keyword arguments to pass to :func:`pystow.utils.download`
@@ -336,6 +336,6 @@ def __init__(
inductive_testing_path=inductive_testing_path,
inductive_validation_path=inductive_validation_path,
eager=eager,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
load_triples_kwargs=load_triples_kwargs,
)
diff --git a/src/pykeen/datasets/inductive/ilpc2022.py b/src/pykeen/datasets/inductive/ilpc2022.py
index 32b408655c..74be29ab6e 100644
--- a/src/pykeen/datasets/inductive/ilpc2022.py
+++ b/src/pykeen/datasets/inductive/ilpc2022.py
@@ -46,7 +46,7 @@ def __init__(self, **kwargs):
inductive_inference_url=SMALL_INFERENCE_URL,
inductive_validation_url=SMALL_INFERENCE_VAL_URL,
inductive_testing_url=SMALL_INFERENCE_TEST_URL,
- create_inverse_triples=True,
+ use_inverse_relations=True,
eager=True,
**kwargs,
)
@@ -75,7 +75,7 @@ def __init__(self, **kwargs):
inductive_inference_url=LARGE_INFERENCE_URL,
inductive_validation_url=LARGE_INFERENCE_VAL_URL,
inductive_testing_url=LARGE_INFERENCE_TEST_URL,
- create_inverse_triples=True,
+ use_inverse_relations=True,
eager=True,
**kwargs,
)
diff --git a/src/pykeen/datasets/literal_base.py b/src/pykeen/datasets/literal_base.py
index 1a908efc8d..4f966a8c2c 100644
--- a/src/pykeen/datasets/literal_base.py
+++ b/src/pykeen/datasets/literal_base.py
@@ -25,7 +25,7 @@ def __init__(
validation_path: Union[str, pathlib.Path, TextIO],
literals_path: Union[str, pathlib.Path, TextIO],
eager: bool = False,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
) -> None:
"""Initialize the dataset.
@@ -34,14 +34,14 @@ def __init__(
:param validation_path: Path to the validation triples file or validation triples file.
:param literals_path: Path to the literals triples file or literal triples file
:param eager: Should the data be loaded eagerly? Defaults to false.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
"""
self.training_path = training_path
self.testing_path = testing_path
self.validation_path = validation_path
self.literals_path = literals_path
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
if eager:
self._load()
@@ -51,7 +51,7 @@ def _load(self) -> None:
self._training = self.triples_factory_cls.from_path(
path=self.training_path,
path_to_numeric_triples=self.literals_path,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
)
self._testing = self.triples_factory_cls.from_path(
path=self.testing_path,
diff --git a/src/pykeen/datasets/mocks.py b/src/pykeen/datasets/mocks.py
index 391e0283f8..9e20efa35b 100644
--- a/src/pykeen/datasets/mocks.py
+++ b/src/pykeen/datasets/mocks.py
@@ -15,7 +15,7 @@ def create_inductive_dataset(
num_triples_inference: int,
num_triples_testing: int,
random_state: int = 42,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
# num_triples_validation: Optional[int],
) -> InductiveDataset:
"""
@@ -33,7 +33,7 @@ def create_inductive_dataset(
the number of (inductive) inference triples. defaults to `num_triples_training`
:param num_triples_testing:
the number of (inductive) testing triples. defaults to `num_triples_training`
- :param create_inverse_triples:
+ :param use_inverse_relations:
whether to create inverse triples
:param random_state:
the random state to use.
@@ -46,22 +46,22 @@ def create_inductive_dataset(
num_entities=num_entities_transductive,
num_relations=num_relations,
num_triples=num_triples_training,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
random_state=random_state,
),
inductive_inference=generate_triples_factory(
num_entities=num_entities_inductive,
num_relations=num_relations,
num_triples=num_triples_inference,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
random_state=random_state + 1, # different random states for different triples
),
inductive_testing=generate_triples_factory(
num_entities=num_entities_inductive,
num_relations=num_relations,
num_triples=num_triples_testing,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
random_state=random_state + 2, # different random states for different triples
),
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
)
diff --git a/src/pykeen/datasets/ogb.py b/src/pykeen/datasets/ogb.py
index c25e86a965..aa2bea9ed3 100644
--- a/src/pykeen/datasets/ogb.py
+++ b/src/pykeen/datasets/ogb.py
@@ -28,15 +28,15 @@ class OGBLoader(LazyDataset):
#: The name of the dataset to download
name: ClassVar[str]
- def __init__(self, cache_root: Optional[str] = None, create_inverse_triples: bool = False):
+ def __init__(self, cache_root: Optional[str] = None, use_inverse_relations: bool = False):
"""Initialize the OGB loader.
:param cache_root: An optional override for where data should be cached.
If not specified, uses default PyKEEN location with :mod:`pystow`.
- :param create_inverse_triples: Should inverse triples be created? Defaults to false.
+ :param use_inverse_relations: Should inverse triples be created? Defaults to false.
"""
self.cache_root = self._help_cache(cache_root)
- self._create_inverse_triples = create_inverse_triples
+ self._use_inverse_relations = use_inverse_relations
def _load(self) -> None:
try:
@@ -77,7 +77,7 @@ def _make_tf(self, x, entity_to_id=None, relation_to_id=None):
return TriplesFactory.from_labeled_triples(
triples=triples,
- create_inverse_triples=self._create_inverse_triples,
+ use_inverse_relations=self._use_inverse_relations,
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
)
@@ -113,7 +113,7 @@ def _make_tf(self, x, entity_to_id=None, relation_to_id=None):
return TriplesFactory.from_labeled_triples(
triples=triples,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
)
diff --git a/src/pykeen/datasets/utils.py b/src/pykeen/datasets/utils.py
index 4a78fe667c..571a440346 100644
--- a/src/pykeen/datasets/utils.py
+++ b/src/pykeen/datasets/utils.py
@@ -181,14 +181,14 @@ def _digest_kwargs(dataset_kwargs: Mapping[str, Any], ignore: Collection[str] =
return base64.urlsafe_b64encode(digester.digest()).decode("utf8")[:32]
-def _set_inverse_triples_(dataset_instance: Dataset, create_inverse_triples: bool) -> Dataset:
- # note: we only need to set the create_inverse_triples in the training factory.
- if dataset_instance.create_inverse_triples and not create_inverse_triples:
+def _set_inverse_triples_(dataset_instance: Dataset, use_inverse_relations: bool) -> Dataset:
+ # note: we only need to set the use_inverse_relations in the training factory.
