From bbe62e94dd8f661b011b141e2c20997a3529db74 Mon Sep 17 00:00:00 2001
From: Srinivas Vasudevan <srvasude@google.com>
Date: Wed, 2 Oct 2019 19:14:14 -0700
Subject: [PATCH] Add tf.math.ndtri and tf.math.erfinv.
PiperOrigin-RevId: 272571083
---
tensorflow/cc/gradients/math_grad.cc | 34 ++++++++
tensorflow/cc/gradients/math_grad_test.cc | 24 +++++-
.../api_def/base_api/api_def_Erfinv.pbtxt | 3 +
.../core/api_def/base_api/api_def_Ndtri.pbtxt | 3 +
tensorflow/core/kernels/cwise_op_ndtri.cc | 32 ++++++++
.../core/kernels/cwise_op_ndtri_double.cu.cc | 30 +++++++
.../core/kernels/cwise_op_ndtri_float.cu.cc | 30 +++++++
tensorflow/core/kernels/cwise_ops.h | 33 ++++++++
tensorflow/core/kernels/cwise_ops_gradients.h | 79 +++++++++++++++++++
tensorflow/core/ops/math_ops.cc | 3 +-
tensorflow/python/ops/math_grad.py | 18 +++++
.../python/ops/parallel_for/math_test.py | 2 +
tensorflow/python/ops/parallel_for/pfor.py | 2 +
.../python/ops/ragged/ragged_dispatch.py | 2 +
.../python/ops/ragged/ragged_dispatch_test.py | 2 +
.../tools/api/golden/v1/tensorflow.pbtxt | 8 ++
.../api/golden/v1/tensorflow.raw_ops.pbtxt | 8 ++
.../tools/api/golden/v2/tensorflow.pbtxt | 8 ++
.../api/golden/v2/tensorflow.raw_ops.pbtxt | 8 ++
19 files changed, 327 insertions(+), 2 deletions(-)
create mode 100644 tensorflow/core/api_def/base_api/api_def_Erfinv.pbtxt
create mode 100644 tensorflow/core/api_def/base_api/api_def_Ndtri.pbtxt
create mode 100644 tensorflow/core/kernels/cwise_op_ndtri.cc
create mode 100644 tensorflow/core/kernels/cwise_op_ndtri_double.cu.cc
create mode 100644 tensorflow/core/kernels/cwise_op_ndtri_float.cu.cc
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc
index 1329b568ab8..b3c1e6a913a 100644
--- a/tensorflow/cc/gradients/math_grad.cc
+++ b/tensorflow/cc/gradients/math_grad.cc
@@ -767,6 +767,40 @@ Status ErfGrad(const Scope& scope, const Operation& op,
}
REGISTER_GRADIENT_OP("Erf", ErfGrad);
+Status ErfinvGrad(const Scope& scope, const Operation& op,
+ const std::vector<Output>& grad_inputs,
+ std::vector<Output>* grad_outputs) {
+ auto grad = grad_inputs[0];
+ auto root_pi_over_two =
+ Cast(scope, Const(scope, std::sqrt(M_PI) / 2), grad.type());
+ Scope grad_scope = scope.WithControlDependencies(grad);
+ auto x = ConjugateHelper(grad_scope, op.input(0));
+ // grad * sqrt(pi) / 2 * exp(erfinv(x) ** 2)
+ auto dx = Mul(grad_scope, Mul(grad_scope, grad, root_pi_over_two),
+ Exp(grad_scope, Square(grad_scope, op.output(0))));
+ grad_outputs->push_back(dx);
+ return grad_scope.status();
+}
+REGISTER_GRADIENT_OP("Erfinv", ErfinvGrad);
+
+Status NdtriGrad(const Scope& scope, const Operation& op,
+ const std::vector<Output>& grad_inputs,
+ std::vector<Output>* grad_outputs) {
+ auto grad = grad_inputs[0];
+ auto root_two_pi =
+ Cast(scope, Const(scope, std::sqrt(2 * M_PI)), grad.type());
+ auto two = Cast(scope, Const(scope, 2), grad.type());
+ Scope grad_scope = scope.WithControlDependencies(grad);
+ auto x = ConjugateHelper(grad_scope, op.input(0));
+ // grad * sqrt(2 * pi) * exp(ndtri(x) ** 2 / 2)
+ auto dx = Mul(
+ grad_scope, Mul(grad_scope, grad, root_two_pi),
+ Exp(grad_scope, Div(grad_scope, Square(grad_scope, op.output(0)), two)));
+ grad_outputs->push_back(dx);
+ return grad_scope.status();
+}
+REGISTER_GRADIENT_OP("Ndtri", NdtriGrad);
+
Status LgammaGrad(const Scope& scope, const Operation& op,
