add scatter_add_nd, label_smooth, huber_loss yaml (#41462) (#41611)

python/paddle/fluid/layers/loss.py

@@ -1610,6 +1610,10 @@ def huber_loss(input, label, delta):
         HuberLoss, = exe.run(feed={'input':input_data ,'label':label_data}, fetch_list=[loss.name])
         print(HuberLoss)  #[[1.5], [0.5], [0.5], [0. ]], dtype=float32
     """
+    if in_dygraph_mode():
+        out, residual = _C_ops.final_state_huber_loss(input, label, delta)
+        return out
+
     helper = LayerHelper('huber_loss', **locals())
     check_variable_and_dtype(input, 'input', ['float32', 'float64'],
                              'huber_loss')

python/paddle/fluid/layers/nn.py

@@ -7095,6 +7095,10 @@ def label_smooth(label,
             smooth_label = layers.label_smooth(
                 label=one_hot_label, epsilon=0.1, dtype="float32")
     """
+    if in_dygraph_mode():
+        return _C_ops.final_state_label_smooth(label, prior_dist,
+                                               float(epsilon))
+
     if epsilon > 1. or epsilon < 0.:
         raise ValueError("The value of epsilon must be between 0 and 1.")
 
@@ -8839,8 +8843,7 @@ def scatter_nd_add(ref, index, updates, name=None):
     """
 
     if in_dygraph_mode():
-        op = getattr(_C_ops, 'scatter_nd_add')
-        return op(ref, index, updates)
+        return _C_ops.final_state_scatter_nd_add(ref, index, updates)
     else:
         if _in_legacy_dygraph():
             op = getattr(_C_ops, 'scatter_nd_add')

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

@@ -18,6 +18,7 @@ import unittest
 import numpy as np
 from op_test import OpTest
 import paddle.fluid as fluid
+import paddle
 from paddle.fluid import compiler, Program, program_guard
 
 
@@ -32,6 +33,8 @@ def huber_loss_forward(val, delta):
 class TestHuberLossOp(OpTest):
     def setUp(self):
         self.op_type = 'huber_loss'
+        self.python_api = paddle.fluid.layers.huber_loss
+        self.python_out_sig = ["Out"]
         self.delta = 1.0
         self.init_input()
         shape = self.set_shape()
@@ -52,10 +55,10 @@ class TestHuberLossOp(OpTest):
         return (100, 1)
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_eager=True)
 
     def test_check_grad_normal(self):
-        self.check_grad(['X', 'Y'], 'Out')
+        self.check_grad(['X', 'Y'], 'Out', check_eager=True)
 
     def test_check_grad_ingore_x(self):
         self.check_grad(
@@ -103,4 +106,5 @@ class TestHuberLossOpError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -39,10 +39,10 @@ class TestLabelSmoothOp(OpTest):
         self.outputs = {'Out': smoothed_label}
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(["X"], "Out", check_eager=False)
+        self.check_grad(["X"], "Out", check_eager=True)
 
 
 class TestLabelSmoothOpWithPriorDist(TestLabelSmoothOp):

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

@@ -77,10 +77,10 @@ class TestScatterNdAddSimpleOp(OpTest):
         self.outputs = {'Out': expect_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(['X', 'Updates'], 'Out', check_eager=False)
+        self.check_grad(['X', 'Updates'], 'Out', check_eager=True)
 
 
 class TestScatterNdAddWithEmptyIndex(OpTest):
@@ -101,10 +101,10 @@ class TestScatterNdAddWithEmptyIndex(OpTest):
         self.outputs = {'Out': expect_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(['X', 'Updates'], 'Out', check_eager=False)
+        self.check_grad(['X', 'Updates'], 'Out', check_eager=True)
 
 
 class TestScatterNdAddWithHighRankSame(OpTest):
@@ -128,10 +128,10 @@ class TestScatterNdAddWithHighRankSame(OpTest):
         self.outputs = {'Out': expect_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(['X', 'Updates'], 'Out', check_eager=False)
+        self.check_grad(['X', 'Updates'], 'Out', check_eager=True)
 
 
 class TestScatterNdAddWithHighRankDiff(OpTest):
@@ -154,10 +154,10 @@ class TestScatterNdAddWithHighRankDiff(OpTest):
         self.outputs = {'Out': expect_np}
 
     def test_check_output(self):
-        self.check_output(check_eager=False)
+        self.check_output(check_eager=True)
 
     def test_check_grad(self):
-        self.check_grad(['X', 'Updates'], 'Out', check_eager=False)
+        self.check_grad(['X', 'Updates'], 'Out', check_eager=True)
 
