[Eager, Performance optimization] support mod / matmul ( % and @ operator) to...

[Eager, Performance optimization] support mod / matmul ( % and @ operator) to sink to Cpp layer (#46565)

* [Eager, Performance optimization] support mod ( % operator) to sink to Cpp layer

* fix mod logic

* support matmul math operator

* rm LOG(warning), use VLOG(6)

* fix conflicts mistake

paddle/fluid/pybind/eager_math_op_patch.cc

@@ -224,8 +224,7 @@ static PyObject* tensor__add__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -320,8 +319,7 @@ static PyObject* tensor__sub__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -414,8 +412,7 @@ static PyObject* tensor__rsub__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -515,8 +512,7 @@ static PyObject* tensor__mul__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -617,8 +613,7 @@ static PyObject* tensor__div__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -733,8 +728,7 @@ static PyObject* tensor__rdiv__method(TensorObject* self,
         other_tensor = cast_ad_func(other_tensor, promote_dtype);
       }
     } else {
-      LOG(WARNING)
-          << "The dtype of left and right Tensor are not the same, left "
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                  "dtype is "
               << lhs_dtype << ", but right dtype is " << rhs_dtype
               << ", the right dtype will convert to " << lhs_dtype;
@@ -829,7 +823,7 @@ static PyObject* tensor__gt__method(TensorObject* self,
   phi::DataType lhs_dtype = self_tensor.dtype();
   phi::DataType rhs_dtype = other_tensor.dtype();
   if (lhs_dtype != rhs_dtype) {
-    LOG(WARNING) << "The dtype of left and right Tensor are not the same, left "
+    VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                "dtype is "
             << lhs_dtype << ", but right dtype is " << rhs_dtype
             << ", the right dtype will convert to " << lhs_dtype;
@@ -914,7 +908,7 @@ static PyObject* tensor__ge__method(TensorObject* self,
   phi::DataType lhs_dtype = self_tensor.dtype();
   phi::DataType rhs_dtype = other_tensor.dtype();
   if (lhs_dtype != rhs_dtype) {
-    LOG(WARNING) << "The dtype of left and right Tensor are not the same, left "
+    VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                "dtype is "
             << lhs_dtype << ", but right dtype is " << rhs_dtype
             << ", the right dtype will convert to " << lhs_dtype;
@@ -933,6 +927,192 @@ static PyObject* tensor__ge__method(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
+static PyObject* tensor__mod__method(TensorObject* self,
+                                     PyObject* args,
+                                     PyObject* kwargs) {
+  paddle::platform::RecordEvent pythonc_record_event(
+      "__mod__ pybind_patch_func",
+      paddle::platform::TracerEventType::UserDefined,
+      1);
+  EAGER_TRY
+
+  VLOG(6) << "Running Eager tensor__mod__method";
+
+  // Set Device ID
+  auto place = egr::Controller::Instance().GetExpectedPlace();
+  SetDevice(place);
+
+  paddle::experimental::Tensor ret;
+  paddle::experimental::Tensor self_tensor = self->tensor;
+
+  PyObject* other_obj = PyTuple_GET_ITEM(args, 0);
+
+  // 1. scalar exists cases
+  // there is no scalar_mod function for __mod__ now
+  float other_float = 0.0;
+  bool has_other_float = false;
+  if (PyFloat_Check(other_obj) || PyCheckInteger(other_obj) ||
+      IsNumpyType(other_obj)) {
+    if (PyFloat_Check(other_obj)) {
+      other_float = CastPyArg2AttrFloat(other_obj, 0);
+      has_other_float = true;
+      if (_supported_int_dtype_.find(self_tensor.dtype()) !=
+          _supported_int_dtype_.end()) {
+        eager_gil_scoped_release guard;
+        self_tensor = cast_ad_func(self_tensor, DataType::FLOAT32);
+      }
+    } else if (PyCheckInteger(other_obj) || IsNumpyType(other_obj)) {
+      other_float = static_cast<float>(CastPyArg2AttrInt(other_obj, 0));
+      has_other_float = true;
+    }
+  }
+
+  // 2. create or get tensor for other_obj
+  paddle::experimental::Tensor other_tensor;
+  if (has_other_float) {
+    eager_gil_scoped_release guard;
+    other_tensor = full_ad_func(self_tensor.shape(),
+                                phi::Scalar(other_float),
+                                self_tensor.dtype(),
+                                place);
+  } else if (!PyCheckTensor(other_obj)) {
+    paddle::experimental::Scalar value =
+        CastPyArg2Scalar(other_obj, "__mod__", 0);
+    if (PyComplex_Check(other_obj)) {
+      eager_gil_scoped_release guard;
+      other_tensor = full_ad_func({1}, value, DataType::COMPLEX64, place);
+    } else {
+      eager_gil_scoped_release guard;
+      other_tensor =
+          full_ad_func(self_tensor.shape(), value, self_tensor.dtype(), place);
+    }
+  } else {
+    other_tensor = CastPyArg2Tensor(other_obj, 0);
+  }
+
+  // 3. promote types or unify right var type to left var
+  phi::DataType lhs_dtype = self_tensor.dtype();
+  phi::DataType rhs_dtype = other_tensor.dtype();
+  if (lhs_dtype != rhs_dtype) {
+    VLOG(6) << "The  dtype of left and right Tensor are not the same, left "
+               "dtype is "
+            << lhs_dtype << ", but right dtype is " << rhs_dtype
+            << ", the right dtype will convert to " << lhs_dtype;
+    eager_gil_scoped_release guard;
+    other_tensor = cast_ad_func(other_tensor, lhs_dtype);
+  }
+
+  // 4. calculation
+  VLOG(6) << "Calling remainder_ad_func in tensor__mod__method";
+  {
+    eager_gil_scoped_release guard;
+    ret = remainder_ad_func(self_tensor, other_tensor);
+  }
+  return ToPyObject(ret);
