diff --git a/paddle/phi/api/yaml/legacy_backward.yaml b/paddle/phi/api/yaml/legacy_backward.yaml index 234885a9d7ee5dc7265325e5582325433fed02f1..2f4eff98356044343bee115cf169a050be117417 100755 --- a/paddle/phi/api/yaml/legacy_backward.yaml +++ b/paddle/phi/api/yaml/legacy_backward.yaml @@ -2096,6 +2096,12 @@ optional : grad_grad_out_grad inplace : (grad_grad_x -> fwd_grad_out_grad) +- backward_op : sign_grad + forward : sign (Tensor x) -> Tensor(out) + args : (Tensor out_grad) + output : Tensor(x_grad) + invoke : scale(out_grad, 0.0, 0.0, true) + - backward_op : silu_grad forward : silu (Tensor x) -> Tensor(out) args : (Tensor x, Tensor out_grad) diff --git a/paddle/phi/api/yaml/legacy_ops.yaml b/paddle/phi/api/yaml/legacy_ops.yaml index ee251b8d9997e2e9d4779cba8a81ae8f1b3008cf..eddc9117f05188a1a834d5a6585c27f06cbda233 100755 --- a/paddle/phi/api/yaml/legacy_ops.yaml +++ b/paddle/phi/api/yaml/legacy_ops.yaml @@ -2377,6 +2377,7 @@ func : UnchangedInferMeta kernel : func : sign + backward : sign_grad - op : silu args : (Tensor x) diff --git a/python/paddle/fluid/tests/unittests/test_sign_op.py b/python/paddle/fluid/tests/unittests/test_sign_op.py index 444675a4bb5c22c701177f052751e5efb7753e38..3eda8b286c84021a84ffb9d6d6d434337f36ad42 100644 --- a/python/paddle/fluid/tests/unittests/test_sign_op.py +++ b/python/paddle/fluid/tests/unittests/test_sign_op.py @@ -19,7 +19,11 @@ import numpy as np from op_test import OpTest import paddle import paddle.fluid as fluid +import paddle.fluid.core as core from paddle.fluid import Program, program_guard +import gradient_checker +from decorator_helper import prog_scope +import paddle.fluid.layers as layers class TestSignOp(OpTest): @@ -91,6 +95,80 @@ class TestSignAPI(unittest.TestCase): paddle.sign(input4) +class TestSignDoubleGradCheck(unittest.TestCase): + + def sign_wrapper(self, x): + return paddle.sign(x[0]) + + @prog_scope() + def func(self, place): + # the shape of input variable should be clearly specified, not inlcude -1. + eps = 0.005 + dtype = np.float32 + + data = layers.data('data', [1, 4], False, dtype) + data.persistable = True + out = paddle.sign(data) + data_arr = np.random.uniform(-1, 1, data.shape).astype(dtype) + + gradient_checker.double_grad_check([data], + out, + x_init=[data_arr], + place=place, + eps=eps) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) + gradient_checker.double_grad_check_for_dygraph(self.sign_wrapper, + [data], + out, + x_init=[data_arr], + place=place) + + def test_grad(self): + paddle.enable_static() + places = [fluid.CPUPlace()] + if core.is_compiled_with_cuda(): + places.append(fluid.CUDAPlace(0)) + for p in places: + self.func(p) + + +class TestSignTripleGradCheck(unittest.TestCase): + + def sign_wrapper(self, x): + return paddle.sign(x[0]) + + @prog_scope() + def func(self, place): + # the shape of input variable should be clearly specified, not inlcude -1. + eps = 0.005 + dtype = np.float32 + + data = layers.data('data', [1, 4], False, dtype) + data.persistable = True + out = paddle.sign(data) + data_arr = np.random.uniform(-1, 1, data.shape).astype(dtype) + + gradient_checker.triple_grad_check([data], + out, + x_init=[data_arr], + place=place, + eps=eps) + fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True}) + gradient_checker.triple_grad_check_for_dygraph(self.sign_wrapper, + [data], + out, + x_init=[data_arr], + place=place) + + def test_grad(self): + paddle.enable_static() + places = [fluid.CPUPlace()] + if core.is_compiled_with_cuda(): + places.append(fluid.CUDAPlace(0)) + for p in places: + self.func(p) + + if __name__ == "__main__": paddle.enable_static() unittest.main()