const std::vector<Output>& grad_inputs,
std::vector<Output>* grad_outputs) {
diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc
index c16938322c3..0ecd5095650 100644
--- a/tensorflow/cc/gradients/math_grad_test.cc
+++ b/tensorflow/cc/gradients/math_grad_test.cc
@@ -89,7 +89,9 @@ class CWiseUnaryGradTest : public ::testing::Test {
COMPLEX,
ANGLE,
LGAMMA,
- ERF
+ ERF,
+ ERFINV,
+ NDTRI
};
template <typename X_T, typename Y_T>
@@ -200,6 +202,12 @@ class CWiseUnaryGradTest : public ::testing::Test {
case ERF:
y = Erf(scope_, x);
break;
+ case ERFINV:
+ y = Erfinv(scope_, x);
+ break;
+ case NDTRI:
+ y = Ndtri(scope_, x);
+ break;
}
float max_error;
@@ -567,6 +575,20 @@ TEST_F(CWiseUnaryGradTest, Erf_Complex) {
}
}
+TEST_F(CWiseUnaryGradTest, Ndtri) {
+ auto x_fn = [this](const int i) {
+ return RV({0.1, 0.2, 0.3, 0.5, 0.7, 0.9});
+ };
+ TestCWiseGrad<float, float>(NDTRI, x_fn);
+}
+
+TEST_F(CWiseUnaryGradTest, Erfinv) {
+ auto x_fn = [this](const int i) {
+ return RV({-0.9, -0.3, -0.1, 0.2, 0.6, 0.8});
+ };
+ TestCWiseGrad<float, float>(ERFINV, x_fn);
+}
+
class MathGradTest : public ::testing::Test {
protected:
MathGradTest() : root_(Scope::NewRootScope().WithDevice("/cpu:0")) {}
diff --git a/tensorflow/core/api_def/base_api/api_def_Erfinv.pbtxt b/tensorflow/core/api_def/base_api/api_def_Erfinv.pbtxt
new file mode 100644
index 00000000000..281dbc19cf4
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_Erfinv.pbtxt
@@ -0,0 +1,3 @@
+op {
+ graph_op_name: "Erfinv"
+}
diff --git a/tensorflow/core/api_def/base_api/api_def_Ndtri.pbtxt b/tensorflow/core/api_def/base_api/api_def_Ndtri.pbtxt
new file mode 100644
index 00000000000..bcd68bb19f1
--- /dev/null
+++ b/tensorflow/core/api_def/base_api/api_def_Ndtri.pbtxt
@@ -0,0 +1,3 @@
+op {
+ graph_op_name: "Ndtri"
+}
diff --git a/tensorflow/core/kernels/cwise_op_ndtri.cc b/tensorflow/core/kernels/cwise_op_ndtri.cc
new file mode 100644
index 00000000000..1ebbfe373ee
--- /dev/null
+++ b/tensorflow/core/kernels/cwise_op_ndtri.cc
@@ -0,0 +1,32 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/core/kernels/cwise_ops_common.h"
+#include "tensorflow/core/kernels/cwise_ops_gradients.h"
+
+namespace tensorflow {
+REGISTER2(UnaryOp, CPU, "Ndtri", functor::ndtri, float, double);
+REGISTER2(UnaryOp, CPU, "Erfinv", functor::erfinv, float, double);
+REGISTER2(SimpleBinaryOp, CPU, "NdtriGrad", functor::ndtri_grad, float, double);
+REGISTER2(SimpleBinaryOp, CPU, "ErfinvGrad", functor::erfinv_grad, float,
+ double);
+#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
+REGISTER2(UnaryOp, GPU, "Ndtri", functor::ndtri, float, double);
+REGISTER2(UnaryOp, GPU, "Erfinv", functor::erfinv, float, double);
+REGISTER2(SimpleBinaryOp, GPU, "NdtriGrad", functor::ndtri_grad, float, double);
+REGISTER2(SimpleBinaryOp, GPU, "ErfinvGrad", functor::erfinv_grad, float,
+ double);
+#endif
+} // namespace tensorflow
diff --git a/tensorflow/core/kernels/cwise_op_ndtri_double.cu.cc b/tensorflow/core/kernels/cwise_op_ndtri_double.cu.cc
new file mode 100644
index 00000000000..f56323362bb
--- /dev/null
+++ b/tensorflow/core/kernels/cwise_op_ndtri_double.cu.cc
@@ -0,0 +1,30 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
+
+#include "tensorflow/core/kernels/cwise_ops_gpu_common.cu.h"
+#include "tensorflow/core/kernels/cwise_ops_gpu_gradients.cu.h"
+
+namespace tensorflow {
