feat: Implement TrainerClient Backends & Local Process

python/kubeflow/trainer/backends/__init__.py

@@ -0,0 +1,28 @@
+# Copyright 2025 The Kubeflow Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from kubeflow.trainer.backends.k8s import K8SBackend
+from kubeflow.trainer.backends.local_process import LocalProcessBackend
+from kubeflow.trainer.types.backends import K8SBackendConfig, LocalProcessBackendConfig
+
+TRAINER_BACKEND_REGISTRY = {
+    "kubernetes": {
+        "backend_cls": K8SBackend,
+        "config_cls": K8SBackendConfig,
+    },
+    "local": {
+        "backend_cls": LocalProcessBackend,
+        "config_cls": LocalProcessBackendConfig,
+    }
+}

python/kubeflow/trainer/backends/base.py

@@ -0,0 +1,62 @@
+# Copyright 2025 The Kubeflow Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import abc
+
+from typing import Dict, List, Optional
+from kubeflow.trainer.constants import constants
+from kubeflow.trainer.types import types
+
+
+class TrainingBackend(abc.ABC):
+
+    @abc.abstractmethod
+    def list_runtimes(self) -> List[types.Runtime]:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def get_runtime(self, name: str) -> Optional[types.Runtime]:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def train(self,
+              train_job_name: str,
+              runtime: types.Runtime,
+              initializer: Optional[types.Initializer] = None,
+              trainer: Optional[types.Trainer] = None,
+              ) -> str:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def list_jobs(
+            self, runtime: Optional[types.Runtime] = None
+    ) -> List[types.TrainJob]:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def get_job(self, name: str) -> Optional[types.TrainJob]:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def get_job_logs(self,
+                     name: str,
+                     follow: Optional[bool] = False,
+                     step: str = constants.NODE,
+                     node_rank: int = 0,
+                     ) -> Dict[str, str]:
+        raise NotImplementedError()
+
+    @abc.abstractmethod
+    def delete_job(self, name: str) -> None:
+        raise NotImplementedError()