Support hook to take effect only when user-defined conditions are met (…

…#23)

* Support hook to take effect only when user-defined conditions are met

* Support hook to take effect only when user-defined conditions are met

op_tools/__init__.py

@@ -8,4 +8,4 @@
     OpDtypeCast,
 )
 
-from .custom_apply_hook import fallback_ops, dump_all_ops_args
+from .custom_apply_hook import apply_feature

op_tools/base_hook.py

@@ -7,7 +7,7 @@
 def is_should_apply_hook(name, func, *args, **kwargs):
     if name is None:
         return False
-    if inspect.isroutine(func) == False:
+    if callable(func) == False:
         return False
     if name.startswith("torch.Tensor.") and (
         name.endswith("__get__") or name.endswith("__set__")
@@ -47,6 +47,18 @@ def __init__(self, name, func) -> None:
         self.exception = None
         self.func = func
         self.wrapper_func = self.construct_wrapper_func()
+        self.condition_funcs = []
+
+    def add_condition_func(self, func):
+        if not callable(func):
+            raise ValueError("condition_func must be callable")
+        self.condition_funcs.append(func)
+
+    def conditions_met(self, *args, **kwargs):
+        for func in self.condition_funcs:
+            if not func(*args, **kwargs):
+                return False
+        return True
 
     def before_call_op(self, *args, **kwargs):
         self.args = args
@@ -80,9 +92,9 @@ def is_should_apply(self, *args, **kwargs):
 
     def __call__(self, *args, **kwargs):
         self.args_on_cpu, self.device = is_cpu_op(*args, **kwargs)
-        # import pdb; pdb.set_trace()
         if (
             self.enable
+            and self.conditions_met(*args, **kwargs)
             and not self.args_on_cpu
             and is_should_apply_hook(self.name, self.func, *args, **kwargs)
             and self.is_should_apply(*args, **kwargs)

op_tools/custom_apply_hook.py

@@ -25,8 +25,10 @@ def get_func_name(func):
     return name
 
 
-def apply_hook_to_ops(ops, hook):
+def apply_hook_to_ops(ops, hook, condition_funcs=[]):
+    index = -1
     for op in traverse_container(ops):
+        index += 1
         if isinstance(op, str):
             func = get_function_from_string(op)
             name = op
@@ -46,29 +48,48 @@ def apply_hook_to_ops(ops, hook):
             continue
         if not hasattr(func, "__name__"):
             func.__name__ = name.split(".")[-1]
+        if isinstance(condition_funcs, list):
+            if len(condition_funcs) > index:
+                condition_func = condition_funcs[index]
+            else:
+                condition_func = lambda *args, **kwargs: True
+        else:
+            condition_func = condition_funcs
+        assert callable(condition_func)
+
         hook_obj = hook(name, func)
+        hook_obj.add_condition_func(condition_func)
         setattr(module, func.__name__, hook_obj)
 
 
-def fallback_ops(ops):
-    apply_hook_to_ops(ops, OpFallbackHook)
-
-
-def fallback_op_if(op, condition=lambda *args, **kwargs: False):
-    apply_hook_to_ops(op, OpFallbackHook)
-
-
-def dump_ops_args(ops):
-    apply_hook_to_ops(ops, OpDispatchWatcherHook)
-
-
-def dump_all_ops_args():
-    apply_hook_to_ops(torch, OpDispatchWatcherHook)
-
-
-def autocompare_ops(ops):
-    apply_hook_to_ops(ops, OpAutoCompareHook)
-
-
-def measure_ops_elasped(ops):
-    apply_hook_to_ops(ops, OpTimeMeasureHook)
+def apply_feature(ops, feature, condition_func=lambda *args, **kwargs: True):
+    assert isinstance(ops, (str, list))
+    feature_options = [
+        "fallback",
+        "autocompare",
+        "measure_op_time",
+        "dump_op_args",
+        "cast_dtype",
+    ]
+    assert (
+        feature in feature_options
+    ), f"feature must be one of {feature_options}, but got {feature}"
+    assert callable(condition_func)
+    if feature == "fallback":
+        hook_cls = OpFallbackHook
+    elif feature == "autocompare":
+        hook_cls = OpAutoCompareHook
+    elif feature == "measure_op_time":
+        hook_cls = OpTimeMeasureHook
+    elif feature == "dump_op_args":
+        hook_cls = OpDispatchWatcherHook
+    elif feature == "cast_dtype":
+        hook_cls = OpDtypeCastHook
+
+    if isinstance(ops, str):
+        apply_hook_to_ops(ops, hook_cls, condition_func)
+    elif isinstance(ops, list):
+        for op in ops:
+            apply_hook_to_ops(op, hook_cls, condition_func)
+    else:
+        assert False, f"ops must be str or list, but got {type(ops)}"