+namespace functor {
+DEFINE_UNARY1(ndtri, double);
+DEFINE_UNARY1(erfinv, double);
+DEFINE_SIMPLE_BINARY1(ndtri_grad, double);
+DEFINE_SIMPLE_BINARY1(erfinv_grad, double);
+} // namespace functor
+} // namespace tensorflow
+
+#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
diff --git a/tensorflow/core/kernels/cwise_op_ndtri_float.cu.cc b/tensorflow/core/kernels/cwise_op_ndtri_float.cu.cc
new file mode 100644
index 00000000000..2557241d892
--- /dev/null
+++ b/tensorflow/core/kernels/cwise_op_ndtri_float.cu.cc
@@ -0,0 +1,30 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
+
+#include "tensorflow/core/kernels/cwise_ops_gpu_common.cu.h"
+#include "tensorflow/core/kernels/cwise_ops_gpu_gradients.cu.h"
+
+namespace tensorflow {
+namespace functor {
+DEFINE_UNARY1(ndtri, float);
+DEFINE_UNARY1(erfinv, float);
+DEFINE_SIMPLE_BINARY1(ndtri_grad, float);
+DEFINE_SIMPLE_BINARY1(erfinv_grad, float);
+} // namespace functor
+} // namespace tensorflow
+
+#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
diff --git a/tensorflow/core/kernels/cwise_ops.h b/tensorflow/core/kernels/cwise_ops.h
index c210a1edd1e..f2f3bb89f1e 100644
--- a/tensorflow/core/kernels/cwise_ops.h
+++ b/tensorflow/core/kernels/cwise_ops.h
@@ -728,6 +728,33 @@ struct functor_traits<xdivy_op<Scalar>> {
};
};
+template <typename T>
+struct scalar_erfinv_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_erfinv_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T operator()(const T& x) const {
+ T y = numext::ndtri((x + static_cast<T>(1.)) / static_cast<T>(2.));
+ return y / static_cast<T>(numext::sqrt(2.));
+ }
+ template <typename Packet>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet
+ packetOp(const Packet& x) const {
+ Packet y = pndtri<Packet>(pmadd(pset1<Packet>(0.5), x, pset1<Packet>(0.5)));
+ return pdiv(y, psqrt(pset1<Packet>(2.)));
+ }
+};
+
+template <typename T>
+struct functor_traits<scalar_erfinv_op<T>> {
+ enum {
+ Cost = functor_traits<scalar_ndtri_op<T>>::Cost + NumTraits<T>::AddCost,
+#if TENSORFLOW_USE_ROCM
+ PacketAccess = false,
+#else
+ PacketAccess = packet_traits<T>::HasNdtri,
+#endif
+ };
+};
+
} // end namespace internal
} // end namespace Eigen
@@ -873,6 +900,12 @@ struct erf : base<T, Eigen::internal::scalar_erf_op<T>> {};
template <typename T>
struct erfc : base<T, Eigen::internal::scalar_erfc_op<T>> {};
+template <typename T>
+struct ndtri : base<T, Eigen::internal::scalar_ndtri_op<T>> {};
+
+template <typename T>
+struct erfinv : base<T, Eigen::internal::scalar_erfinv_op<T>> {};
+
template <typename T>
struct sigmoid : base<T, Eigen::internal::scalar_logistic_op<T>> {};
diff --git a/tensorflow/core/kernels/cwise_ops_gradients.h b/tensorflow/core/kernels/cwise_ops_gradients.h
index 1c5d169f5db..ad413b5f1ce 100644
--- a/tensorflow/core/kernels/cwise_ops_gradients.h
+++ b/tensorflow/core/kernels/cwise_ops_gradients.h
@@ -174,6 +174,79 @@ struct functor_traits<scalar_rsqrt_gradient_op<T>> {
};
};
+#define SQRT_PI 1.772453850905516027298167483341
+#define SQRT_2PI 2.506628274631000502415765284811
+
+// Gradient for the erfinv function
+template <typename T>
+struct scalar_erfinv_gradient_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_erfinv_gradient_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T
+ operator()(const T& output, const T& output_gradient) const {