+ if dataset_instance.use_inverse_relations and not use_inverse_relations:
assert dataset_instance.training.num_relations % 2 == 0
dataset_instance.training.num_relations //= 2
- elif create_inverse_triples and not dataset_instance.training.create_inverse_triples:
+ elif use_inverse_relations and not dataset_instance.training.use_inverse_relations:
dataset_instance.training.num_relations *= 2
- dataset_instance.training.create_inverse_triples = create_inverse_triples
+ dataset_instance.training.use_inverse_relations = use_inverse_relations
return dataset_instance
@@ -207,7 +207,7 @@ def _cached_get_dataset(
force = force or dataset_kwargs.pop("force", False)
# hash kwargs
- digest = _digest_kwargs(dataset_kwargs, ignore={"create_inverse_triples"})
+ digest = _digest_kwargs(dataset_kwargs, ignore={"use_inverse_relations"})
# normalize dataset name
dataset_cls = dataset_resolver.lookup(dataset)
@@ -221,7 +221,7 @@ def _cached_get_dataset(
logger.info(f"Loading cached preprocessed dataset from {path.as_uri()}")
return _set_inverse_triples_(
dataset_cls.from_directory_binary(path),
- create_inverse_triples=dataset_kwargs.get("create_inverse_triples", False),
+ use_inverse_relations=dataset_kwargs.get("use_inverse_relations", False),
)
# load dataset without cache
diff --git a/src/pykeen/experiments/boxe/abboud2020_boxe_yago310.yaml b/src/pykeen/experiments/boxe/abboud2020_boxe_yago310.yaml
index 3a9ec623b6..b0ddc7a567 100644
--- a/src/pykeen/experiments/boxe/abboud2020_boxe_yago310.yaml
+++ b/src/pykeen/experiments/boxe/abboud2020_boxe_yago310.yaml
@@ -6,7 +6,7 @@ pipeline:
dataset: yago310
# introduce inverse relations and reciprocal facts
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
# optimization is using negative sampling self-adversarial loss.
diff --git a/src/pykeen/experiments/conve/dettmers2018_conve_fb15k.json b/src/pykeen/experiments/conve/dettmers2018_conve_fb15k.json
index 94cf40da25..6154c1ecdd 100644
--- a/src/pykeen/experiments/conve/dettmers2018_conve_fb15k.json
+++ b/src/pykeen/experiments/conve/dettmers2018_conve_fb15k.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "fb15k",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "ConvE",
"model_kwargs": {
diff --git a/src/pykeen/experiments/conve/dettmers2018_conve_fb15k237.json b/src/pykeen/experiments/conve/dettmers2018_conve_fb15k237.json
index 35f4c9cedc..40ab04c1f7 100644
--- a/src/pykeen/experiments/conve/dettmers2018_conve_fb15k237.json
+++ b/src/pykeen/experiments/conve/dettmers2018_conve_fb15k237.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "fb15k237",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "ConvE",
"model_kwargs": {
diff --git a/src/pykeen/experiments/conve/dettmers2018_conve_wn18.json b/src/pykeen/experiments/conve/dettmers2018_conve_wn18.json
index 66e7c53215..9f15987730 100644
--- a/src/pykeen/experiments/conve/dettmers2018_conve_wn18.json
+++ b/src/pykeen/experiments/conve/dettmers2018_conve_wn18.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "wn18",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "ConvE",
"model_kwargs": {
diff --git a/src/pykeen/experiments/conve/dettmers2018_conve_wn18rr.json b/src/pykeen/experiments/conve/dettmers2018_conve_wn18rr.json
index 9437a5e0ab..79ebc989ed 100644
--- a/src/pykeen/experiments/conve/dettmers2018_conve_wn18rr.json
+++ b/src/pykeen/experiments/conve/dettmers2018_conve_wn18rr.json
@@ -7,7 +7,7 @@
"dataset": "wn18rr",
"model": "ConvE",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model_kwargs": {
"embedding_dim": 200,
diff --git a/src/pykeen/experiments/ermlp/ali2020_ermlp_fb15k237.yaml b/src/pykeen/experiments/ermlp/ali2020_ermlp_fb15k237.yaml
index 41508e8f6f..db6110680f 100644
--- a/src/pykeen/experiments/ermlp/ali2020_ermlp_fb15k237.yaml
+++ b/src/pykeen/experiments/ermlp/ali2020_ermlp_fb15k237.yaml
@@ -4,7 +4,7 @@ metadata:
pipeline:
dataset: fb15k237
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: bceaftersigmoid
diff --git a/src/pykeen/experiments/ermlp/ali2020_ermlp_wn18rr.yaml b/src/pykeen/experiments/ermlp/ali2020_ermlp_wn18rr.yaml
index 2ff0733336..e1975c6b67 100644
--- a/src/pykeen/experiments/ermlp/ali2020_ermlp_wn18rr.yaml
+++ b/src/pykeen/experiments/ermlp/ali2020_ermlp_wn18rr.yaml
@@ -4,7 +4,7 @@ metadata:
pipeline:
dataset: wn18rr
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: softplus
diff --git a/src/pykeen/experiments/inverse_stability.py b/src/pykeen/experiments/inverse_stability.py
index 56a93ca84f..2e8623140b 100644
--- a/src/pykeen/experiments/inverse_stability.py
+++ b/src/pykeen/experiments/inverse_stability.py
@@ -64,7 +64,7 @@ def run_inverse_stability_workflow(
dataset_instance: Dataset = get_dataset(
dataset=dataset,
dataset_kwargs=dict(
- create_inverse_triples=True,
+ use_inverse_relations=True,
),
)
dataset_name = dataset_instance.get_normalized_name()
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl.yaml
index fa3436a5e9..80a90ed077 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: codexlarge
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_noancs.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_noancs.yaml
index 0022ed5c18..650a1cbd8a 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_noancs.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_noancs.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: codexlarge
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_norels.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_norels.yaml
index 4ce726eb7c..b5f0678c8e 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_norels.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_codexl_norels.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: codexlarge
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237.yaml
index b6c0254dec..67127979f2 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: fb15k237
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_noancs.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_noancs.yaml
index 2b9353603b..f2427cb8a9 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_noancs.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_noancs.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: fb15k237
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_norels.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_norels.yaml
index 97e5320563..9a93601bc3 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_norels.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_fb15k237_norels.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: fb15k237
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: BCEWithLogitsLoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr.yaml
index 1e7a3a1ecb..398f56699b 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: wn18rr
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_noancs.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_noancs.yaml
index ecf5d8510d..0bd571fc76 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_noancs.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_noancs.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: wn18rr
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_norels.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_norels.yaml
index 64ae564e1f..a99ec9e177 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_norels.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_wn18rr_norels.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: wn18rr
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310.yaml
index 3b3ffcc57f..705291f868 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: yago310
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_noancs.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_noancs.yaml
index 8f19440463..c8bac8f344 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_noancs.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_noancs.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: yago310
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_norels.yaml b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_norels.yaml
index 9b5c616990..f4e19bae50 100644
--- a/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_norels.yaml
+++ b/src/pykeen/experiments/nodepiece/galkin2022_nodepiece_yago310_norels.yaml
@@ -4,7 +4,7 @@ pipeline:
random_seed: 42
dataset: yago310
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: NSSALoss
diff --git a/src/pykeen/experiments/rescal/ali2020_rescal_fb15k237.yaml b/src/pykeen/experiments/rescal/ali2020_rescal_fb15k237.yaml
index 40210ffc8b..ded3df1598 100644
--- a/src/pykeen/experiments/rescal/ali2020_rescal_fb15k237.yaml
+++ b/src/pykeen/experiments/rescal/ali2020_rescal_fb15k237.yaml
@@ -4,7 +4,7 @@ metadata:
pipeline:
dataset: fb15k237
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: crossentropy
diff --git a/src/pykeen/experiments/rescal/ali2020_rescal_wn18rr.yaml b/src/pykeen/experiments/rescal/ali2020_rescal_wn18rr.yaml
index 4e3d8e071c..3d8ad398f8 100644
--- a/src/pykeen/experiments/rescal/ali2020_rescal_wn18rr.yaml
+++ b/src/pykeen/experiments/rescal/ali2020_rescal_wn18rr.yaml
@@ -4,7 +4,7 @@ metadata:
pipeline:
dataset: wn18rr
dataset_kwargs:
- create_inverse_triples: True
+ use_inverse_relations: True
evaluator_kwargs:
filtered: true
loss: crossentropy
diff --git a/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k.json b/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k.json
index 67209e32c9..838c2856c6 100644
--- a/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k.json
+++ b/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "fb15k",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "TuckER",
"model_kwargs": {
diff --git a/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k237.json b/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k237.json
index 1fbe3bdfb4..d35cfca864 100644
--- a/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k237.json
+++ b/src/pykeen/experiments/tucker/balazevic2019_tucker_fb15k237.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "fb15k237",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "TuckER",
"model_kwargs": {
diff --git a/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18.json b/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18.json
index 49897c0809..ef092e5f78 100644
--- a/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18.json
+++ b/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "wn18",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "TuckER",
"model_kwargs": {
diff --git a/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18rr.json b/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18rr.json
index 26c7173e3e..838c7dff42 100644
--- a/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18rr.json
+++ b/src/pykeen/experiments/tucker/balazevic2019_tucker_wn18rr.json
@@ -6,7 +6,7 @@
"pipeline": {
"dataset": "wn18rr",
"dataset_kwargs": {
- "create_inverse_triples": true
+ "use_inverse_relations": true
},
"model": "TuckER",
"model_kwargs": {
diff --git a/src/pykeen/models/base.py b/src/pykeen/models/base.py
index 784ab30e13..a8bb86a931 100644
--- a/src/pykeen/models/base.py
+++ b/src/pykeen/models/base.py
@@ -97,7 +97,7 @@ def __init__(
else:
self.loss = loss_resolver.make(loss, pos_kwargs=loss_kwargs)
- self.use_inverse_triples = triples_factory.create_inverse_triples
+ self.use_inverse_triples = triples_factory.use_inverse_relations
self.num_entities = triples_factory.num_entities
self.num_relations = triples_factory.num_relations
@@ -480,7 +480,7 @@ def _prepare_inverse_batch(self, batch: torch.LongTensor, index_relation: int) -
if not self.use_inverse_triples:
raise ValueError(
"Your model is not configured to predict with inverse relations."
