Remove axis in some elementwise api (#50190)

* remove axis in some elementwise api

* fix inplace bug eager-gen

* fix bug

* revert change for CheckInplace

* polish code

paddle/fluid/eager/auto_code_generator/generator/eager_gen.py

@@ -261,6 +261,9 @@ FORWARD_ONLY_FUNCTION_TEMPLATE = """
   // Get Outputs
 {}
   VLOG(4) << \"Finish AD API: {}";
+
+  // Check Inplace if needed
+{}{}
   // LOG IF DEBUG
   {}
   // Returns
@@ -1462,8 +1465,31 @@ class DygraphForwardFunctionGenerator(DygraphFunctionGeneratorBase):
             returns_str = ", ".join(returns_list)
             returns_str = f"{returns_type_str}{{{returns_str}}}"
 
+        # Check Inplace
+        check_inplace_str = ""
+        bump_inplace_version_str = ""
+        # Note: When the name of original api in yaml is end of '_', that means this api is a
+        # special inplace api and it doesn't require checking and bumping version (except assign_out_).
+        # This rule is obscure, so we maybe replace it by adding new design in the future.
+        if is_inplaced and (
+            self.forward_api_name[-1] != '_'
+            or self.forward_api_name == 'assign_out_'
+        ):
+            for inplace_name in forward_inplace_map.keys():
+                if (
+                    not self.is_forward_only
+                    and forward_api_name not in inplace_check_blacklist
+                ):
+                    check_inplace_str += CHECK_INPLACE_TEMPLATE.format(
+                        inplace_name, GetAutoGradMetaName(inplace_name)
+                    )
+                bump_inplace_version_str += (
+                    BUMP_INPLACE_VERSION_TEMPLATE.format(
+                        inplace_name, inplace_name
+                    )
+                )
+
         # Node Creation Pre-Processing
-        inputs_names = []
         if not self.is_forward_only:
             # 1. Get Input AutoGradMeta
             inputs_autograd_meta_list = []
@@ -1478,13 +1504,9 @@ class DygraphForwardFunctionGenerator(DygraphFunctionGeneratorBase):
                 ) in backward_grad_outputs_map.items():
                     if pos == corresponding_pos:
                         has_corresponding_grad_output = True
-                if (
-                    has_corresponding_grad_output
-                    or (
+                if has_corresponding_grad_output or (
                     name in forward_inplace_map
                     and forward_api_name not in inplace_check_blacklist
-                    )
-                    or self.is_forward_only
                 ):
                     input_autograd_meta_name = GetAutoGradMetaName(name)
                     if IsPlainTensorType(ttype):
@@ -1532,24 +1554,6 @@ class DygraphForwardFunctionGenerator(DygraphFunctionGeneratorBase):
                 outputs_autograd_meta_list.append(output_autograd_meta)
             outputs_autograd_meta_str = "\n".join(outputs_autograd_meta_list)
 
-            # 3. Check Inplace
-            check_inplace_str = ""
-            bump_inplace_version_str = ""
-            if is_inplaced:
-                for inplace_name in forward_inplace_map.keys():
-                    if forward_api_name not in inplace_check_blacklist:
-                        inplace_autograd_meta_name = GetAutoGradMetaName(
-                            inplace_name
-                        )
-                        check_inplace_str += CHECK_INPLACE_TEMPLATE.format(
-                            inplace_name, inplace_autograd_meta_name
-                        )
-                    bump_inplace_version_str += (
-                        BUMP_INPLACE_VERSION_TEMPLATE.format(
-                            inplace_name, inplace_name
-                        )
-                    )
-
             # Node Creation
             self.GenerateNodeCreationCodes()
             node_creation_str = self.node_creation_str
@@ -1643,6 +1647,8 @@ class DygraphForwardFunctionGenerator(DygraphFunctionGeneratorBase):
                     forward_call_str,
                     get_outputs_str,
                     forward_api_name,
+                    check_inplace_str,
+                    bump_inplace_version_str,
                     log_str,
                     returns_str,
                 )

paddle/phi/api/yaml/legacy_ops.yaml

@@ -1429,7 +1429,7 @@
 
 - op : remainder
   args : (Tensor x, Tensor y)
-  output : Tensor
+  output : Tensor (out)
   infer_meta :
     func : ElementwiseInferMeta
   kernel :

python/paddle/fluid/layers/nn.py

@@ -101,28 +101,6 @@ def _get_reduce_dim(dim, input):
     return reduce_all, dim
 