+ // grad * sqrt(pi) / 2 * exp(erfinv(x) ** 2)
+ if (output_gradient == T(0)) {
+ return T(0);
+ } else {
+ return static_cast<T>(0.5 * SQRT_PI) * numext::exp(output * output) *
+ output_gradient;
+ }
+ }
+ template <typename Packet>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet
+ packetOp(const Packet& output, const Packet& output_gradient) const {
+ const Packet const_half_sqrt_pi =
+ pset1<Packet>(static_cast<T>(0.5 * SQRT_PI));
+ return pmul(pmul(const_half_sqrt_pi, pexp(pmul(output, output))),
+ output_gradient);
+ }
+};
+template <typename T>
+struct functor_traits<scalar_erfinv_gradient_op<T>> {
+ enum {
+#if TENSORFLOW_USE_ROCM
+ PacketAccess = false,
+#else
+ PacketAccess = packet_traits<T>::HasNdtri,
+#endif
+ Cost = 10 * NumTraits<T>::MulCost + scalar_div_cost<T, PacketAccess>::value,
+ };
+};
+
+// Gradient for the ndtri function
+template <typename T>
+struct scalar_ndtri_gradient_op {
+ EIGEN_EMPTY_STRUCT_CTOR(scalar_ndtri_gradient_op)
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const T
+ // grad * sqrt(2 * pi) * exp(ndtri(x) ** 2 / 2)
+ operator()(const T& output, const T& output_gradient) const {
+ if (output_gradient == T(0)) {
+ return T(0);
+ } else {
+ return static_cast<T>(SQRT_2PI) * numext::exp(output * output / 2.) *
+ output_gradient;
+ }
+ }
+ template <typename Packet>
+ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Packet
+ packetOp(const Packet& output, const Packet& output_gradient) const {
+ const Packet const_sqrt_two_pi = pset1<Packet>(static_cast<T>(SQRT_2PI));
+ return pmul(pmul(const_sqrt_two_pi,
+ pexp(pdiv(pmul(output, output), pset1<Packet>(2.)))),
+ output_gradient);
+ }
+};
+template <typename T>
+struct functor_traits<scalar_ndtri_gradient_op<T>> {
+ enum {
+#if TENSORFLOW_USE_ROCM
+ PacketAccess = false,
+#else
+ PacketAccess = packet_traits<T>::HasNdtri,
+#endif
+ Cost = 10 * NumTraits<T>::MulCost + scalar_div_cost<T, PacketAccess>::value,
+ };
+};
+
} // end namespace internal
} // end namespace Eigen
@@ -234,6 +307,12 @@ struct rsqrt_grad : base<T, Eigen::internal::scalar_rsqrt_gradient_op<T>> {};
template <typename T>
struct igamma_grad_a : base<T, Eigen::internal::scalar_igamma_der_a_op<T>> {};
+template <typename T>
+struct erfinv_grad : base<T, Eigen::internal::scalar_erfinv_gradient_op<T>> {};
+
+template <typename T>
+struct ndtri_grad : base<T, Eigen::internal::scalar_ndtri_gradient_op<T>> {};
+
} // end namespace functor
} // end namespace tensorflow
diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc
index 660fc9db08c..7d6aedbcd1f 100644
--- a/tensorflow/core/ops/math_ops.cc
+++ b/tensorflow/core/ops/math_ops.cc
@@ -281,7 +281,8 @@ REGISTER_OP("Lgamma").UNARY_REAL();
REGISTER_OP("Digamma").UNARY_REAL();
REGISTER_OP("Erf").UNARY_REAL();
-
+REGISTER_OP("Erfinv").UNARY_REAL();
+REGISTER_OP("Ndtri").UNARY_REAL();
REGISTER_OP("Erfc").UNARY_REAL();
REGISTER_OP("Sigmoid").UNARY_COMPLEX();
diff --git a/tensorflow/python/ops/math_grad.py b/tensorflow/python/ops/math_grad.py
index 18f1ba11950..7bc6316cd5a 100644
--- a/tensorflow/python/ops/math_grad.py
+++ b/tensorflow/python/ops/math_grad.py
@@ -804,6 +804,24 @@ def _ErfcGrad(op, grad):
return grad * minus_two_over_root_pi * math_ops.exp(-math_ops.square(x))
+@ops.RegisterGradient("Erfinv")
+def _ErfinvGrad(op, grad):
+ """Returns grad * sqrt(pi) / 2 * exp(erfinv(x)**2)."""
