feat: add filter and timestamp splits (#627)

* Fixed splits * Fixed docstrings * Fix test bug * Ran linter * Fixed FractionSplit and AutoMLVideo FilterSplit issues * Added warning for incomplete filter splits * Fixed AutoMLVideo tests * Fixed type * Moved annotation_schema_uri * Tweaked docstrings Co-authored-by: sasha-gitg <44654632+sasha-gitg@users.noreply.github.com>

Author: ivanmkc

google/cloud/aiplatform/training_jobs.py

@@ -103,14 +103,11 @@
 _TEST_DATASET_NAME = "test-dataset-name"
 
 _TEST_MODEL_DISPLAY_NAME = "model-display-name"
+
 _TEST_LABELS = {"key": "value"}
 _TEST_MODEL_LABELS = {"model_key": "model_value"}
-_TEST_TRAINING_FRACTION_SPLIT = 0.8
-_TEST_VALIDATION_FRACTION_SPLIT = 0.1
-_TEST_TEST_FRACTION_SPLIT = 0.1
-_TEST_PREDEFINED_SPLIT_COLUMN_NAME = "split"
 
-_TEST_OUTPUT_PYTHON_PACKAGE_PATH = "gs://test/ouput/python/trainer.tar.gz"
+_TEST_PREDEFINED_SPLIT_COLUMN_NAME = "split"
 
 _TEST_MODEL_NAME = "projects/my-project/locations/us-central1/models/12345"
 
@@ -261,18 +258,11 @@ def test_run_call_pipeline_service_create(
  if not sync:
  model_from_job.wait()
 
- true_fraction_split = gca_training_pipeline.FractionSplit(
- training_fraction=_TEST_TRAINING_FRACTION_SPLIT,
- validation_fraction=_TEST_VALIDATION_FRACTION_SPLIT,
- test_fraction=_TEST_TEST_FRACTION_SPLIT,
- )
-
  true_managed_model = gca_model.Model(
  display_name=_TEST_MODEL_DISPLAY_NAME, labels=_TEST_MODEL_LABELS
  )
 
  true_input_data_config = gca_training_pipeline.InputDataConfig(
- fraction_split=true_fraction_split,
  predefined_split=gca_training_pipeline.PredefinedSplit(
  key=_TEST_PREDEFINED_SPLIT_COLUMN_NAME
  ),
@@ -348,19 +338,12 @@ def test_run_call_pipeline_if_no_model_display_name_nor_model_labels(
  if not sync:
  model_from_job.wait()
 
- true_fraction_split = gca_training_pipeline.FractionSplit(
- training_fraction=_TEST_TRAINING_FRACTION_SPLIT,
- validation_fraction=_TEST_VALIDATION_FRACTION_SPLIT,
- test_fraction=_TEST_TEST_FRACTION_SPLIT,
- )
-
  # Test that if defaults to the job display name
  true_managed_model = gca_model.Model(
  display_name=_TEST_DISPLAY_NAME, labels=_TEST_LABELS,
  )
 
  true_input_data_config = gca_training_pipeline.InputDataConfig(
- fraction_split=true_fraction_split,
  dataset_id=mock_dataset_time_series.name,
  )
 
@@ -422,17 +405,10 @@ def test_run_call_pipeline_if_set_additional_experiments(
  if not sync:
  model_from_job.wait()
 
- true_fraction_split = gca_training_pipeline.FractionSplit(
- training_fraction=_TEST_TRAINING_FRACTION_SPLIT,
- validation_fraction=_TEST_VALIDATION_FRACTION_SPLIT,
- test_fraction=_TEST_TEST_FRACTION_SPLIT,
- )
-
  # Test that if defaults to the job display name
  true_managed_model = gca_model.Model(display_name=_TEST_DISPLAY_NAME)
 
  true_input_data_config = gca_training_pipeline.InputDataConfig(
- fraction_split=true_fraction_split,
  dataset_id=mock_dataset_time_series.name,
  )