 
-@dygraph_only
-def _elementwise_op_in_dygraph(
-    x, y, axis=-1, act=None, use_mkldnn=False, op_name=None
-):
-    def is_inplace(op_name):
-        return op_name[-1] == "_"
-
-    if op_name not in OP_NAMEMAPPING.keys() or axis != -1:
-        op = getattr(_legacy_C_ops, op_name)
-        out = op(x, y, 'axis', axis, 'use_mkldnn', use_mkldnn)
-    else:
-        if in_dygraph_mode():
-            op = getattr(
-                _C_ops,
-                OP_NAMEMAPPING[op_name] if not is_inplace(op_name) else op_name,
-            )
-            out = op(x, y)
-    return dygraph_utils._append_activation_in_dygraph(
-        out, act, use_mkldnn=use_mkldnn
-    )
-
-
 @deprecated(since="2.0.0", update_to="paddle.nn.functional.embedding")
 def embedding(
     input,

python/paddle/fluid/tests/unittests/ir/inference/test_trt_elementwise_op.py

@@ -50,7 +50,7 @@ class TensorRTSubgraphPassElementwiseBroadcastTest(InferencePassTest):
         self.fetch_list = [out]
 
     def append_eltwise(self, data1, data2):
-        return paddle.tensor.math._add_with_axis(x=data1, y=data2, axis=0)
+        return paddle.tensor.math.add(x=data1, y=data2)
 
     def test_check_output(self):
         if os.path.exists(self.path + "_opt_cache"):
@@ -67,21 +67,21 @@ class TensorRTSubgraphPassElementwiseBroadcastTest1(
     TensorRTSubgraphPassElementwiseBroadcastTest
 ):
     def append_eltwise(self, data1, data2):
-        return paddle.tensor.math._subtract_with_axis(x=data1, y=data2, axis=0)
+        return paddle.tensor.math.subtract(x=data1, y=data2)
 
 
 class TensorRTSubgraphPassElementwiseBroadcastTest2(
     TensorRTSubgraphPassElementwiseBroadcastTest
 ):
     def append_eltwise(self, data1, data2):
-        return paddle.tensor.math._multiply_with_axis(x=data1, y=data2, axis=0)
+        return paddle.tensor.math.multiply(x=data1, y=data2)
 
 
 class TensorRTSubgraphPassElementwiseBroadcastTest3(
     TensorRTSubgraphPassElementwiseBroadcastTest
 ):
     def append_eltwise(self, data1, data2):
-        return paddle.tensor.math._divide_with_axis(x=data1, y=data2, axis=0)
+        return paddle.tensor.math.divide(x=data1, y=data2)
 
 
 if __name__ == "__main__":

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

@@ -222,7 +222,7 @@ class TestElementwiseDivDoubleGradCheck(unittest.TestCase):
         y = paddle.static.data('y', shape, dtype)
         x.persistable = True
         y.persistable = True
-        out = paddle.tensor.math._divide_with_axis(x, y, axis=0)
+        out = paddle.tensor.math.divide(x, y)
         x_arr = np.random.uniform(-1, 1, shape).astype(dtype)
         y_arr = np.random.uniform(-1, 1, shape).astype(dtype)
         y_arr[np.abs(y_arr) < 0.005] = 0.02