- " Set ``create_inverse_triples=True`` when creating the dataset/triples factory"
+ " Set ``use_inverse_relations=True`` when creating the dataset/triples factory"
" or using the pipeline().",
)
return relation_inverter.invert_(batch=batch, index=index_relation).flip(1)
diff --git a/src/pykeen/models/cli/builders.py b/src/pykeen/models/cli/builders.py
index da0e6f0fae..79bbc118e2 100644
--- a/src/pykeen/models/cli/builders.py
+++ b/src/pykeen/models/cli/builders.py
@@ -123,7 +123,7 @@ def _decorate_model_kwargs(command: click.Command) -> click.Command:
@options.num_workers_option
@options.random_seed_option
@_decorate_model_kwargs
- @options.inverse_triples_option
+ @options.use_inverse_relations_option
@click.option("--silent", is_flag=True)
@click.option("--output-directory", type=pathlib.Path, default=None, help="Where to dump the results")
def main(
@@ -147,7 +147,7 @@ def main(
num_workers,
random_seed,
silent: bool,
- create_inverse_triples: bool,
+ use_inverse_relations: bool,
**model_kwargs,
):
"""CLI for PyKEEN."""
@@ -172,18 +172,22 @@ def main(
def _triples_factory(path: Optional[str]) -> Optional[TriplesFactory]:
if path is None:
return None
- return TriplesFactory.from_path(path=path, create_inverse_triples=create_inverse_triples)
+ return TriplesFactory.from_path(path=path, use_inverse_relations=use_inverse_relations)
training = _triples_factory(training_triples_factory)
testing = _triples_factory(testing_triples_factory)
validation = _triples_factory(validation_triples_factory)
+ if use_inverse_relations:
+ model_kwargs = model_kwargs or {}
+ model_kwargs["use_inverse_relations"] = True
+
pipeline_result = pipeline(
device=device,
model=model,
model_kwargs=model_kwargs,
dataset=dataset,
- dataset_kwargs=dict(create_inverse_triples=create_inverse_triples),
+ dataset_kwargs=dict(use_inverse_relations=use_inverse_relations),
training=training,
testing=testing or training,
validation=validation,
diff --git a/src/pykeen/models/cli/options.py b/src/pykeen/models/cli/options.py
index 06acc63bb0..ea91157ffa 100644
--- a/src/pykeen/models/cli/options.py
+++ b/src/pykeen/models/cli/options.py
@@ -182,4 +182,6 @@ def _callback(_, __, value):
show_default=True,
help="Random seed for PyTorch, NumPy, and Python.",
)
-inverse_triples_option = click.option("-I", "--create-inverse-triples", is_flag=True, help="Model inverse triples")
+use_inverse_relations_option = click.option(
+ "-I", "--use-inverse-relations", is_flag=True, help="Model inverse relations"
+)
diff --git a/src/pykeen/models/inductive/inductive_nodepiece.py b/src/pykeen/models/inductive/inductive_nodepiece.py
index 764ad55b7d..5a0c6ab9ca 100644
--- a/src/pykeen/models/inductive/inductive_nodepiece.py
+++ b/src/pykeen/models/inductive/inductive_nodepiece.py
@@ -64,13 +64,13 @@ def __init__(
Initialize the model.
:param triples_factory:
- the triples factory of training triples. Must have create_inverse_triples set to True.
+ the triples factory of training triples. Must have use_inverse_relations set to True.
:param inference_factory:
- the triples factory of inference triples. Must have create_inverse_triples set to True.
+ the triples factory of inference triples. Must have use_inverse_relations set to True.
:param validation_factory:
- the triples factory of validation triples. Must have create_inverse_triples set to True.
+ the triples factory of validation triples. Must have use_inverse_relations set to True.
:param test_factory:
- the triples factory of testing triples. Must have create_inverse_triples set to True.
+ the triples factory of testing triples. Must have use_inverse_relations set to True.
:param num_tokens:
the number of relations to use to represent each entity, cf.
:class:`pykeen.nn.NodePieceRepresentation`.
@@ -100,7 +100,7 @@ def __init__(
:raises ValueError:
if the triples factory does not create inverse triples
"""
- if not triples_factory.create_inverse_triples:
+ if not triples_factory.use_inverse_relations:
raise ValueError(
"The provided triples factory does not create inverse triples. However, for the node piece "
"representations inverse relation representations are required.",
diff --git a/src/pykeen/models/unimodal/conv_e.py b/src/pykeen/models/unimodal/conv_e.py
index 8e7473db5f..84636bb54b 100644
--- a/src/pykeen/models/unimodal/conv_e.py
+++ b/src/pykeen/models/unimodal/conv_e.py
@@ -62,7 +62,7 @@ class ConvE(ERModel):
>>> # Step 1: Get triples
>>> from pykeen.datasets import Nations
- >>> dataset = Nations(create_inverse_triples=True)
+ >>> dataset = Nations(use_inverse_relations=True)
>>> # Step 2: Configure the model
>>> from pykeen.models import ConvE
>>> model = ConvE(
@@ -139,10 +139,10 @@ def __init__(
) -> None:
"""Initialize the model."""
