add unit test

llama_stack/providers/tests/post_training/fixtures.py

@@ -0,0 +1,74 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import pytest
+import pytest_asyncio
+
+from llama_models.llama3.api.datatypes import URL
+from llama_stack.apis.common.type_system import *  # noqa: F403
+from llama_stack.apis.datasets import DatasetInput
+from llama_stack.apis.models import ModelInput
+
+from llama_stack.distribution.datatypes import Api, Provider
+
+from llama_stack.providers.tests.resolver import construct_stack_for_test
+
+from ..conftest import ProviderFixture
+
+
+@pytest.fixture(scope="session")
+def post_training_torchtune() -> ProviderFixture:
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="torchtune",
+                provider_type="inline::torchtune",
+                config={},
+            )
+        ],
+    )
+
+
+POST_TRAINING_FIXTURES = ["torchtune"]
+
+
+@pytest_asyncio.fixture(scope="session")
+async def post_training_stack(request):
+    fixture_dict = request.param
+
+    providers = {}
+    provider_data = {}
+    for key in ["post_training", "datasetio"]:
+        fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
+        providers[key] = fixture.providers
+        if fixture.provider_data:
+            provider_data.update(fixture.provider_data)
+
+    test_stack = await construct_stack_for_test(
+        [Api.post_training, Api.datasetio],
+        providers,
+        provider_data,
+        models=[ModelInput(model_id="meta-llama/Llama-3.2-3B-Instruct")],
+        datasets=[
+            DatasetInput(
+                dataset_id="alpaca",
+                provider_id="huggingface",
+                url=URL(uri="https://huggingface.co/datasets/tatsu-lab/alpaca"),
+                metadata={
+                    "path": "tatsu-lab/alpaca",
+                    "split": "train",
+                },
+                dataset_schema={
+                    "instruction": StringType(),
+                    "input": StringType(),
+                    "output": StringType(),
+                    "text": StringType(),
+                },
+            ),
+        ],
+    )
+
+    return test_stack.impls[Api.post_training]