[Train] Training Pipeline (#1214)

Order of reviews:
#1206
#1207
#1209
#1212
#1214 <-- Here

SUMMARY:
* Refactor Training pipeline
* Remove initialize, finalize from the session functions
* Add training information on entrypoints/readme.md on the different
types of training that can be carried out on llm-compressor
* Decouple training from text_generation.py::main. The new logic loves
in llmcompressor/entrypoints/train.py that takes the flow of
pre-process, carry out training logic and then post-process
* Delete outdated info on transformers/finetune/readme.md
* Update session_mixin.py to use session().initialize or
session().finalize.
* Deprecate train.py in text_generation.py, raising deprecation message
if used.
* Update tests to use llmcompressor's train, not
llmcompressor.transformers' train

TEST PLAN:
* Pass tests

---------

Co-authored-by: Dipika Sikka <dipikasikka1@gmail.com>

Author: George

src/llmcompressor/__init__.py

@@ -38,8 +38,6 @@
     active_session,
     callbacks,
     create_session,
-    finalize,
-    initialize,
     reset_session,
 )
-from llmcompressor.entrypoints import Oneshot, oneshot
+from llmcompressor.entrypoints import Oneshot, oneshot, train

src/llmcompressor/core/__init__.py

@@ -13,8 +13,6 @@
     active_session,
     callbacks,
     create_session,
-    finalize,
-    initialize,
     reset_session,
 )
 from llmcompressor.core.state import Data, Hardware, ModifiedState, State
@@ -35,8 +33,6 @@
     "create_session",
     "active_session",
     "reset_session",
-    "initialize",
-    "finalize",
     "apply",
     "callbacks",
     "LifecycleCallbacks",

src/llmcompressor/core/session_functions.py

@@ -1,18 +1,15 @@
 import threading
 from contextlib import contextmanager
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Optional
 
 from llmcompressor.core.events import EventType
 from llmcompressor.core.session import CompressionSession
 from llmcompressor.core.state import ModifiedState
-from llmcompressor.recipe import Recipe
 
 __all__ = [
     "create_session",
     "active_session",
     "reset_session",
-    "initialize",
-    "finalize",
     "callbacks",
     "LifecycleCallbacks",
 ]
@@ -58,79 +55,6 @@ def reset_session():
     session._lifecycle.reset()
 
 
-def initialize(
-    recipe: Union[str, List[str], "Recipe", List["Recipe"], None] = None,
-    recipe_stage: Union[str, List[str], None] = None,
-    recipe_args: Optional[Dict[str, Any]] = None,
-    model: Optional[Any] = None,
-    teacher_model: Optional[Any] = None,
-    optimizer: Optional[Any] = None,
-    attach_optim_callbacks: bool = True,
-    train_data: Optional[Any] = None,
-    val_data: Optional[Any] = None,
-    test_data: Optional[Any] = None,
-    calib_data: Optional[Any] = None,
-    copy_data: bool = True,
-    start: Optional[float] = None,
-    steps_per_epoch: Optional[int] = None,
-    batches_per_step: Optional[int] = None,
-    **kwargs,
-) -> ModifiedState:
-    """
-    A method to initialize the active session for sparsification
-
-    :param recipe: the recipe to use for the sparsification, can be a path to a
-        recipe file, a raw recipe string, a recipe object, or a list of recipe objects.
-    :param recipe_stage: the stage to target for the sparsification
-    :param recipe_args: the args to use for overriding the recipe defaults
-    :param model: the model to sparsify
-    :param teacher_model: the teacher model to use for knowledge distillation
-    :param optimizer: the optimizer to use for the sparsification
-    :param attach_optim_callbacks: True to attach the optimizer callbacks to the
-        sparsification lifecycle, False otherwise
-    :param train_data: the training data to use for the sparsification
-    :param val_data: the validation data to use for the sparsification
-    :param test_data: the testing data to use for the sparsification
-    :param calib_data: the calibration data to use for the sparsification
-    :param copy_data: True to copy the data, False otherwise
-    :param start: the start epoch to use for the sparsification
-    :param steps_per_epoch: the number of steps per epoch to use for the
-        sparsification
-    :param batches_per_step: the number of batches per step to use for
-        sparsification
-    :param kwargs: additional kwargs to pass to the lifecycle's initialize method
-    :return: the modified state of the active session after initializing
-    """
-    return active_session().initialize(
-        recipe=recipe,
-        recipe_stage=recipe_stage,
-        recipe_args=recipe_args,
-        model=model,
-        teacher_model=teacher_model,
-        optimizer=optimizer,
-        attach_optim_callbacks=attach_optim_callbacks,
-        train_data=train_data,
-        val_data=val_data,
-        test_data=test_data,
-        calib_data=calib_data,
-        copy_data=copy_data,
-        start=start,
-        steps_per_epoch=steps_per_epoch,
-        batches_per_step=batches_per_step,
-        **kwargs,
-    )
-
-
-def finalize(**kwargs) -> ModifiedState:
-    """
-    Method to finalize the active session for sparsification
-
-    :param kwargs: additional kwargs to pass to the lifecycle's finalize method
-    :return: the modified state of the active session after finalizing
-    """
-    return active_session().finalize(**kwargs)
-
-
 class LifecycleCallbacks:
     """
     A class for invoking lifecycle events for the active session