python/paddle/tensor/math.py

@@ -480,31 +480,6 @@ OP_NAMEMAPPING = {
 }
 
 
-@dygraph_only
-def _elementwise_op_in_dygraph(
-    x, y, axis=-1, act=None, use_mkldnn=False, op_name=None
-):
-    def is_inplace(op_name):
-        return op_name[-1] == "_"
-
-    if op_name not in OP_NAMEMAPPING.keys() or axis != -1:
-        op = getattr(_legacy_C_ops, op_name)
-        out = op(x, y, 'axis', axis, 'use_mkldnn', use_mkldnn)
-    else:
-        if in_dygraph_mode():
-            op = getattr(
-                _C_ops,
-                OP_NAMEMAPPING[op_name] if not is_inplace(op_name) else op_name,
-            )
-            out = op(x, y)
-    if act is None:
-        return out
-    else:
-        return dygraph_utils._append_activation_in_dygraph(
-            out, act, use_mkldnn=use_mkldnn
-        )
-
-
 def _elementwise_op(helper):
     op_type = helper.layer_type
     original_op_type = helper.kwargs.get('original_op_type', op_type)
@@ -616,8 +591,6 @@ def add_(x, y, name=None):
     Inplace version of ``add`` API, the output Tensor will be inplaced with input ``x``.
     Please refer to :ref:`api_tensor_add`.
     """
-    op_type = 'elementwise_add_'
-    axis = -1
 
     out_shape = broadcast_shape(x.shape, y.shape)
     if out_shape != x.shape:
@@ -627,11 +600,7 @@ def add_(x, y, name=None):
             )
         )
 
-    if in_dygraph_mode():
     return _C_ops.add_(x, y)
-    else:
-        out = _elementwise_op_in_dygraph(x, y, axis=axis, op_name=op_type)
-        return out
 
 
 def subtract(x, y, name=None):
@@ -690,13 +659,10 @@ def subtract(x, y, name=None):
             # Tensor(shape=[3], dtype=float64, place=Place(cpu), stop_gradient=True,
             #        [ 4.  ,  inf., -inf.])
     """
-    op_type = 'elementwise_sub'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.subtract(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_sub', **locals()))
 
 
 @inplace_apis_in_dygraph_only
@@ -705,8 +671,6 @@ def subtract_(x, y, name=None):
     Inplace version of ``subtract`` API, the output Tensor will be inplaced with input ``x``.
     Please refer to :ref:`api_tensor_subtract`.
     """
-    axis = -1
-    act = None
 
     out_shape = broadcast_shape(x.shape, y.shape)
     if out_shape != x.shape:
@@ -716,13 +680,7 @@ def subtract_(x, y, name=None):
             )
         )
 
-    if in_dygraph_mode():
     return _C_ops.subtract_(x, y)
-    else:
-        out = _elementwise_op_in_dygraph(
-            x, y, axis=axis, act=act, op_name='elementwise_sub_'
-        )
-        return out
 
 
 def divide(x, y, name=None):
@@ -757,13 +715,10 @@ def divide(x, y, name=None):
             print(z)  # [2., 0.6, 2.]
 
     """
-    op_type = 'elementwise_div'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.divide(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_div', **locals()))
 
 
 def floor_divide(x, y, name=None):
@@ -800,12 +755,10 @@ def floor_divide(x, y, name=None):
             print(z)  # [2, 0, 2, 2]
 
     """
-    op_type = 'elementwise_floordiv'
-    axis = -1
     if in_dygraph_mode():
         return _C_ops.floor_divide(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_floordiv', **locals()))
 
 
 def remainder(x, y, name=None):
@@ -841,13 +794,10 @@ def remainder(x, y, name=None):
             print(z)  # [0, 3, 2, 1]
 
     """
-    op_type = 'elementwise_mod'
-    axis = -1
-
     if in_dygraph_mode():
         return _C_ops.remainder(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_mod', **locals()))
 
 
 @inplace_apis_in_dygraph_only
@@ -856,9 +806,6 @@ def remainder_(x, y, name=None):
     Inplace version of ``remainder`` API, the output Tensor will be inplaced with input ``x``.
     Please refer to :ref:`api_tensor_remainder`.
     """
-    op_type = 'elementwise_mod_'
-    axis = -1
-
     out_shape = broadcast_shape(x.shape, y.shape)
     if out_shape != x.shape:
         raise ValueError(
@@ -866,8 +813,7 @@ def remainder_(x, y, name=None):
                 out_shape, x.shape
             )
         )
-
-    return _elementwise_op_in_dygraph(x, y, axis=axis, op_name=op_type)
+    return _C_ops.remainder_(x, y)
 
 
 mod = remainder  # noqa: F841
@@ -911,10 +857,6 @@ def multiply(x, y, name=None):
             print(res) # [[[2, 4, 6], [2, 4, 6]]]
 
