[SOT] Cleanup legacy flags and policies

python/paddle/jit/sot/opcode_translator/executor/opcode_executor.py

@@ -112,7 +112,7 @@
 if TYPE_CHECKING:
     from .function_graph import CompileGraphResult, FunctionGraph
 
-SUPPORT_COMPARE_OP = {
+COMPARE_OP_NAME_TO_FN = {
     ">": operator.gt,
     "<": operator.lt,
     ">=": operator.ge,
@@ -1347,7 +1347,7 @@ def COMPARE_OP(self, instr: Instruction):
         right, left = self.stack.pop(), self.stack.pop()
         self.stack.push(
             BuiltinVariable(
-                SUPPORT_COMPARE_OP[op], self._graph, DanglingTracker()
+                COMPARE_OP_NAME_TO_FN[op], self._graph, DanglingTracker()
             )(left, right)
         )
 
@@ -1366,7 +1366,7 @@ def IS_OP(self, instr: Instruction):
         op = "is" if instr.arg == 0 else "is not"
         self.stack.push(
             BuiltinVariable(
-                SUPPORT_COMPARE_OP[op], self._graph, DanglingTracker()
+                COMPARE_OP_NAME_TO_FN[op], self._graph, DanglingTracker()
             )(left, right)
         )
 
@@ -1583,7 +1583,7 @@ def CONTAINS_OP(self, instr: Instruction):
         op = "in" if instr.arg == 0 else "not in"
         self.stack.push(
             BuiltinVariable(
-                SUPPORT_COMPARE_OP[op], self._graph, DanglingTracker()
+                COMPARE_OP_NAME_TO_FN[op], self._graph, DanglingTracker()
             )(left, right)
         )
 

python/paddle/jit/sot/opcode_translator/executor/pycode_generator.py

@@ -33,7 +33,6 @@
     FallbackError,
     InnerError,
     ResumeFnNameFactory,
-    is_clean_code,
     list_contain_by_id,
     list_find_index_by_id,
     no_eval_frame,
@@ -516,8 +515,6 @@ def gen_disable_eval_frame(self):
         """
         Generates instructions to disable the evaluation frame.
         """
-        if is_clean_code():
-            return
         self.gen_load_object(
             paddle.framework.core.set_eval_frame, "paddle_set_eval_frame_fn"
         )
@@ -529,8 +526,6 @@ def gen_enable_eval_frame(self):
         """
         Generates instructions to enable the evaluation frame.
         """
-        if is_clean_code():
-            return
         self.gen_load_object(
             paddle.framework.core.set_eval_frame, "paddle_set_eval_frame_fn"
         )

python/paddle/jit/sot/translate.py

@@ -26,7 +26,6 @@
     GraphLogger,
     InfoCollector,
     StepInfoManager,
-    StepState,
     log_do,
 )
 
@@ -96,42 +95,23 @@ def symbolic_translate(fn: Callable[P, R], **kwargs) -> Callable[P, R]:
     def callback(frame):
         return eval_frame_callback(frame, **kwargs)
 
-    def impl_sot(*args: P.args, **kwargs: P.kwargs) -> R:
-        assert hasattr(
-            fn, "__code__"
-        ), "Target function doesn't have code for simulating."
-        StepInfoManager().sot_step()
-        GraphLogger().clear()
-        InfoCollector().clear_step_info()
-        paddle.framework.core.set_eval_frame(callback)
-        try:
-            outs = fn(*args, **kwargs)
-        except Exception as e:
-            raise e
-        finally:
-            paddle.framework.core.set_eval_frame(None)
-
-        log_do(1, lambda: GraphLogger().print_info())
-        InfoCollector().print_step_report()
-        return outs
-
-    def impl_dynamic(*args: P.args, **kwargs: P.kwargs) -> R:
-        outs = fn(*args, **kwargs)
-        return outs
-
     def impl(*args: P.args, **kwargs: P.kwargs) -> R:
         with StepInfoManager().step_guard(fn.__code__), SotStepProfilerGuard():
-            state = StepInfoManager().current_state
-
-            if state == StepState.RUN_SOT:
-                return impl_sot(*args, **kwargs)
-            elif state == StepState.RUN_DYN:
-                return impl_dynamic(*args, **kwargs)
-            elif state == StepState.COLLECT_INFO:
-                return StepInfoManager().collect_info(
-                    impl_dynamic, impl_sot, *args, **kwargs
-                )
-            else:
-                raise RuntimeError("Unknown state.")
+            assert hasattr(
+                fn, "__code__"
+            ), "Target function doesn't have code for simulating."
+            GraphLogger().clear()
+            InfoCollector().clear_step_info()
+            paddle.framework.core.set_eval_frame(callback)
+            try:
+                outs = fn(*args, **kwargs)
+            except Exception as e:
+                raise e
+            finally:
+                paddle.framework.core.set_eval_frame(None)
+
+            log_do(1, lambda: GraphLogger().print_info())
+            InfoCollector().print_step_report()
+            return outs
 