# ConvE should be trained with inverse triples
- if not triples_factory.create_inverse_triples:
+ if not triples_factory.use_inverse_relations:
logger.warning(
"\nThe ConvE model should be trained with inverse triples.\n"
- "This can be done by defining the TriplesFactory class with the _create_inverse_triples_ parameter set "
+ "This can be done by defining the TriplesFactory class with the _use_inverse_relations_ parameter set "
"to true.",
)
diff --git a/src/pykeen/models/unimodal/node_piece.py b/src/pykeen/models/unimodal/node_piece.py
index 90180ec971..7c58b5bc6d 100644
--- a/src/pykeen/models/unimodal/node_piece.py
+++ b/src/pykeen/models/unimodal/node_piece.py
@@ -66,7 +66,7 @@ def __init__(
Initialize the model.
:param triples_factory:
- the triples factory. Must have create_inverse_triples set to True.
+ the triples factory. Must have use_inverse_relations set to True.
:param num_tokens:
the number of relations to use to represent each entity, cf.
:class:`pykeen.nn.NodePieceRepresentation`.
@@ -114,7 +114,7 @@ def __init__(
:raises ValueError:
if the triples factory does not create inverse triples
"""
- if not triples_factory.create_inverse_triples:
+ if not triples_factory.use_inverse_relations:
raise ValueError(
"The provided triples factory does not create inverse triples. However, for the node piece "
"representations inverse relation representations are required.",
diff --git a/src/pykeen/nn/message_passing.py b/src/pykeen/nn/message_passing.py
index 014a3f4b0c..ece5cbed33 100644
--- a/src/pykeen/nn/message_passing.py
+++ b/src/pykeen/nn/message_passing.py
@@ -584,7 +584,7 @@ def __init__(
raise ValueError(
f"max_id={max_id} differs from triples_factory.num_entities={triples_factory.num_entities}"
)
- if triples_factory.create_inverse_triples:
+ if triples_factory.use_inverse_relations:
raise ValueError(
"RGCN internally creates inverse triples. It thus expects a triples factory without them.",
)
diff --git a/src/pykeen/nn/node_piece/representation.py b/src/pykeen/nn/node_piece/representation.py
index 0300f537d7..10273ee736 100644
--- a/src/pykeen/nn/node_piece/representation.py
+++ b/src/pykeen/nn/node_piece/representation.py
@@ -266,7 +266,7 @@ def __init__(
# normalize triples
mapped_triples = triples_factory.mapped_triples
- if triples_factory.create_inverse_triples:
+ if triples_factory.use_inverse_relations:
# inverse triples are created afterwards implicitly
mapped_triples = mapped_triples[mapped_triples[:, 1] < triples_factory.real_num_relations]
diff --git a/src/pykeen/nn/pyg.py b/src/pykeen/nn/pyg.py
index 7604c0bcb1..e840fa308e 100644
--- a/src/pykeen/nn/pyg.py
+++ b/src/pykeen/nn/pyg.py
@@ -26,7 +26,7 @@
from pykeen.nn.init import LabelBasedInitializer
from pykeen.pipeline import pipeline
- dataset = get_dataset(dataset="nations", dataset_kwargs=dict(create_inverse_triples=True))
+ dataset = get_dataset(dataset="nations", dataset_kwargs=dict(use_inverse_relations=True))
entity_initializer = LabelBasedInitializer.from_triples_factory(
triples_factory=dataset.training,
for_entities=True,
diff --git a/src/pykeen/nn/representation.py b/src/pykeen/nn/representation.py
index 49607f8278..45e4df65f6 100644
--- a/src/pykeen/nn/representation.py
+++ b/src/pykeen/nn/representation.py
@@ -816,7 +816,7 @@ def __init__(
"""
super().__init__()
# TODO: Check
- assert triples_factory.create_inverse_triples
+ assert triples_factory.use_inverse_relations
self.entity_representations = build_representation(
max_id=triples_factory.num_entities,
representation=entity_representations,
diff --git a/src/pykeen/triples/deteriorate.py b/src/pykeen/triples/deteriorate.py
index c818154170..38fe67e245 100644
--- a/src/pykeen/triples/deteriorate.py
+++ b/src/pykeen/triples/deteriorate.py
@@ -40,7 +40,7 @@ def deteriorate(
:raises ValueError: If a float is given for n that isn't between 0 and 1
"""
# TODO: take care that triples aren't removed that are the only ones with any given entity
- if reference.create_inverse_triples:
+ if reference.use_inverse_relations:
raise NotImplementedError
if isinstance(n, float):
diff --git a/src/pykeen/triples/generation.py b/src/pykeen/triples/generation.py
index 4ef6c84d30..24569bcdb0 100644
--- a/src/pykeen/triples/generation.py
+++ b/src/pykeen/triples/generation.py
@@ -50,7 +50,7 @@ def generate_triples_factory(
num_relations: int = 7,
num_triples: int = 101,
random_state: TorchRandomHint = None,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
) -> CoreTriplesFactory:
"""Generate a triples factory with random triples."""
mapped_triples = generate_triples(
@@ -61,5 +61,5 @@ def generate_triples_factory(
)
return CoreTriplesFactory.create(
mapped_triples=mapped_triples,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
)
diff --git a/src/pykeen/triples/leakage.py b/src/pykeen/triples/leakage.py
index 73dee84c0c..1cfca92e65 100644
--- a/src/pykeen/triples/leakage.py
+++ b/src/pykeen/triples/leakage.py
@@ -369,7 +369,7 @@ def reindex(*triples_factories: CoreTriplesFactory) -> List[CoreTriplesFactory]:
entity_translation=entity_id_translation,
relation_translation=relation_id_translation,
),
- create_inverse_triples=factory.create_inverse_triples,
+ use_inverse_relations=factory.use_inverse_relations,
)
for factory in triples_factories
]
diff --git a/src/pykeen/triples/remix.py b/src/pykeen/triples/remix.py
index 219ebddbc3..a1ccd31e2a 100644
--- a/src/pykeen/triples/remix.py
+++ b/src/pykeen/triples/remix.py
@@ -30,10 +30,10 @@ def remix(*triples_factories: CoreTriplesFactory, **kwargs) -> List[CoreTriplesF
:param kwargs: Keyword arguments to be passed to :func:`split`
:returns: A sequence of triples factories of the same sizes but randomly re-assigned triples
- :raises NotImplementedError: if any of the triples factories have ``create_inverse_triples``
+ :raises NotImplementedError: if any of the triples factories have ``use_inverse_relations``
"""
for tf in triples_factories:
- if tf.create_inverse_triples:
+ if tf.use_inverse_relations:
raise NotImplementedError("The remix algorithm is not implemented for datasets with inverse triples")
all_triples = cat_triples(*triples_factories)
diff --git a/src/pykeen/triples/triples_factory.py b/src/pykeen/triples/triples_factory.py
index e9d9352a0c..376c7b7e49 100644
--- a/src/pykeen/triples/triples_factory.py
+++ b/src/pykeen/triples/triples_factory.py
@@ -337,7 +337,7 @@ class KGInfo(ExtraReprMixin):
num_relations: int
#: whether to create inverse triples
- create_inverse_triples: bool
+ use_inverse_relations: bool
#: the number of real relations, i.e., without artificial inverses
real_num_relations: int
@@ -346,7 +346,7 @@ def __init__(
self,
num_entities: int,
num_relations: int,
- create_inverse_triples: bool,
+ use_inverse_relations: bool,
) -> None:
"""
Initialize the information object.
@@ -355,22 +355,22 @@ def __init__(
the number of entities.
:param num_relations:
the number of relations, excluding artifical inverse relations.