     """
-    op_type = 'elementwise_mul'
-    act = None
-    axis = -1
-
     if in_dygraph_mode():
         return _C_ops.multiply(x, y)
     else:
@@ -924,7 +866,7 @@ def multiply(x, y, name=None):
                 % (x.dtype, y.dtype)
             )
 
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_mul', **locals()))
 
 
 @dygraph_only
@@ -958,7 +900,6 @@ def _add_with_axis(x, y, axis=-1, name=None):
         return _elementwise_op_with_axis_in_dygraph(x, y, axis, name, "add")
     else:
         op_type = 'elementwise_add'
-        act = None
         return _elementwise_op(LayerHelper(op_type, **locals()))
 
 
@@ -970,7 +911,6 @@ def _subtract_with_axis(x, y, axis=-1, name=None):
         )
     else:
         op_type = 'elementwise_sub'
-        act = None
         return _elementwise_op(LayerHelper(op_type, **locals()))
 
 
@@ -982,7 +922,6 @@ def _multiply_with_axis(x, y, axis=-1, name=None):
         )
     else:
         op_type = 'elementwise_mul'
-        act = None
         return _elementwise_op(LayerHelper(op_type, **locals()))
 
 
@@ -992,7 +931,6 @@ def _divide_with_axis(x, y, axis=-1, name=None):
         return _elementwise_op_with_axis_in_dygraph(x, y, axis, name, "divide")
     else:
         op_type = 'elementwise_div'
-        act = None
         return _elementwise_op(LayerHelper(op_type, **locals()))
 
 
@@ -1052,13 +990,10 @@ def maximum(x, y, name=None):
             # Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
             #        [5.  , 3.  , inf.])
     """
-    op_type = 'elementwise_max'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.maximum(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_max', **locals()))
 
 
 def minimum(x, y, name=None):
@@ -1117,13 +1052,10 @@ def minimum(x, y, name=None):
             # Tensor(shape=[3], dtype=float64, place=Place(cpu), stop_gradient=True,
             #        [ 1.  , -inf.,  5.  ])
     """
-    op_type = 'elementwise_min'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.minimum(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_min', **locals()))
 
 
 def fmax(x, y, name=None):
@@ -1184,13 +1116,10 @@ def fmax(x, y, name=None):
             # Tensor(shape=[3], dtype=float32, place=Place(cpu), stop_gradient=True,
             #        [5.  , 3.  , inf.])
     """
-    op_type = 'elementwise_fmax'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.fmax(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_fmax', **locals()))
 
 
 def fmin(x, y, name=None):
@@ -1251,13 +1180,10 @@ def fmin(x, y, name=None):
             # Tensor(shape=[3], dtype=float64, place=Place(cpu), stop_gradient=True,
             #        [ 1.  , -inf.,  5.  ])
     """
-    op_type = 'elementwise_fmin'
-    axis = -1
-    act = None
     if in_dygraph_mode():
         return _C_ops.fmin(x, y)
     else:
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_fmin', **locals()))
 
 
 def sum(x, axis=None, dtype=None, keepdim=False, name=None):
@@ -4888,9 +4814,6 @@ def frac(x, name=None):
             #        [[ 0.22000003, -0.02999997],
             #         [-0.54999995,  0.66000003]])
     """
-    op_type = 'elementwise_sub'
-    axis = -1
-    act = None
     if x.dtype not in [
         paddle.int32,
         paddle.int64,
@@ -4917,7 +4840,7 @@ def frac(x, name=None):
         helper.append_op(
             type="trunc", inputs=inputs, attrs=attrs, outputs={"Out": y}
         )
-        return _elementwise_op(LayerHelper(op_type, **locals()))
+        return _elementwise_op(LayerHelper('elementwise_sub', **locals()))
 
 
 def sgn(x, name=None):