No public description

PiperOrigin-RevId: 788929755

Author: speedstorm1

google/genai/tests/tunings/test_tune.py

@@ -32,107 +32,6 @@
         ),
         exception_if_mldev="gcs_uri parameter is not supported in Gemini API.",
     ),
-    pytest_helper.TestTableItem(
-        name="test_dataset_gcs_uri_all_parameters",
-        parameters=genai_types._CreateTuningJobParameters(
-            base_model="gemini-1.5-pro-002",
-            training_dataset=genai_types.TuningDataset(
-                gcs_uri="gs://cloud-samples-data/ai-platform/generative_ai/gemini-1_5/text/sft_train_data.jsonl",
-            ),
-            config=genai_types.CreateTuningJobConfig(
-                tuned_model_display_name="Model display name",
-                epoch_count=1,
-                learning_rate_multiplier=1.0,
-                adapter_size="ADAPTER_SIZE_ONE",
-                validation_dataset=genai_types.TuningDataset(
-                    gcs_uri="gs://cloud-samples-data/ai-platform/generative_ai/gemini-1_5/text/sft_validation_data.jsonl",
-                ),
-                # Not supported in Vertex AI
-                # batch_size=4,
-                # learning_rate=0.01,
-            ),
-        ),
-        exception_if_mldev="gcs_uri parameter is not supported in Gemini API.",
-    ),
-    pytest_helper.TestTableItem(
-        name="test_dataset_gcs_uri_parameters_unsupported_by_vertex",
-        parameters=genai_types._CreateTuningJobParameters(
-            base_model="gemini-1.5-pro-002",
-            training_dataset=genai_types.TuningDataset(
-                gcs_uri="gs://cloud-samples-data/ai-platform/generative_ai/gemini-1_5/text/sft_train_data.jsonl",
-            ),
-            config=genai_types.CreateTuningJobConfig(
-                # Not supported in Vertex AI
-                batch_size=4,
-                learning_rate=0.01,
-            ),
-        ),
-        exception_if_vertex="batch_size parameter is not supported in Vertex AI.",
-        exception_if_mldev="gcs_uri parameter is not supported in Gemini API.",
-    ),
-    pytest_helper.TestTableItem(
-        name="test_dataset_examples_parameters_unsupported_by_mldev",
-        parameters=genai_types._CreateTuningJobParameters(
-            # Error: "models/gemini-1.5-pro-002 is not found for
-            # CREATE TUNED MODEL at API version v1beta."
-            # base_model="gemini-1.5-pro-002",
-            base_model="models/gemini-1.0-pro-001",
-            training_dataset=genai_types.TuningDataset(
-                examples=[
-                    genai_types.TuningExample(
-                        text_input=f"Input text {i}",
-                        output=f"Output text {i}",
-                    )
-                    for i in range(5)
-                ],
-            ),
-            # Required for MLDev:
-            # "Either tuned_model_id or display_name must be set."
-            config=genai_types.CreateTuningJobConfig(
-                tuned_model_display_name="Model display name",
-                # Not supported in MLDev
-                adapter_size="ADAPTER_SIZE_ONE",
-                # Generator issue: "validationDatasetUri": {}. See b/375079287
-                # validation_dataset=genai_types.TuningDataset(
-                #     gcs_uri="gs://cloud-samples-data/ai-platform/generative_ai/gemini-1_5/text/sft_validation_data.jsonl",
-                # ),
-            ),
-        ),
-        exception_if_mldev="adapter_size parameter is not supported in Gemini API.",
-        exception_if_vertex="examples parameter is not supported in Vertex AI.",
-    ),
-    pytest_helper.TestTableItem(
-        name="test_dataset_vertex_dataset_resource",
-        parameters=genai_types._CreateTuningJobParameters(
-            base_model="gemini-1.5-pro-002",
-            training_dataset=genai_types.TuningDataset(
-                vertex_dataset_resource="projects/613165508263/locations/us-central1/datasets/8254568702121345024",
-            ),
-        ),
-        exception_if_mldev="vertex_dataset_resource parameter is not supported in Gemini API.",
-    ),
-    pytest_helper.TestTableItem(
-        name="test_dataset_dataset_resource_all_parameters",
-        parameters=genai_types._CreateTuningJobParameters(
-            base_model="gemini-1.5-pro-002",
-            training_dataset=genai_types.TuningDataset(
-                vertex_dataset_resource="projects/613165508263/locations/us-central1/datasets/8254568702121345024",
-            ),
-            config=genai_types.CreateTuningJobConfig(
-                tuned_model_display_name="Model display name",
-                epoch_count=1,
-                learning_rate_multiplier=1.0,
-                adapter_size="ADAPTER_SIZE_ONE",
-                validation_dataset=genai_types.TuningDataset(
-                    vertex_dataset_resource="projects/613165508263/locations/us-central1/datasets/5556912525326417920",
-                ),
-                # Not supported in Vertex AI
-                # batch_size=4,
-                # learning_rate=0.01,
-            ),
-        ),
-        exception_if_mldev="vertex_dataset_resource parameter is not supported in Gemini API.",
-    ),
 ]
 
 pytestmark = pytest_helper.setup(

google/genai/tunings.py

@@ -86,20 +86,6 @@ def _ListTuningJobsParameters_to_mldev(
   return to_object
 
 
-def _TuningExample_to_mldev(
-    from_object: Union[dict[str, Any], object],
-    parent_object: Optional[dict[str, Any]] = None,
-) -> dict[str, Any]:
-  to_object: dict[str, Any] = {}
-  if getv(from_object, ['text_input']) is not None:
-    setv(to_object, ['textInput'], getv(from_object, ['text_input']))
-
-  if getv(from_object, ['output']) is not None:
-    setv(to_object, ['output'], getv(from_object, ['output']))
-
-  return to_object
-
-
 def _TuningDataset_to_mldev(
     from_object: Union[dict[str, Any], object],
     parent_object: Optional[dict[str, Any]] = None,
@@ -113,16 +99,6 @@ def _TuningDataset_to_mldev(
         'vertex_dataset_resource parameter is not supported in Gemini API.'
     )
 