- :param create_inverse_triples:
+ :param use_inverse_relations:
whether to create inverse triples
"""
self.num_entities = num_entities
self.real_num_relations = num_relations
- if create_inverse_triples:
+ if use_inverse_relations:
num_relations *= 2
self.num_relations = num_relations
- self.create_inverse_triples = create_inverse_triples
+ self.use_inverse_relations = use_inverse_relations
def iter_extra_repr(self) -> Iterable[str]:
"""Iterate over extra_repr components."""
yield from super().iter_extra_repr()
yield f"num_entities={self.num_entities}"
yield f"num_relations={self.num_relations}"
- yield f"create_inverse_triples={self.create_inverse_triples}"
+ yield f"use_inverse_relations={self.use_inverse_relations}"
class CoreTriplesFactory(KGInfo):
@@ -384,7 +384,7 @@ def __init__(
mapped_triples: Union[MappedTriples, np.ndarray],
num_entities: int,
num_relations: int,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
metadata: Optional[Mapping[str, Any]] = None,
):
"""
@@ -396,7 +396,7 @@ def __init__(
The number of entities.
:param num_relations:
The number of relations.
- :param create_inverse_triples:
+ :param use_inverse_relations:
Whether to create inverse triples.
:param metadata:
Arbitrary metadata to go with the graph
@@ -409,7 +409,7 @@ def __init__(
super().__init__(
num_entities=num_entities,
num_relations=num_relations,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
)
# ensure torch.Tensor
mapped_triples = torch.as_tensor(mapped_triples)
@@ -430,7 +430,7 @@ def create(
mapped_triples: MappedTriples,
num_entities: Optional[int] = None,
num_relations: Optional[int] = None,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
metadata: Optional[Mapping[str, Any]] = None,
) -> "CoreTriplesFactory":
"""
@@ -442,7 +442,7 @@ def create(
The number of entities. If not given, inferred from mapped_triples.
:param num_relations:
The number of relations. If not given, inferred from mapped_triples.
- :param create_inverse_triples:
+ :param use_inverse_relations:
Whether to create inverse triples.
:param metadata:
Additional metadata to store in the factory.
@@ -458,7 +458,7 @@ def create(
mapped_triples=mapped_triples,
num_entities=num_entities,
num_relations=num_relations,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
metadata=metadata,
)
@@ -469,7 +469,7 @@ def __eq__(self, __o: object) -> bool: # noqa: D105
(self.num_entities == __o.num_entities)
and (self.num_relations == __o.num_relations)
and (self.num_triples == __o.num_triples)
- and (self.create_inverse_triples == __o.create_inverse_triples)
+ and (self.use_inverse_relations == __o.use_inverse_relations)
and bool((self.mapped_triples == __o.mapped_triples).all().item())
)
@@ -506,19 +506,19 @@ def with_labels(
mapped_triples=self.mapped_triples,
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
metadata=self.metadata,
)
def get_inverse_relation_id(self, relation: int) -> int:
"""Get the inverse relation identifier for the given relation."""
- if not self.create_inverse_triples:
+ if not self.use_inverse_relations:
raise ValueError("Can not get inverse triple, they have not been created.")
return relation_inverter.get_inverse_id(relation_id=relation)
def _add_inverse_triples_if_necessary(self, mapped_triples: MappedTriples) -> MappedTriples:
"""Add inverse triples if they shall be created."""
- if not self.create_inverse_triples:
+ if not self.use_inverse_relations:
return mapped_triples
logger.info("Creating inverse triples.")
@@ -579,7 +579,7 @@ def clone_and_exchange_triples(
mapped_triples: MappedTriples,
extra_metadata: Optional[Dict[str, Any]] = None,
keep_metadata: bool = True,
- create_inverse_triples: Optional[bool] = None,
+ use_inverse_relations: Optional[bool] = None,
) -> "CoreTriplesFactory":
"""
Create a new triples factory sharing everything except the triples.
@@ -594,19 +594,19 @@ def clone_and_exchange_triples(
the dictionaries will be unioned with precedence taken on keys from ``extra_metadata``.
:param keep_metadata:
Pass the current factory's metadata to the new triples factory
- :param create_inverse_triples:
+ :param use_inverse_relations:
Change inverse triple creation flag. If None, use flag from this factory.
:return:
The new factory.
"""
- if create_inverse_triples is None:
- create_inverse_triples = self.create_inverse_triples
+ if use_inverse_relations is None:
+ use_inverse_relations = self.use_inverse_relations
return CoreTriplesFactory(
mapped_triples=mapped_triples,
num_entities=self.num_entities,
num_relations=self.real_num_relations,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
metadata={
**(extra_metadata or {}),
**(self.metadata if keep_metadata else {}), # type: ignore
@@ -661,7 +661,7 @@ def split(
self.clone_and_exchange_triples(
mapped_triples=triples,
# do not explicitly create inverse triples for testing; this is handled by the evaluation code
- create_inverse_triples=None if i == 0 else False,
+ use_inverse_relations=None if i == 0 else False,
)
for i, triples in enumerate(
split(
@@ -852,9 +852,9 @@ def to_path_binary(
def _get_binary_state(self):
return dict(
num_entities=self.num_entities,
- # note: num_relations will be doubled again when instantiating with create_inverse_triples=True
+ # note: num_relations will be doubled again when instantiating with use_inverse_relations=True
num_relations=self.real_num_relations,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
metadata=self.metadata,
)
@@ -870,7 +870,7 @@ def __init__(
mapped_triples: MappedTriples,
entity_to_id: EntityMapping,
relation_to_id: RelationMapping,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
metadata: Optional[Mapping[str, Any]] = None,
num_entities: Optional[int] = None,
num_relations: Optional[int] = None,
@@ -884,7 +884,7 @@ def __init__(
The mapping from entities' labels to their indices.
:param relation_to_id:
The mapping from relations' labels to their indices.
- :param create_inverse_triples:
+ :param use_inverse_relations:
Whether to create inverse triples.
:param metadata:
Arbitrary metadata to go with the graph
@@ -917,7 +917,7 @@ def __init__(
mapped_triples=mapped_triples,
num_entities=num_entities,
num_relations=num_relations,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations = use_inverse_relations,
metadata=metadata,
)
@@ -926,7 +926,7 @@ def from_labeled_triples(
cls,
triples: LabeledTriples,
*,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
entity_to_id: Optional[EntityMapping] = None,
relation_to_id: Optional[RelationMapping] = None,
compact_id: bool = True,
@@ -938,7 +938,7 @@ def from_labeled_triples(
:param triples: shape: (n, 3), dtype: str
The label-based triples.
- :param create_inverse_triples:
+ :param use_inverse_relations:
Whether to create inverse triples.
:param entity_to_id:
The mapping from entity labels to ID. If None, create a new one from the triples.
@@ -956,7 +956,7 @@ def from_labeled_triples(
"""
# Check if the triples are inverted already
# We re-create them pure index based to ensure that _all_ inverse triples are present and that they are
- # contained if and only if create_inverse_triples is True.
+ # contained if and only if use_inverse_relations is True.
if filter_out_candidate_inverse_relations:
unique_relations, inverse = np.unique(triples[:, 1], return_inverse=True)
suspected_to_be_inverse_relations = {r for r in unique_relations if r.endswith(INVERSE_SUFFIX)}
@@ -996,7 +996,7 @@ def from_labeled_triples(
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
mapped_triples=mapped_triples,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
metadata=metadata,
)
@@ -1005,7 +1005,7 @@ def from_path(
cls,
path: Union[str, pathlib.Path, TextIO],
*,
- create_inverse_triples: bool = False,
+ use_inverse_relations: bool = False,
entity_to_id: Optional[EntityMapping] = None,
relation_to_id: Optional[RelationMapping] = None,
compact_id: bool = True,
@@ -1018,7 +1018,7 @@ def from_path(
:param path:
The path where the label-based triples are stored.