 
 #Test Python API

python/paddle/nn/functional/common.py

@@ -1623,6 +1623,10 @@ def label_smooth(label, prior_dist=None, epsilon=0.1, name=None):
             #[[[0.03333334 0.93333334 0.03333334]
             #  [0.93333334 0.03333334 0.93333334]]]
     """
+    if in_dygraph_mode():
+        return _C_ops.final_state_label_smooth(label, prior_dist,
+                                               float(epsilon))
+
     if epsilon > 1. or epsilon < 0.:
         raise ValueError("The value of epsilon must be between 0 and 1.")
 

python/paddle/utils/code_gen/api.yaml

@@ -812,7 +812,7 @@
     func : HuberLossInferMeta
   kernel :
     func : huber_loss
-  # backward : huber_loss_grad
+  backward : huber_loss_grad
 
 - api : imag
   args : (Tensor x)
@@ -916,6 +916,19 @@
     func : kthvalue
   backward : kthvalue_grad
 
+# label_smooth
+- api : label_smooth
+  args : (Tensor label, Tensor prior_dist, float epsilon)
+  output : Tensor
+  infer_meta :
+    func : UnchangedInferMeta
+    param : [label]
+  kernel :
+    func : label_smooth
+    data_type : label
+  optional : prior_dist
+  backward : label_smooth_grad
+
 # leaky_relu
 - api : leaky_relu
   args : (Tensor x, float alpha)

python/paddle/utils/code_gen/backward.yaml

@@ -100,7 +100,7 @@
     func : asinh_grad
 
 - backward_api : atan2_grad
-  forward : cross (Tensor x, Tensor y) -> Tensor(out)
+  forward : atan2 (Tensor x, Tensor y) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor out_grad)
   output : Tensor(x_grad), Tensor(y_grad)
   infer_meta :
@@ -193,7 +193,7 @@
     func : cholesky_grad
 
 - backward_api : cholesky_solve_grad
-  forward : cholesky (Tensor x, Tensor y, bool upper) -> Tensor(out)
+  forward : cholesky_solve (Tensor x, Tensor y, bool upper) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper)
   output : Tensor(x_grad), Tensor(y_grad)
   infer_meta :
@@ -404,7 +404,7 @@
     data_type : out_grad
 
 - backward_api : erfinv_grad
-  forward : erf (Tensor x) -> Tensor(out)
+  forward : erfinv (Tensor x) -> Tensor(out)
   args : (Tensor out, Tensor out_grad)
   output : Tensor(x_grad)
   infer_meta :
@@ -537,6 +537,16 @@
   kernel :
     func : hard_sigmoid_grad
 
+- backward_api : huber_loss_grad
+  forward : huber_loss (Tensor input, Tensor label, float delta) -> Tensor(out), Tensor(residual)
+  args : (Tensor residual, Tensor out_grad, float delta)
+  output : Tensor(input_grad), Tensor(label_grad)
+  infer_meta :
+    func : GeneralBinaryGradInferMeta
+    param : [residual, residual]
+  kernel :
+    func : huber_loss_grad
+
 - backward_api : imag_grad
   forward : imag (Tensor x) -> Tensor(out)
   args : (Tensor out_grad)
@@ -608,7 +618,7 @@
     func : leaky_relu_grad
 
 - backward_api : lerp_grad
-  forward : transpose (Tensor x, Tensor y, Tensor weight) -> Tensor(out)
+  forward : lerp (Tensor x, Tensor y, Tensor weight) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor weight, Tensor out, Tensor out_grad)
   output : Tensor(x_grad), Tensor(y_grad)
   infer_meta :
@@ -867,7 +877,7 @@
     func : mode_grad
 
 - backward_api : modulo_grad
-  forward : add (Tensor x, Tensor y) -> Tensor(out)
+  forward : modulo (Tensor x, Tensor y) -> Tensor(out)
   args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1)
   output : Tensor(x_grad), Tensor(y_grad)
   infer_meta :
@@ -1120,14 +1130,14 @@
   no_need_buffer : updates
 
 - backward_api : scatter_nd_add_grad
-  forward : scatter (Tensor x, Tensor index, Tensor updates) -> Tensor(out)
+  forward : scatter_nd_add (Tensor x, Tensor index, Tensor updates) -> Tensor(out)
   args : (Tensor index, Tensor updates, Tensor out_grad)
   output : Tensor(x_grad), Tensor(updates_grad)
   infer_meta :
     func : ScatterNdAddGradInferMeta
     param : [index, updates, out_grad]
   kernel :
-    func : scatter_nd_grad
+    func : scatter_nd_add_grad
   no_need_buffer : updates
 
 - backward_api : segment_pool_grad

tools/infrt/skipped_phi_api.json

 {
-"phi_apis":["conj", "dropout", "expand_as", "flatten", "nll_loss", "psroi_pool", "roi_align", "roi_pool"],
+"phi_apis":["conj", "dropout", "expand_as", "flatten", "nll_loss", "psroi_pool", "roi_align", "roi_pool", "label_smooth"],
 "phi_kernels":["equal_all"]
 }