-  if getv(from_object, ['examples']) is not None:
-    setv(
-        to_object,
-        ['examples', 'examples'],
-        [
-            _TuningExample_to_mldev(item, to_object)
-            for item in getv(from_object, ['examples'])
-        ],
-    )
-
   return to_object
 
 
@@ -169,20 +145,6 @@ def _CreateTuningJobConfig_to_mldev(
   if getv(from_object, ['adapter_size']) is not None:
     raise ValueError('adapter_size parameter is not supported in Gemini API.')
 
-  if getv(from_object, ['batch_size']) is not None:
-    setv(
-        parent_object,
-        ['tuningTask', 'hyperparameters', 'batchSize'],
-        getv(from_object, ['batch_size']),
-    )
-
-  if getv(from_object, ['learning_rate']) is not None:
-    setv(
-        parent_object,
-        ['tuningTask', 'hyperparameters', 'learningRate'],
-        getv(from_object, ['learning_rate']),
-    )
-
   return to_object
 
 
@@ -289,9 +251,6 @@ def _TuningDataset_to_vertex(
         getv(from_object, ['vertex_dataset_resource']),
     )
 
-  if getv(from_object, ['examples']) is not None:
-    raise ValueError('examples parameter is not supported in Vertex AI.')
-
   return to_object
 
 
@@ -366,12 +325,6 @@ def _CreateTuningJobConfig_to_vertex(
         getv(from_object, ['adapter_size']),
     )
 
-  if getv(from_object, ['batch_size']) is not None:
-    raise ValueError('batch_size parameter is not supported in Vertex AI.')
-
-  if getv(from_object, ['learning_rate']) is not None:
-    raise ValueError('learning_rate parameter is not supported in Vertex AI.')
-
   return to_object
 
 

google/genai/types.py

@@ -9082,28 +9082,6 @@ class ListTuningJobsResponseDict(TypedDict, total=False):
 ]
 
 
-class TuningExample(_common.BaseModel):
-
-  text_input: Optional[str] = Field(
-      default=None, description="""Text model input."""
-  )
-  output: Optional[str] = Field(
-      default=None, description="""The expected model output."""
-  )
-
-
-class TuningExampleDict(TypedDict, total=False):
-
-  text_input: Optional[str]
-  """Text model input."""
-
-  output: Optional[str]
-  """The expected model output."""
-
-
-TuningExampleOrDict = Union[TuningExample, TuningExampleDict]
-
-
 class TuningDataset(_common.BaseModel):
   """Supervised fine-tuning training dataset."""
 
@@ -9115,10 +9093,6 @@ class TuningDataset(_common.BaseModel):
       default=None,
       description="""The resource name of the Vertex Multimodal Dataset that is used as training dataset. Example: 'projects/my-project-id-or-number/locations/my-location/datasets/my-dataset-id'.""",
   )
-  examples: Optional[list[TuningExample]] = Field(
-      default=None,
-      description="""Inline examples with simple input/output text.""",
-  )
 
 
 class TuningDatasetDict(TypedDict, total=False):
@@ -9130,9 +9104,6 @@ class TuningDatasetDict(TypedDict, total=False):
   vertex_dataset_resource: Optional[str]
   """The resource name of the Vertex Multimodal Dataset that is used as training dataset. Example: 'projects/my-project-id-or-number/locations/my-location/datasets/my-dataset-id'."""
 
-  examples: Optional[list[TuningExampleDict]]
-  """Inline examples with simple input/output text."""
-
 
 TuningDatasetOrDict = Union[TuningDataset, TuningDatasetDict]
 
@@ -9195,14 +9166,6 @@ class CreateTuningJobConfig(_common.BaseModel):
   adapter_size: Optional[AdapterSize] = Field(
       default=None, description="""Adapter size for tuning."""
   )
-  batch_size: Optional[int] = Field(
-      default=None,
-      description="""The batch size hyperparameter for tuning. If not set, a default of 4 or 16 will be used based on the number of training examples.""",
-  )
-  learning_rate: Optional[float] = Field(
-      default=None,
-      description="""The learning rate hyperparameter for tuning. If not set, a default of 0.001 or 0.0002 will be calculated based on the number of training examples.""",
-  )
 
 
 class CreateTuningJobConfigDict(TypedDict, total=False):
@@ -9232,12 +9195,6 @@ class CreateTuningJobConfigDict(TypedDict, total=False):
   adapter_size: Optional[AdapterSize]
   """Adapter size for tuning."""
 
-  batch_size: Optional[int]
-  """The batch size hyperparameter for tuning. If not set, a default of 4 or 16 will be used based on the number of training examples."""
-
-  learning_rate: Optional[float]
-  """The learning rate hyperparameter for tuning. If not set, a default of 0.001 or 0.0002 will be calculated based on the number of training examples."""
-
 
 CreateTuningJobConfigOrDict = Union[
     CreateTuningJobConfig, CreateTuningJobConfigDict