- :param create_inverse_triples:
+ :param use_inverse_relations:
Whether to create inverse triples.
:param entity_to_id:
The mapping from entity labels to ID. If None, create a new one from the triples.
@@ -1045,7 +1045,7 @@ def from_path(
return cls.from_labeled_triples(
triples=triples,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
entity_to_id=entity_to_id,
relation_to_id=relation_to_id,
compact_id=compact_id,
@@ -1069,7 +1069,7 @@ def to_core_triples_factory(self) -> CoreTriplesFactory:
mapped_triples=self.mapped_triples,
num_entities=self.num_entities,
num_relations=self.num_relations,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
metadata=self.metadata,
)
@@ -1105,21 +1105,28 @@ def _from_path_binary(cls, path: pathlib.Path) -> MutableMapping[str, Any]:
data[name] = dict(zip(df["label"], df["id"]))
return data
+ # docstr-coverage: inherited
+ def _get_binary_state(self): # noqa: D102
+ return dict(
+ use_inverse_relations=self.use_inverse_relations,
+ metadata=self.metadata,
+ )
+
# docstr-coverage: inherited
def clone_and_exchange_triples(
self,
mapped_triples: MappedTriples,
extra_metadata: Optional[Dict[str, Any]] = None,
keep_metadata: bool = True,
- create_inverse_triples: Optional[bool] = None,
+ use_inverse_relations: Optional[bool] = None,
) -> "TriplesFactory": # noqa: D102
- if create_inverse_triples is None:
- create_inverse_triples = self.create_inverse_triples
+ if use_inverse_relations is None:
+ use_inverse_relations = self.use_inverse_relations
return TriplesFactory(
entity_to_id=self.entity_to_id,
relation_to_id=self.relation_to_id,
mapped_triples=mapped_triples,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
metadata={
**(extra_metadata or {}),
**(self.metadata if keep_metadata else {}), # type: ignore
diff --git a/src/pykeen/triples/triples_numeric_literals_factory.py b/src/pykeen/triples/triples_numeric_literals_factory.py
index 933483676b..081d7407a4 100644
--- a/src/pykeen/triples/triples_numeric_literals_factory.py
+++ b/src/pykeen/triples/triples_numeric_literals_factory.py
@@ -103,7 +103,7 @@ def from_labeled_triples(
entity_to_id=base.entity_to_id,
relation_to_id=base.relation_to_id,
mapped_triples=base.mapped_triples,
- create_inverse_triples=base.create_inverse_triples,
+ use_inverse_relations=base.use_inverse_relations,
numeric_literals=numeric_literals,
literals_to_id=literals_to_id,
)
@@ -128,15 +128,15 @@ def clone_and_exchange_triples(
mapped_triples: MappedTriples,
extra_metadata: Optional[Dict[str, Any]] = None,
keep_metadata: bool = True,
- create_inverse_triples: Optional[bool] = None,
+ use_inverse_relations: Optional[bool] = None,
) -> "TriplesNumericLiteralsFactory": # noqa: D102
- if create_inverse_triples is None:
- create_inverse_triples = self.create_inverse_triples
+ if use_inverse_relations is None:
+ use_inverse_relations = self.use_inverse_relations
return TriplesNumericLiteralsFactory(
mapped_triples=mapped_triples,
entity_to_id=self.entity_to_id,
relation_to_id=self.relation_to_id,
- create_inverse_triples=create_inverse_triples,
+ use_inverse_relations=use_inverse_relations,
metadata={
**(extra_metadata or {}),
**(self.metadata if keep_metadata else {}), # type: ignore
diff --git a/tests/cases.py b/tests/cases.py
index 314145a945..adeef75724 100644
--- a/tests/cases.py
+++ b/tests/cases.py
@@ -931,7 +931,7 @@ class ModelTestCase(unittest_templates.GenericTestCase[Model]):
embedding_dim: int = 3
#: Whether to create inverse triples (needed e.g. by ConvE)
- create_inverse_triples: bool = False
+ use_inverse_relations: bool = False
#: The sampler to use for sLCWA (different e.g. for R-GCN)
sampler: Optional[str] = None
@@ -965,7 +965,7 @@ def pre_setup_hook(self) -> None: # noqa: D102
def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMapping[str, Any]: # noqa: D102
kwargs = super()._pre_instantiation_hook(kwargs=kwargs)
- dataset = Nations(create_inverse_triples=self.create_inverse_triples)
+ dataset = Nations(use_inverse_relations=self.use_inverse_relations)
self.factory = dataset.training
# insert shared parameters
kwargs["triples_factory"] = self.factory
@@ -1038,7 +1038,7 @@ def _test_score(
self.skipTest(str(e))
else:
raise e
- if score is self.instance.score_r and self.create_inverse_triples:
+ if score is self.instance.score_r and self.use_inverse_relations:
# TODO: look into score_r for inverse relations
logger.warning("score_r's shape is not clear yet for models with inverse relations")
else:
@@ -1201,8 +1201,8 @@ def _cli_extras(self):
]
extras.extend(self.cli_extras)
- # Make sure that inverse triples are created if create_inverse_triples=True
- if self.create_inverse_triples:
+ # Make sure that inverse triples are created if use_inverse_relations=True
+ if self.use_inverse_relations:
extras.append("--create-inverse-triples")
extras = [str(e) for e in extras]
@@ -1223,7 +1223,7 @@ def test_pipeline_nations_early_stopper(self):
model=self.cls,
model_kwargs=model_kwargs,
dataset="nations",
- dataset_kwargs=dict(create_inverse_triples=self.create_inverse_triples),
+ dataset_kwargs=dict(use_inverse_relations=self.use_inverse_relations),
stopper="early",
training_loop_kwargs=self.training_loop_kwargs,
stopper_kwargs=dict(frequency=1),
@@ -1421,7 +1421,7 @@ class BaseNodePieceTest(ModelTestCase):
"""Test the NodePiece model."""