+ root_pi_over_two = constant_op.constant(np.sqrt(np.pi) / 2, dtype=grad.dtype)
+ with ops.control_dependencies([grad]):
+ return grad * root_pi_over_two * math_ops.exp(
+ math_ops.square(op.outputs[0]))
+
+
+@ops.RegisterGradient("Ndtri")
+def _NdtriGrad(op, grad):
+ """Returns grad * sqrt(2 * pi) * exp(ndtri(x)**2 / 2)."""
+ root_two_pi = constant_op.constant(np.sqrt(2 * np.pi), dtype=grad.dtype)
+ with ops.control_dependencies([grad]):
+ return grad * root_two_pi * math_ops.exp(
+ math_ops.square(op.outputs[0]) / 2.)
+
+
@ops.RegisterGradient("Lgamma")
def _LgammaGrad(op, grad):
"""Returns grad * digamma(x)."""
diff --git a/tensorflow/python/ops/parallel_for/math_test.py b/tensorflow/python/ops/parallel_for/math_test.py
index f6811f11fe8..5927e6743c3 100644
--- a/tensorflow/python/ops/parallel_for/math_test.py
+++ b/tensorflow/python/ops/parallel_for/math_test.py
@@ -99,6 +99,7 @@ class MathTest(PForTestCase, parameterized.TestCase):
math_ops.digamma,
math_ops.erf,
math_ops.erfc,
+ math_ops.erfinv,
math_ops.exp,
math_ops.expm1,
math_ops.inv,
@@ -107,6 +108,7 @@ class MathTest(PForTestCase, parameterized.TestCase):
math_ops.lgamma,
math_ops.log,
math_ops.log1p,
+ math_ops.ndtri,
]
self._test_unary_cwise_ops(real_ops, False)
diff --git a/tensorflow/python/ops/parallel_for/pfor.py b/tensorflow/python/ops/parallel_for/pfor.py
index c54fc58bfa6..6fc95dd8b15 100644
--- a/tensorflow/python/ops/parallel_for/pfor.py
+++ b/tensorflow/python/ops/parallel_for/pfor.py
@@ -2434,6 +2434,7 @@ def _convert_cast(pfor_input):
@RegisterPForWithArgs("Elu", nn_ops.elu)
@RegisterPForWithArgs("Erf", math_ops.erf)
@RegisterPForWithArgs("Erfc", math_ops.erfc)
+@RegisterPForWithArgs("Erfinv", math_ops.erfinv)
@RegisterPForWithArgs("Exp", math_ops.exp)
@RegisterPForWithArgs("Expm1", math_ops.expm1)
@RegisterPForWithArgs("Floor", math_ops.floor)
@@ -2465,6 +2466,7 @@ def _convert_cast(pfor_input):
@RegisterPForWithArgs("Mod", math_ops.mod)
@RegisterPForWithArgs("Mul", math_ops.multiply)
@RegisterPForWithArgs("MulNoNan", math_ops.mul_no_nan)
+@RegisterPForWithArgs("Ndtri", math_ops.ndtri)
@RegisterPForWithArgs("Neg", math_ops.negative)
@RegisterPForWithArgs("Polygamma", math_ops.polygamma)
@RegisterPForWithArgs("Pow", math_ops.pow)
diff --git a/tensorflow/python/ops/ragged/ragged_dispatch.py b/tensorflow/python/ops/ragged/ragged_dispatch.py
index 8a32e407fd5..515100df6c8 100644
--- a/tensorflow/python/ops/ragged/ragged_dispatch.py
+++ b/tensorflow/python/ops/ragged/ragged_dispatch.py
@@ -303,6 +303,7 @@ _UNARY_ELEMENTWISE_OPS = [
math_ops.digamma,
math_ops.erf,
math_ops.erfc,
+ math_ops.erfinv,
math_ops.exp,
math_ops.expm1,
math_ops.floor,
@@ -315,6 +316,7 @@ _UNARY_ELEMENTWISE_OPS = [
math_ops.log1p,
math_ops.log_sigmoid,
math_ops.logical_not,
+ math_ops.ndtri,
math_ops.negative,
math_ops.real,
math_ops.reciprocal,
diff --git a/tensorflow/python/ops/ragged/ragged_dispatch_test.py b/tensorflow/python/ops/ragged/ragged_dispatch_test.py
index eafd2cde32d..b7e15a40889 100644
--- a/tensorflow/python/ops/ragged/ragged_dispatch_test.py
+++ b/tensorflow/python/ops/ragged/ragged_dispatch_test.py
@@ -58,6 +58,7 @@ UNARY_FLOAT_OPS = [