     return impl

python/paddle/jit/sot/utils/__init__.py

@@ -14,8 +14,6 @@
 
 from .call_ast_utils import get_static_function, try_ast_func  # noqa: F401
 from .envs import (  # noqa: F401
-    ENV_CLEAN_CODE,
-    ENV_COST_MODEL,
     ENV_MIN_GRAPH_SIZE,
     ENV_SOT_ALLOW_DYNAMIC_SHAPE,
     ENV_SOT_ENABLE_FASTER_GUARD,
@@ -26,7 +24,6 @@
     ENV_SOT_WITH_CONTROL_FLOW,
     ENV_STRICT_MODE,
     allow_dynamic_shape_guard,
-    cost_model_guard,
     export_guard,
     faster_guard_guard,
     guard_tree_guard,
@@ -65,7 +62,6 @@
     Singleton,
     SotUndefinedVar,
     StepInfoManager,
-    StepState,
     count_if,
     current_symbol_registry,
     execute_time,
@@ -78,7 +74,6 @@
     in_paddle_module,
     is_break_graph_api,
     is_builtin_fn,
-    is_clean_code,
     is_comprehensive_name,
     is_paddle_api,
     is_strict_mode,

python/paddle/jit/sot/utils/envs.py

@@ -25,11 +25,9 @@
     StringListEnvironmentVariable,
 )
 
-ENV_COST_MODEL = BooleanEnvironmentVariable("COST_MODEL", False)
 ENV_MIN_GRAPH_SIZE = IntegerEnvironmentVariable("MIN_GRAPH_SIZE", 10)
 ENV_SOT_LOG_LEVEL = IntegerEnvironmentVariable("SOT_LOG_LEVEL", 0)
 ENV_STRICT_MODE = BooleanEnvironmentVariable("STRICT_MODE", False)
-ENV_CLEAN_CODE = BooleanEnvironmentVariable("CLEAN_CODE", False)
 ENV_SOT_WITH_CONTROL_FLOW = BooleanEnvironmentVariable(
     "SOT_WITH_CONTROL_FLOW", True
 )
@@ -60,12 +58,6 @@
 )
 
 
-@contextmanager
-def cost_model_guard(value: bool):
-    with EnvironmentVariableGuard(ENV_COST_MODEL, value):
-        yield
-
-
 @contextmanager
 def strict_mode_guard(value: bool):
     with EnvironmentVariableGuard(ENV_STRICT_MODE, value):

python/paddle/jit/sot/utils/utils.py

@@ -22,7 +22,6 @@
 import weakref
 from collections import OrderedDict
 from contextlib import contextmanager
-from enum import Enum
 from typing import TYPE_CHECKING, Any, Callable, TypeVar
 from weakref import WeakValueDictionary
 
@@ -32,8 +31,6 @@
 from paddle.utils import flatten, map_structure
 
 from .envs import (
-    ENV_CLEAN_CODE,
-    ENV_COST_MODEL,
     ENV_SOT_LOG_LEVEL,
     ENV_STRICT_MODE,
 )
@@ -319,10 +316,6 @@ def is_strict_mode():
     return ENV_STRICT_MODE.get()
 
 
-def is_clean_code() -> bool:
-    return ENV_CLEAN_CODE.get()
-
-
 def list_find_index_by_id(li: list[Any], item: Any) -> int:
     return [id(it) for it in li].index(id(item))
 
