Upgrade PyTorch to version 2.3.1

eland/cli/eland_import_hub_model.py

@@ -230,6 +230,7 @@ def check_cluster_version(es_client, logger):
     sem_ver = parse_es_version(es_info["version"]["number"])
     major_version = sem_ver[0]
     minor_version = sem_ver[1]
+    patch_version = sem_ver[2]
 
     # NLP models added in 8
     if major_version < 8:
@@ -238,13 +239,13 @@ def check_cluster_version(es_client, logger):
         )
         exit(1)
 
-    # PyTorch was upgraded to version 2.1.2 in 8.13
+    # PyTorch was upgraded to version 2.3.1 in 8.15.1
     # and is incompatible with earlier versions
-    if major_version == 8 and minor_version < 13:
+    if major_version == 8 and minor_version < 15 and patch_version < 1:
         import torch
 
         logger.error(
-            f"Eland uses PyTorch version {torch.__version__} which is incompatible with Elasticsearch versions prior to 8.13. Please upgrade Elasticsearch to at least version 8.13"
+            f"Eland uses PyTorch version {torch.__version__} which is incompatible with Elasticsearch versions prior to 8.15.1. Please upgrade Elasticsearch to at least version 8.15.1"
         )
         exit(1)
 

noxfile.py

@@ -121,7 +121,7 @@ def test(session, pandas_version: str):
         "--nbval",
     )
 
-    # PyTorch 2.1.2 doesn't support Python 3.12
+    # PyTorch 2.3.1 doesn't support Python 3.12
     if session.python == "3.12":
         pytest_args += ("--ignore=eland/ml/pytorch",)
     session.run(

setup.py

@@ -60,10 +60,10 @@
     "lightgbm": ["lightgbm>=2,<4"],
     "pytorch": [
         "requests<3",
-        "torch==2.1.2",
+        "torch==2.3.1",
         "tqdm",
-        "sentence-transformers>=2.1.0,<=2.3.1",
-        "transformers[torch]>=4.31.0,<4.36.0",
+        "sentence-transformers>=2.1.0,<=2.7.0",
+        "transformers[torch]>=4.31.0,<4.44.0",
     ],
 }
 extras["all"] = list({dep for deps in extras.values() for dep in deps})

tests/ml/pytorch/test_pytorch_model_config_pytest.py

@@ -58,8 +58,8 @@
 
 pytestmark = [
     pytest.mark.skipif(
-        ES_VERSION < (8, 13, 0),
-        reason="Eland uses Pytorch 2.1.2, versions of Elasticsearch prior to 8.13.0 are incompatible with PyTorch 2.1.2",
+        ES_VERSION < (8, 15, 1),
+        reason="Eland uses Pytorch 2.3.1, versions of Elasticsearch prior to 8.15.1 are incompatible with PyTorch 2.3.1",
     ),
     pytest.mark.skipif(
         not HAS_SKLEARN, reason="This test requires 'scikit-learn' package to run"
@@ -163,7 +163,6 @@
 
 
 class TestModelConfguration:
-    @pytest.mark.skip(reason="https://github.com/elastic/eland/issues/633")
     @pytest.mark.parametrize(
         "model_id,task_type,config_type,tokenizer_type,max_sequence_len,embedding_size",
         MODEL_CONFIGURATIONS,

tests/ml/pytorch/test_pytorch_model_upload_pytest.py

@@ -39,8 +39,8 @@
 
 pytestmark = [
     pytest.mark.skipif(
-        ES_VERSION < (8, 13, 0),
-        reason="Eland uses Pytorch 2.1.2, versions of Elasticsearch prior to 8.13.0 are incompatible with PyTorch 2.1.2",
+        ES_VERSION < (8, 15, 1),
+        reason="Eland uses Pytorch 2.3.1, versions of Elasticsearch prior to 8.15.1 are incompatible with PyTorch 2.3.1",
     ),
     pytest.mark.skipif(
         not HAS_SKLEARN, reason="This test requires 'scikit-learn' package to run"