+  EAGER_CATCH_AND_THROW_RETURN_NULL
+}
+
+static PyObject* tensor__matmul__method(TensorObject* self,
+                                        PyObject* args,
+                                        PyObject* kwargs) {
+  paddle::platform::RecordEvent pythonc_record_event(
+      "__matmul__ pybind_patch_func",
+      paddle::platform::TracerEventType::UserDefined,
+      1);
+  EAGER_TRY
+
+  VLOG(6) << "Running Eager tensor__matmul__method";
+
+  // Set Device ID
+  auto place = egr::Controller::Instance().GetExpectedPlace();
+  SetDevice(place);
+
+  paddle::experimental::Tensor ret;
+  paddle::experimental::Tensor self_tensor = self->tensor;
+
+  PyObject* other_obj = PyTuple_GET_ITEM(args, 0);
+
+  // 1. scalar exists cases
+  // there is no scalar_matmul function for __matmul__ now
+  float other_float = 0.0;
+  bool has_other_float = false;
+  if (PyFloat_Check(other_obj) || PyCheckInteger(other_obj) ||
+      IsNumpyType(other_obj)) {
+    if (PyFloat_Check(other_obj)) {
+      other_float = CastPyArg2AttrFloat(other_obj, 0);
+      has_other_float = true;
+      if (_supported_int_dtype_.find(self_tensor.dtype()) !=
+          _supported_int_dtype_.end()) {
+        eager_gil_scoped_release guard;
+        self_tensor = cast_ad_func(self_tensor, DataType::FLOAT32);
+      }
+    } else if (PyCheckInteger(other_obj) || IsNumpyType(other_obj)) {
+      other_float = static_cast<float>(CastPyArg2AttrInt(other_obj, 0));
+      has_other_float = true;
+    }
+  }
+
+  // 2. create or get tensor for other_obj
+  paddle::experimental::Tensor other_tensor;
+  if (has_other_float) {
+    eager_gil_scoped_release guard;
+    other_tensor =
+        full_ad_func({1}, phi::Scalar(other_float), self_tensor.dtype(), place);
+  } else if (!PyCheckTensor(other_obj)) {
+    paddle::experimental::Scalar value =
+        CastPyArg2Scalar(other_obj, "__matmul__", 0);
+    if (PyComplex_Check(other_obj)) {
+      eager_gil_scoped_release guard;
+      other_tensor = full_ad_func({1}, value, DataType::COMPLEX64, place);
+    } else {
+      eager_gil_scoped_release guard;
+      other_tensor = full_ad_func({1}, value, self_tensor.dtype(), place);
+    }
+  } else {
+    other_tensor = CastPyArg2Tensor(other_obj, 0);
+  }
+
+  // 3. promote types or unify right var type to left var
+  phi::DataType lhs_dtype = self_tensor.dtype();
+  phi::DataType rhs_dtype = other_tensor.dtype();
+  if (lhs_dtype != rhs_dtype) {
+    // note: only op_type in _supported_promote_complex_types_ should promote
+    // dtype
+    if (_complex_dtypes.find(lhs_dtype) != _complex_dtypes.end() ||
+        _complex_dtypes.find(rhs_dtype) != _complex_dtypes.end()) {
+      phi::DataType promote_dtype =
+          framework::TransToPhiDataType(framework::PromoteTypesIfComplexExists(
+              framework::TransToProtoVarType(lhs_dtype),
+              framework::TransToProtoVarType(rhs_dtype)));
+      if (lhs_dtype != promote_dtype) {
+        // cast
+        eager_gil_scoped_release guard;
+        self_tensor = cast_ad_func(self_tensor, promote_dtype);
+      }
+      if (rhs_dtype != promote_dtype) {
+        eager_gil_scoped_release guard;
+        other_tensor = cast_ad_func(other_tensor, promote_dtype);
+      }
+    } else {
+      VLOG(6) << "The dtype of left and right Tensor are not the same, left "
+                 "dtype is "
+              << lhs_dtype << ", but right dtype is " << rhs_dtype
+              << ", the right dtype will convert to " << lhs_dtype;
+      eager_gil_scoped_release guard;
+      other_tensor = cast_ad_func(other_tensor, lhs_dtype);
+    }
+  }
+
+  // 4. calculation
+  VLOG(6) << "Calling matmul_ad_func in tensor__matmul__method";
+  {
+    eager_gil_scoped_release guard;
+    ret = matmul_ad_func(self_tensor, other_tensor, false, false);
+  }
+  return ToPyObject(ret);
+  EAGER_CATCH_AND_THROW_RETURN_NULL
+}
+
 static PyObject* tensor__lt__method(TensorObject* self,
                                     PyObject* args,
                                     PyObject* kwargs) {
@@ -999,7 +1179,7 @@ static PyObject* tensor__lt__method(TensorObject* self,
   phi::DataType lhs_dtype = self_tensor.dtype();
   phi::DataType rhs_dtype = other_tensor.dtype();
   if (lhs_dtype != rhs_dtype) {
-    LOG(WARNING) << "The dtype of left and right Tensor are not the same, left "
+    VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                "dtype is "
             << lhs_dtype << ", but right dtype is " << rhs_dtype
             << ", the right dtype will convert to " << lhs_dtype;
@@ -1084,7 +1264,7 @@ static PyObject* tensor__le__method(TensorObject* self,
   phi::DataType lhs_dtype = self_tensor.dtype();
   phi::DataType rhs_dtype = other_tensor.dtype();
   if (lhs_dtype != rhs_dtype) {
-    LOG(WARNING) << "The dtype of left and right Tensor are not the same, left "
+    VLOG(6) << "The dtype of left and right Tensor are not the same, left "
                "dtype is "
             << lhs_dtype << ", but right dtype is " << rhs_dtype
             << ", the right dtype will convert to " << lhs_dtype;
@@ -1144,6 +1324,14 @@ PyMethodDef math_op_patch_methods[] = {
      (PyCFunction)(void (*)(void))tensor__rdiv__method,
      METH_VARARGS | METH_KEYWORDS,
      NULL},
+    {"__mod__",
+     (PyCFunction)(void (*)(void))tensor__mod__method,
+     METH_VARARGS | METH_KEYWORDS,
+     NULL},
+    {"__matmul__",
+     (PyCFunction)(void (*)(void))tensor__matmul__method,
+     METH_VARARGS | METH_KEYWORDS,
+     NULL},
     {"__gt__",
      (PyCFunction)(void (*)(void))tensor__gt__method,
      METH_VARARGS | METH_KEYWORDS,