@@ -409,69 +402,15 @@ def printable(obj):
         return False
 
 
-class StepState(Enum):
-    COLLECT_INFO = 1
-    RUN_SOT = 2
-    RUN_DYN = 3
-
-
 class StepInfo:
-    REQUIRED_DYN_INFOS = 10
-    REQUIRED_SOT_INFOS = 10
-
-    USED_DYN_INFOS = 5
-
-    COLLECT_INFO_MAX_STEP = 50
-    CV_BOUNDARY = 0.1
-
     BACK_TRACE_STEPS = 20
 
     def __init__(self):
         self.step_count = -1
-        self.state = (
-            StepState.COLLECT_INFO
-            if ENV_COST_MODEL.get()
-            else StepState.RUN_SOT
-        )
-        self.dyn_time_costs = []
-        self.avg_dyn_time = 0
-        self.sot_time_costs = []
-        self.sot_step = -1
-
-    def add_dynamic_time_info(self, time_cost):
-        self.dyn_time_costs.append(time_cost)
-        if len(self.dyn_time_costs) == self.REQUIRED_DYN_INFOS:
-            self.avg_dyn_time = np.mean(
-                self.dyn_time_costs[-self.USED_DYN_INFOS :]
-            )
-
-    def add_sot_time_info(self, time_cost, current_code):
-        self.sot_time_costs.append(time_cost)
-        if len(self.sot_time_costs) == self.REQUIRED_SOT_INFOS:
-            avg_sot_time = np.mean(self.sot_time_costs)
-            log(
-                1,
-                f"[Cost Model] sot: {avg_sot_time}, dyn: {self.avg_dyn_time}\n",
-            )
-            if avg_sot_time < self.avg_dyn_time:
-                log(1, f"[Cost Model] Switch to RUN_SOT: {current_code} \n")
-                self.state = StepState.RUN_SOT
-            elif (
-                self.step_count > self.COLLECT_INFO_MAX_STEP
-                or np.std(self.sot_time_costs) / avg_sot_time < self.CV_BOUNDARY
-            ):
-                log(1, f"[Cost Model] Switch to RUN_DYN: {current_code}\n")
-                self.state = StepState.RUN_DYN
-            else:
-                log(1, f"[Cost Model] Decision delayed: {current_code}\n")
-                self.sot_time_costs.clear()
 
     def need_back_trace(self):
         return self.step_count < self.BACK_TRACE_STEPS
 
-    def need_dynamic_info(self):
-        return len(self.dyn_time_costs) < self.REQUIRED_DYN_INFOS
-
 
 class StepInfoManager(metaclass=Singleton):
     def __init__(self):
@@ -491,34 +430,11 @@ def step_guard(self, code):
             self.current_step_info = self.step_record[code]
 
             self.current_step_info.step_count += 1
-
-            log(
-                2,
-                f"[Cost Model] New step start, current state is {self.current_state}\n",
-            )
             yield
         finally:
             self.current_code = old_code
             self.current_step_info = old_info
 
-    def sot_step(self):
-        self.current_step_info.sot_step += 1
-
-    def collect_info(self, impl_dynamic, impl_sot, /, *args, **kwargs):
-        if self.current_step_info.need_dynamic_info():
-            start_time = time.perf_counter()
-            outs = impl_dynamic(*args, **kwargs)
-            time_cost = time.perf_counter() - start_time
-            self.current_step_info.add_dynamic_time_info(time_cost)
-        else:
-            start_time = time.perf_counter()
-            outs = impl_sot(*args, **kwargs)
-            time_cost = time.perf_counter() - start_time
-            self.current_step_info.add_sot_time_info(
-                time_cost, self.current_code
-            )
-        return outs
-
     @property
     def need_back_trace(self):
         return self.current_step_info.need_back_trace()
@@ -527,10 +443,6 @@ def need_back_trace(self):
     def current_step(self):
         return self.current_step_info.step_count
 
-    @property
-    def current_state(self):
-        return self.current_step_info.state
-
     def clear(self):
         self.step_record.clear()
         self.current_code = None