replace append_op with C_ops for assign op (#41118)

* support C_ops assign

* open unittest

* fix clone

paddle/fluid/eager/auto_code_generator/eager_generator.cc

@@ -2803,7 +2803,7 @@ static void DygraphCodeGeneration(const std::string& output_dir) {
     // Inplace Function Generator.
     // `sum` op has duplicate input. Don't consider adding inplace strategy
     // for `sum` in temporary.
-    if (op_type != "sum" && infer_inplace) {
+    if (infer_inplace && !special_inplace_op_set.count(op_type)) {
       auto in_to_outs = infer_inplace(true);
       for (auto& inplace_pair : in_to_outs) {
         inplace_map[inplace_pair.second] = inplace_pair.first;

paddle/fluid/eager/tensor_wrapper.h

@@ -94,9 +94,9 @@ class TensorWrapper {
       return paddle::experimental::Tensor();
     }
 
+    check_inplace_version();
     // if it's full_reserved just return the full copy of tensor
     if (full_reserved_) {
-      check_inplace_version();
       return intermidiate_tensor_;
     } else {
       std::shared_ptr<GradNodeBase> new_grad_node = grad_node;
@@ -105,7 +105,6 @@ class TensorWrapper {
       intermidiate_tensor_.set_autograd_meta(
           std::static_pointer_cast<paddle::experimental::AbstractAutogradMeta>(
               p_ab_autograd_meta));
-      check_inplace_version();
       return intermidiate_tensor_;
     }
   }

paddle/fluid/pybind/eager_op_function_generator.cc

@@ -433,7 +433,7 @@ GenerateOpFunctions() {
     std::map<std::string, std::string> inplace_map;
     // `sum` op has duplicate input. Don't consider adding inplace strategy
     // for `sum` in temporary.
-    if (op_type != "sum" && infer_inplace) {
+    if (infer_inplace && !special_inplace_op_set.count(op_type)) {
       // Inplace OP: op_type_.
       // The inplace OP needs a new implementation method.
       auto in_to_outs = infer_inplace(true);

paddle/fluid/pybind/op_function_generator.h

@@ -222,6 +222,7 @@ std::map<std::string, std::set<std::string>> op_passing_outs_map = {
     {"c_reduce", {"Out"}},
     {"c_scatter", {"Out"}},
     {"barrier", {"Out"}},
+    {"assign", {"Out"}},
     {"fake_quantize_dequantize_moving_average_abs_max",
      {"Out", "OutScale", "OutAccum", "OutState"}},
     {"fake_quantize_dequantize_abs_max", {"Out", "OutScale"}},
@@ -249,3 +250,12 @@ std::map<std::string, std::pair<std::string, std::string>> view_op_map = {
     {"reshape2", {"X", "Out"}},
     {"flatten_contiguous_range", {"X", "Out"}},
 };
+
+// NOTE(pangyoki): Special inplace ops that are not supported in temporary.
+// The input and output of some inplace ops are special, such as
+// duplicate input. These inplace ops have no usage scenarios and
+// are not supported in temporary.
+std::set<std::string> special_inplace_op_set = {
+    "sum",     // `sum` op has duplicate input
+    "assign",  // output of `assign` op is in `op_passing_outs_map`
+};

python/paddle/fluid/dygraph/varbase_patch_methods.py

@@ -20,7 +20,7 @@ import sys
 
 import paddle
 from .. import framework
-from ..framework import convert_np_dtype_to_dtype_
+from ..framework import convert_np_dtype_to_dtype_, _in_legacy_dygraph
 from .. import core
 from .. import unique_name
 from ..framework import Variable, Parameter, ParamBase, _getitem_impl_, _setitem_impl_, EagerParamBase
@@ -798,7 +798,11 @@ def monkey_patch_varbase():
 
     @framework.dygraph_only
     def clone(self):
-        return _C_ops.assign(self)
+        if _in_legacy_dygraph():
+            output = core.VarBase()
+        else:
+            output = core.eager.Tensor()
+        return _C_ops.assign(self, output)
 
     @framework.dygraph_only
     def value(self):

python/paddle/fluid/layers/tensor.py

@@ -606,6 +606,14 @@ def assign(input, output=None):
     # isinstance(VarBase, Variable) == False. It will cause return None
     # after this api.
     if isinstance(input, (Variable, core.VarBase)):
+        if _non_static_mode():
+            if output is None:
+                if _in_legacy_dygraph():
+                    output = core.VarBase()
+                else:
+                    output = core.eager.Tensor()
+            _C_ops.assign(input, output)
+        else:
             check_dtype(input.dtype, 'input', [
                 'float16', 'uint16', 'float32', 'float64', 'int32', 'int64',
                 'uint8', 'bool'
@@ -614,7 +622,8 @@ def assign(input, output=None):
                 output = helper.create_variable_for_type_inference(
                     dtype=input.dtype)
             helper.append_op(
-            type='assign', inputs={'X': [input]}, outputs={'Out': [output]})
+                type='assign', inputs={'X': [input]},
+                outputs={'Out': [output]})
     elif isinstance(input, numpy.ndarray):
         # Not support [var, var, ...] currently.
         if len(input.shape) > 0 and any(isinstance(x, Variable) for x in input):
@@ -663,8 +672,6 @@ def assign(input, output=None):
             })
 
     if is_inplace and _non_static_mode():
-        # TODO(jiabin): Remove this when we support inplace
-        if _in_legacy_dygraph():
         output._bump_inplace_version()
 
     return output

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

@@ -31,10 +31,6 @@ class TestInplace(unittest.TestCase):
             var[0] = 1.1
             self.assertEqual(var.inplace_version, 1)
 
-            # TODO1: assign don't support inplace in temporary
-            if in_dygraph_mode():
-                var[0] = 2
-            else:
             paddle.assign(paddle.ones(shape=[3]), var)
 
             # NOTE(liym27): assign(input, output) is an inplace operation for output.
@@ -122,7 +118,7 @@ class TestInplace(unittest.TestCase):
             loss.backward()
 
     def test_backward_success_2(self):
-        # TODO2: need to process no_need_buffer in eager mode
+        # TODO: need to process no_need_buffer in eager mode
         # with _test_eager_guard():
         #     self.func_test_backward_success_2()
         self.func_test_backward_success_2()