python/paddle/fluid/dygraph/math_op_patch.py

@@ -393,10 +393,6 @@ def monkey_patch_math_varbase():
                                       None)),
         ('__floordiv__',
          _binary_creator_('__floordiv__', 'floor_divide', False, None, True)),
-        ('__mod__', _binary_creator_('__mod__', 'remainder', False, None,
-                                     True)),
-        ('__matmul__',
-         _binary_creator_('__matmul__', "matmul", False, None, True)),
         # for logical compare
         ('__eq__', _binary_creator_('__eq__', 'equal', False, None, True)),
         ('__ne__', _binary_creator_('__ne__', 'not_equal', False, None, True)),
@@ -414,6 +410,8 @@ def monkey_patch_math_varbase():
         '__truediv__',
         '__rdiv__',
         '__rtruediv__',
+        '__mod__',
+        '__matmul__',
         '__gt__',
         '__ge__',
         '__lt__',

python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py

@@ -732,6 +732,22 @@ class TestMathOpPatchesVarBase(unittest.TestCase):
             self.func_test_complex_scalar()
         self.func_test_complex_scalar()
 
+    def func_test_matmul(self):
+        x_np = np.random.uniform(-1, 1, [2, 3]).astype(self.dtype)
+        y_np = np.random.uniform(-1, 1, [3, 2]).astype(self.dtype)
+        except_out = x_np @ y_np
+
+        with fluid.dygraph.guard():
+            x = paddle.to_tensor(x_np)
+            y = paddle.to_tensor(y_np)
+            out = x @ y
+            np.testing.assert_allclose(out.numpy(), except_out, atol=1e-03)
+
+    def test_matmul(self):
+        with _test_eager_guard():
+            self.func_test_matmul()
+        self.func_test_matmul()
+
 
 if __name__ == '__main__':
     unittest.main()