op_tools/op_autocompare_hook.py

@@ -176,10 +176,12 @@ def before_call_op(self, *args, **kwargs):
             self.args_cpu = to_device(
                 "cpu",
                 self.args,
+                detach=True,
             )
             self.kwargs_cpu = to_device(
                 "cpu",
                 self.kwargs or {},
+                detach=True,
             )
 
     def after_call_op(self, result):
@@ -189,7 +191,7 @@ def after_call_op(self, result):
             self.result = result
             try:
                 self.result_cpu = self.func(*self.args_cpu, **self.kwargs_cpu)
-                self.result_device = to_device("cpu", self.result)
+                self.result_device = to_device("cpu", self.result, detach=True)
                 self.dtype_cast_dict = dict()
                 args_cpu = self.args_cpu
             except Exception as e:
@@ -199,11 +201,13 @@ def after_call_op(self, result):
                     "cpu",
                     self.args_cpu,
                     dtype_cast_dict=self.dtype_cast_dict,
+                    detach=True,
                 )
                 self.kwargs_cpu = to_device(
                     "cpu",
                     self.kwargs_cpu or {},
                     dtype_cast_dict=self.dtype_cast_dict,
+                    detach=True,
                 )
                 # RuntimeError: a leaf Variable that requires grad is being used in an in-place operation.
                 if (is_inplace_op(self.name) or is_view_op(self.name)) and self.args[
@@ -220,6 +224,7 @@ def after_call_op(self, result):
                     "cpu",
                     self.result,
                     dtype_cast_dict=self.dtype_cast_dict,
+                    detach=True,
                 )
 
             if is_inplace_op(self.name):
@@ -259,12 +264,16 @@ def after_call_op(self, result):
                 if isinstance(arg, torch.Tensor) and arg.requires_grad:
                     self.backward_hook_handle.register_tensor_hook(index, arg)
 
-            self.args = to_device("cpu", self.args)
-            self.kwargs = to_device("cpu", self.kwargs or {})
+            self.args = to_device("cpu", self.args, detach=True)
+            self.kwargs = to_device("cpu", self.kwargs or {}, detach=True)
 
     def run_backward_on_cpu(self, grad_inputs, grad_output):
-        self.grad_outputs_cpu = to_device("cpu", grad_output, self.dtype_cast_dict)
-        self.grad_inputs_cpu = to_device("cpu", grad_inputs, self.dtype_cast_dict)
+        self.grad_outputs_cpu = to_device(
+            "cpu", grad_output, dtype_cast_dict=self.dtype_cast_dict, detach=True
+        )
+        self.grad_inputs_cpu = to_device(
+            "cpu", grad_inputs, dtype_cast_dict=self.dtype_cast_dict, detach=True
+        )
         for arg_cpu in traverse_container(self.args_cpu):
             if isinstance(arg_cpu, torch.Tensor) and arg_cpu.grad is not None:
                 arg_cpu.grad.zero_()
@@ -332,7 +341,9 @@ def compare_all_grad(self):
     def set_input_grad(self, index, grad):
         if not hasattr(self, "args_grad"):
             self.args_grad = [None for i in range(len(self.args))]
-        self.args_grad[index] = to_device("cpu", grad, self.dtype_cast_dict)
+        self.args_grad[index] = to_device(
+            "cpu", grad, dtype_cast_dict=self.dtype_cast_dict, detach=True
+        )
 
     def save_forward_args(self):
         save_op_args(

op_tools/op_dtype_cast_hook.py

@@ -33,9 +33,17 @@ def before_call_op(self, *args, **kwargs):
             self.is_cpu_op, self.device = is_cpu_op(*args, **kwargs)
             if self.is_cpu_op:
                 return
-            self.args = to_device(self.device, self.args, self.dtype_cast_dict, False)
+            self.args = to_device(
+                self.device,
+                self.args,
+                dtype_cast_dict=self.dtype_cast_dict,
+                detach=False,
+            )
             self.kwargs = to_device(
-                self.device, self.kwargs or {}, self.dtype_cast_dict, False
+                self.device,
+                self.kwargs or {},
+                dtype_cast_dict=self.dtype_cast_dict,
+                detach=False,
             )
             self.dtype_cast_back_dict = {}
             self.ins_list = []
@@ -62,7 +70,10 @@ def after_call_op(self, result):
         with DisableHookGuard():
             self.result_raw = result
             self.result = to_device(
-                self.device, self.result, self.dtype_cast_back_dict, False
+                self.device,
+                self.result,
+                dtype_cast_dict=self.dtype_cast_back_dict,
+                detach=False,
             )
             i = -1
             for out in traverse_container(self.result_raw):