math_ops.digamma,
math_ops.erf,
math_ops.erfc,
+ math_ops.erfinv,
math_ops.exp,
math_ops.expm1,
math_ops.floor,
@@ -69,6 +70,7 @@ UNARY_FLOAT_OPS = [
math_ops.log,
math_ops.log1p,
math_ops.log_sigmoid,
+ math_ops.ndtri,
math_ops.negative,
math_ops.real,
math_ops.reciprocal,
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.pbtxt
index f7261a7834e..0d5ccb737f3 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.pbtxt
@@ -1236,6 +1236,10 @@ tf_module {
name: "erfc"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "erfinv"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "executing_eagerly"
argspec: "args=[], varargs=None, keywords=None, defaults=None"
@@ -1712,6 +1716,10 @@ tf_module {
name: "multiply"
argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "ndtri"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "negative"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt b/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
index 9d5cb659208..c8f41d8b533 100644
--- a/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
+++ b/tensorflow/tools/api/golden/v1/tensorflow.raw_ops.pbtxt
@@ -1184,6 +1184,10 @@ tf_module {
name: "Erfc"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "Erfinv"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "EuclideanNorm"
argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2348,6 +2352,10 @@ tf_module {
name: "NcclReduce"
argspec: "args=[\'input\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "Ndtri"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "Neg"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.pbtxt
index 0e40a9e8c59..bb967821a5b 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.pbtxt
@@ -612,6 +612,10 @@ tf_module {
name: "equal"
argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "erfinv"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "executing_eagerly"
argspec: "args=[], varargs=None, keywords=None, defaults=None"
@@ -796,6 +800,10 @@ tf_module {
name: "multiply"
argspec: "args=[\'x\', \'y\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "ndtri"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "negative"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
diff --git a/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt b/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
index 9d5cb659208..c8f41d8b533 100644
--- a/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
+++ b/tensorflow/tools/api/golden/v2/tensorflow.raw_ops.pbtxt
@@ -1184,6 +1184,10 @@ tf_module {
name: "Erfc"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "Erfinv"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "EuclideanNorm"
argspec: "args=[\'input\', \'axis\', \'keep_dims\', \'name\'], varargs=None, keywords=None, defaults=[\'False\', \'None\'], "
@@ -2348,6 +2352,10 @@ tf_module {
name: "NcclReduce"
argspec: "args=[\'input\', \'reduction\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
+ member_method {
+ name: "Ndtri"
+ argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
+ }
member_method {
name: "Neg"
argspec: "args=[\'x\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "