Added prompt_template preprocessing param for text features

[tgaddair]

Useful when fine-tuning large language models (LLMs) that benefit from providing additional context to improve the quality of the embeddings they generate. Particularly valuable when using fixed weights (trainable=false).

[github-actions]

Unit Test Results

    6 files  ±  0    6 suites  ±0   31m 8s ⏱️ - 1h 21m 22s
  64 tests  - 87  61 ✔️  - 77    3 💤  - 10  0 ❌ ±0 
104 runs   - 87  93 ✔️  - 77  11 💤  - 10  0 ❌ ±0 

Results for commit 491ab56. ± Comparison against base commit 87a56fa.

This pull request removes 139 and adds 52 tests. Note that renamed tests count towards both.

tests.integration_tests.test_automl ‑ test_auto_train
tests.integration_tests.test_automl ‑ test_autoconfig_preprocessing_balanced
tests.integration_tests.test_automl ‑ test_autoconfig_preprocessing_imbalanced
tests.integration_tests.test_automl ‑ test_autoconfig_preprocessing_text_image
tests.integration_tests.test_automl ‑ test_create_auto_config[image]
tests.integration_tests.test_automl ‑ test_create_auto_config[multimodal]
tests.integration_tests.test_automl ‑ test_create_auto_config[tabular_large]
tests.integration_tests.test_automl ‑ test_create_auto_config[tabular_small]
tests.integration_tests.test_automl ‑ test_create_auto_config[text]
tests.integration_tests.test_automl ‑ test_create_auto_config_with_dataset_profile
…

tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing0-False]
tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing0-True]
tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing0-augmentation_pipeline_ops2]
tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing1-False]
tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing1-True]
tests.ludwig.augmentation.test_augmentation_pipeline ‑ test_ray_model_training_with_augmentation_pipeline[preprocessing1-augmentation_pipeline_ops2]
tests.ludwig.automl.test_base_config ‑ test_dataset_info[dask]
tests.ludwig.automl.test_base_config ‑ test_dataset_info[pandas]
tests.ludwig.automl.test_base_config ‑ test_infer_parquet_types
tests.ludwig.automl.test_base_config ‑ test_is_field_boolean[dask]
…

This pull request removes 11 skipped tests and adds 1 skipped test. Note that renamed tests count towards both.

tests.integration_tests.test_class_imbalance_feature ‑ test_imbalance_ray[oversample_minority]
tests.integration_tests.test_class_imbalance_feature ‑ test_imbalance_ray[undersample_majority]
tests.integration_tests.test_horovod ‑ test_horovod_gpu_memory_limit
tests.integration_tests.test_hyperopt_ray_horovod ‑ test_hyperopt_executor_bohb
tests.integration_tests.test_hyperopt_ray_horovod ‑ test_hyperopt_executor_with_metric
tests.integration_tests.test_hyperopt_ray_horovod ‑ test_hyperopt_run_hyperopt
tests.integration_tests.test_ray ‑ test_ray_image_modin
tests.integration_tests.test_ray ‑ test_ray_set_and_vector_outputs[csv]
tests.integration_tests.test_ray ‑ test_ray_set_and_vector_outputs[parquet]
tests.integration_tests.test_ray ‑ test_ray_split
…

tests.ludwig.models.test_training_determinism ‑ test_training_determinism_ray_backend

♻️ This comment has been updated with latest results.

[justinxzhao]

Would you also be able to remove the rest of the backwards compatibility workaround (introduced in #1859)?

[tgaddair]

I'm not too familiar with this code tbh, maybe you can take it in a follow-up?