cls = pykeen.models.NodePiece
- create_inverse_triples = True
+ use_inverse_relations = True
def _help_test_cli(self, args): # noqa: D102
if self.instance_kwargs.get("tokenizers_kwargs"):
@@ -1448,12 +1448,12 @@ def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMa
num_triples_training=self.num_triples_training,
num_triples_inference=self.num_triples_inference,
num_triples_testing=self.num_triples_testing,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
)
training_loop_kwargs = dict(self.training_loop_kwargs or dict())
training_loop_kwargs["mode"] = self.mode
InductiveModelTestCase.training_loop_kwargs = training_loop_kwargs
- # dataset = InductiveFB15k237(create_inverse_triples=self.create_inverse_triples)
+ # dataset = InductiveFB15k237(use_inverse_relations=self.use_inverse_relations)
kwargs["triples_factory"] = self.factory = dataset.transductive_training
kwargs["inference_factory"] = dataset.inductive_inference
return kwargs
@@ -1543,7 +1543,7 @@ class TriplesFactoryRepresentationTestCase(RepresentationTestCase):
num_entities: ClassVar[int]
num_relations: ClassVar[int] = 7
num_triples: ClassVar[int] = 31
- create_inverse_triples: bool = False
+ use_inverse_relations: bool = False
def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMapping[str, Any]: # noqa: D102
self.num_entities = self.max_id
@@ -1552,7 +1552,7 @@ def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMa
num_entities=self.max_id,
num_relations=self.num_relations,
num_triples=self.num_triples,
- create_inverse_triples=self.create_inverse_triples,
+ use_inverse_relations=self.use_inverse_relations,
)
return kwargs
@@ -2063,7 +2063,7 @@ def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMa
num_entities=self.max_id,
num_relations=self.num_relations,
num_triples=self.num_triples,
- create_inverse_triples=False,
+ use_inverse_relations=False,
)
# inferred from triples factory
kwargs.pop("max_id")
diff --git a/tests/test_datasets/test_loading.py b/tests/test_datasets/test_loading.py
index fc9773b107..f7e77020cf 100644
--- a/tests/test_datasets/test_loading.py
+++ b/tests/test_datasets/test_loading.py
@@ -162,12 +162,12 @@ class TestPathDatasetTriples(cases.LocalDatasetTestCase):
exp_num_triples = 1992
dataset_cls = Nations
- def test_create_inverse_triples(self):
+ def test_use_inverse_relations(self):
"""Verify that inverse triples are only created in the training factory."""
- dataset = Nations(create_inverse_triples=True)
- assert dataset.training.create_inverse_triples
- assert not dataset.testing.create_inverse_triples
- assert not dataset.validation.create_inverse_triples
+ dataset = Nations(use_inverse_relations=True)
+ assert dataset.training.use_inverse_relations
+ assert not dataset.testing.use_inverse_relations
+ assert not dataset.validation.use_inverse_relations
class TestPathDataset(cases.LocalDatasetTestCase):
diff --git a/tests/test_lightning.py b/tests/test_lightning.py
index 67014774aa..63db544d06 100644
--- a/tests/test_lightning.py
+++ b/tests/test_lightning.py
@@ -70,8 +70,8 @@
def test_lit_training(model, model_kwargs, training_loop):
"""Test training models with PyTorch Lightning."""
# some models require inverse relations
- create_inverse_triples = model is not models.RGCN
- dataset = get_dataset(dataset="nations", dataset_kwargs=dict(create_inverse_triples=create_inverse_triples))
+ use_inverse_relations = model is not models.RGCN
+ dataset = get_dataset(dataset="nations", dataset_kwargs=dict(use_inverse_relations=use_inverse_relations))
# some model require access to the training triples
if "triples_factory" in model_kwargs:
diff --git a/tests/test_model_mode.py b/tests/test_model_mode.py
index 0928296d3a..a348cc3600 100644
--- a/tests/test_model_mode.py
+++ b/tests/test_model_mode.py
@@ -128,4 +128,4 @@ class MinimalTriplesFactory:
num_entities = 2
num_relations = 2
- create_inverse_triples: bool = False
+ use_inverse_relations: bool = False
diff --git a/tests/test_models.py b/tests/test_models.py
index 39e9bea363..ba85431516 100644
--- a/tests/test_models.py
+++ b/tests/test_models.py
@@ -48,7 +48,7 @@ class TestCompGCN(cases.ModelTestCase):
"""Test the CompGCN model."""
cls = pykeen.models.CompGCN
- create_inverse_triples = True
+ use_inverse_relations = True
num_constant_init = 3 # BN(2) + Bias
cli_extras = ["--create-inverse-triples"]
@@ -77,7 +77,7 @@ class TestConvE(cases.ModelTestCase):
cls = pykeen.models.ConvE
embedding_dim = 12
- create_inverse_triples = True
+ use_inverse_relations = True
kwargs = {
"output_channels": 2,
"embedding_height": 3,
@@ -190,7 +190,7 @@ def test_disconnected(self):
[[0, 0, 1], [1, 1, 0], [3, 1, 0], [3, 2, 1]], dtype=torch.long
) # node ID 2 is missing as a disconnected node
factory = CoreTriplesFactory.create(
- mapped_triples=edges, num_entities=4, num_relations=3, create_inverse_triples=True
+ mapped_triples=edges, num_entities=4, num_relations=3, use_inverse_relations=True
)
pykeen.models.NodePiece(triples_factory=factory, num_tokens=2)
@@ -270,7 +270,7 @@ class TestInductiveNodePiece(cases.InductiveModelTestCase):
"""Test the InductiveNodePiece model."""
cls = pykeen.models.InductiveNodePiece
- create_inverse_triples = True
+ use_inverse_relations = True
class TestInductiveNodePieceGNN(cases.InductiveModelTestCase):
@@ -278,7 +278,7 @@ class TestInductiveNodePieceGNN(cases.InductiveModelTestCase):
cls = pykeen.models.InductiveNodePieceGNN
num_constant_init = 6
- create_inverse_triples = True
+ use_inverse_relations = True
train_batch_size = 8
@@ -755,6 +755,72 @@ def test_has_hpo_defaults(self): # noqa: D102
raise unittest.SkipTest(f"Base class {self.cls} does not provide HPO defaults.")
+
+class InverseRelationPredictionTests(unittest_templates.GenericTestCase[pykeen.models.FixedModel]):
+ """Test for prediction with inverse relations."""
+
+ cls = pykeen.models.FixedModel
+
+ def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMapping[str, Any]:
+ # create triples factory with inverse relations
+ kwargs = super()._pre_instantiation_hook(kwargs=kwargs)
+ kwargs["triples_factory"] = self.factory = Nations(use_inverse_relations=True).training
+ return kwargs
+
+ def _combination_batch(
+ self,
+ heads: bool = True,
+ relations: bool = True,
+ tails: bool = True,
+ ) -> torch.LongTensor:
+ """Generate a batch with all combinations."""
+ factors = []
+ if heads:
+ factors.append(range(self.factory.num_entities))
+ if relations:
+ factors.append(range(self.factory.real_num_relations))
+ if tails:
+ factors.append(range(self.factory.num_entities))
+ return torch.as_tensor(
+ data=list(itertools.product(*factors)),
+ dtype=torch.long,
+ )
+
+ def test_predict_hrt(self):
+ """Test predict_hrt."""
+ hrt_batch = self._combination_batch()
+ expected_scores = self.instance._generate_fake_scores(
+ h=hrt_batch[:, 0],
+ r=2 * hrt_batch[:, 1],
+ t=hrt_batch[:, 2],
+ ).unsqueeze(dim=-1)
+ scores = self.instance.predict_hrt(hrt_batch=hrt_batch)
+ assert torch.allclose(scores, expected_scores)
+
+ def test_predict_h(self):
+ """Test predict_h."""
+ rt_batch = self._combination_batch(heads=False)
+ # head prediction via inverse tail prediction
+ expected_scores = self.instance._generate_fake_scores(
+ h=rt_batch[:, 1, None],
+ r=2 * rt_batch[:, 0, None] + 1,
+ t=torch.arange(self.factory.num_entities).unsqueeze(dim=0),
+ )
+ scores = self.instance.predict_h(rt_batch=rt_batch)
+ assert torch.allclose(scores, expected_scores)
+
+ def test_predict_t(self):
+ """Test predict_t."""
+ hr_batch = self._combination_batch(tails=False)
+ expected_scores = self.instance._generate_fake_scores(
+ h=hr_batch[:, 0, None],
+ r=2 * hr_batch[:, 1, None],
+ t=torch.arange(self.factory.num_entities).unsqueeze(dim=0),
+ )
+ scores = self.instance.predict_t(hr_batch=hr_batch)
+ assert torch.allclose(scores, expected_scores)
+
+
class CooccurrenceFilteredModelTests(cases.ModelTestCase):
"""Tests for the filtered meta model."""
diff --git a/tests/test_nn/test_representation.py b/tests/test_nn/test_representation.py
index 1bd45a299c..142f5f36f1 100644
--- a/tests/test_nn/test_representation.py
+++ b/tests/test_nn/test_representation.py
@@ -76,7 +76,7 @@ class TestSingleCompGCNRepresentationTests(cases.TriplesFactoryRepresentationTes
cls = pykeen.nn.representation.SingleCompGCNRepresentation
dim: ClassVar[int] = 3
- create_inverse_triples = True
+ use_inverse_relations = True
def _pre_instantiation_hook(self, kwargs: MutableMapping[str, Any]) -> MutableMapping[str, Any]: # noqa: D102
kwargs = super()._pre_instantiation_hook(kwargs=kwargs)
diff --git a/tests/test_prediction.py b/tests/test_prediction.py
index a18f759f66..76ea55ba4a 100644
--- a/tests/test_prediction.py
+++ b/tests/test_prediction.py
@@ -115,7 +115,7 @@ def test_consume_scores(num_entities: int, num_relations: int):
"""Test for consume_scores."""
dataset = pykeen.predict.AllPredictionDataset(num_entities=num_entities, num_relations=num_relations)
model = pykeen.models.mocks.FixedModel(
- triples_factory=KGInfo(num_entities=num_entities, num_relations=num_relations, create_inverse_triples=False)
+ triples_factory=KGInfo(num_entities=num_entities, num_relations=num_relations, use_inverse_relations=False)
)
consumer = pykeen.predict.CountScoreConsumer()
pykeen.predict.consume_scores(model, dataset, consumer)
@@ -128,7 +128,7 @@ def _iter_predict_all_inputs() -> Iterable[Tuple[pykeen.models.Model, Optional[i
# use a small model, since operation is expensive
num_entities, num_relations = 3, 2
model = pykeen.models.mocks.FixedModel(
- triples_factory=KGInfo(num_entities=num_entities, num_relations=num_relations, create_inverse_triples=False)
+ triples_factory=KGInfo(num_entities=num_entities, num_relations=num_relations, use_inverse_relations=False)
)
# all scores, automatic batch size
yield model, None, pykeen.typing.LABEL_TAIL, None
diff --git a/tests/test_triples_factory.py b/tests/test_triples_factory.py
index 33a909063b..6251c455db 100644
--- a/tests/test_triples_factory.py
+++ b/tests/test_triples_factory.py
@@ -84,7 +84,7 @@ def test_correct_inverse_creation(self):
["e1", "a", "e2"],
]
t = np.array(t, dtype=str)
- factory = TriplesFactory.from_labeled_triples(triples=t, create_inverse_triples=True)
+ factory = TriplesFactory.from_labeled_triples(triples=t, use_inverse_relations=True)
instances = factory.create_slcwa_instances()
assert len(instances) == 4
@@ -92,22 +92,22 @@ def test_automatic_incomplete_inverse_detection(self):
"""Test detecting that the triples contain inverses, warns about them, and filters them out."""
# comment(mberr): from my pov this behaviour is faulty: the triples factory is expected to say it contains
# inverse relations, although the triples contained in it are not the same we would have when removing the
- # first triple, and passing create_inverse_triples=True.
+ # first triple, and passing use_inverse_relations=True.
t = [
["e3", f"a.{INVERSE_SUFFIX}", "e10"],
["e1", "a", "e2"],
["e1", "a.", "e5"],
]
t = np.array(t, dtype=str)
- for create_inverse_triples in (False, True):
+ for use_inverse_relations in (False, True):
with patch("pykeen.triples.triples_factory.logger.warning") as warning:
- factory = TriplesFactory.from_labeled_triples(triples=t, create_inverse_triples=create_inverse_triples)
+ factory = TriplesFactory.from_labeled_triples(triples=t, use_inverse_relations=use_inverse_relations)
# check for warning
warning.assert_called()
# check for filtered triples
assert factory.num_triples == 2
# check for correct inverse triples flag
- assert factory.create_inverse_triples == create_inverse_triples
+ assert factory.use_inverse_relations == use_inverse_relations
def test_id_to_label(self):
"""Test ID-to-label conversion."""
@@ -158,7 +158,7 @@ def _test_restriction(
assert no_restriction_to_apply == equal_factory_object
# check that inverse_triples is correctly carried over
- assert original_triples_factory.create_inverse_triples == restricted_triples_factory.create_inverse_triples
+ assert original_triples_factory.use_inverse_relations == restricted_triples_factory.use_inverse_relations
# verify that the label-to-ID mapping has not been changed
assert original_triples_factory.entity_to_id == restricted_triples_factory.entity_to_id
@@ -198,7 +198,7 @@ def test_new_with_restriction(self):
}
for inverse_triples in (True, False):
original_triples_factory = Nations(
- create_inverse_triples=inverse_triples,
+ use_inverse_relations=inverse_triples,
).training
# Test different combinations of restrictions
for (
@@ -252,13 +252,13 @@ def test_create_lcwa_instances(self):
def test_split_inverse_triples(self):
"""Test whether inverse triples are only created in the training factory."""
# set create inverse triple to true
- self.factory.create_inverse_triples = True
+ self.factory.use_inverse_relations = True
# split factory
train, *others = self.factory.split()
# check that in *training* inverse triple are to be created
- assert train.create_inverse_triples
+ assert train.use_inverse_relations
# check that in all other splits no inverse triples are to be created
- assert not any(f.create_inverse_triples for f in others)
+ assert not any(f.use_inverse_relations for f in others)
@needs_packages("wordcloud", "IPython")
def test_entity_word_cloud(self):
@@ -382,7 +382,7 @@ def test_triples(self):
def test_inverse_triples(self):
"""Test that the right number of entities and triples exist after inverting them."""
- triples_factory = TriplesFactory.from_labeled_triples(triples=triples, create_inverse_triples=True)
+ triples_factory = TriplesFactory.from_labeled_triples(triples=triples, use_inverse_relations=True)
self.assertEqual(4, triples_factory.num_relations)
self.assertEqual(
set(range(triples_factory.num_entities)),
@@ -503,7 +503,7 @@ def test_core_binary(self):
def test_core_binary_inverse_relations(self):
"""Test binary i/o on core triples factory with inverse relations."""
- tf1 = Nations(create_inverse_triples=True).training.to_core_triples_factory()
+ tf1 = Nations(use_inverse_relations=True).training.to_core_triples_factory()
self.assert_binary_io(tf1, CoreTriplesFactory)
def assert_binary_io(self, tf, tf_cls):
@@ -528,7 +528,7 @@ def assert_tf_equal(self, tf1, tf2) -> None:
self.assertEqual(tf1.metadata, tf2.metadata)
self.assertEqual(tf1.num_entities, tf2.num_entities)
self.assertEqual(tf1.num_relations, tf2.num_relations)
- self.assertEqual(tf1.create_inverse_triples, tf2.create_inverse_triples)
+ self.assertEqual(tf1.use_inverse_relations, tf2.use_inverse_relations)
self.assertEqual(
tf1.mapped_triples.detach().cpu().numpy().tolist(),
tf2.mapped_triples.detach().cpu().numpy().tolist(),
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