diff --git a/tensorflow/core/kernels/cwise_op_ceil.cc b/tensorflow/core/kernels/cwise_op_ceil.cc index c6e38a55efd..4b1847d758c 100644 --- a/tensorflow/core/kernels/cwise_op_ceil.cc +++ b/tensorflow/core/kernels/cwise_op_ceil.cc @@ -16,8 +16,7 @@ limitations under the License. #include "tensorflow/core/kernels/cwise_ops_common.h" namespace tensorflow { -REGISTER4(UnaryOp, CPU, "Ceil", functor::ceil, float, Eigen::half, double, - int32); +REGISTER3(UnaryOp, CPU, "Ceil", functor::ceil, float, Eigen::half, double); #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM REGISTER3(UnaryOp, GPU, "Ceil", functor::ceil, float, Eigen::half, double); diff --git a/tensorflow/core/kernels/cwise_op_floor.cc b/tensorflow/core/kernels/cwise_op_floor.cc index ba0340372f4..25210a0fa51 100644 --- a/tensorflow/core/kernels/cwise_op_floor.cc +++ b/tensorflow/core/kernels/cwise_op_floor.cc @@ -16,8 +16,7 @@ limitations under the License. #include "tensorflow/core/kernels/cwise_ops_common.h" namespace tensorflow { -REGISTER4(UnaryOp, CPU, "Floor", functor::floor, float, Eigen::half, double, - int32); +REGISTER3(UnaryOp, CPU, "Floor", functor::floor, float, Eigen::half, double); #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM REGISTER3(UnaryOp, GPU, "Floor", functor::floor, float, Eigen::half, double); diff --git a/tensorflow/core/kernels/cwise_op_rint.cc b/tensorflow/core/kernels/cwise_op_rint.cc index c6071d02295..f9fe8321947 100644 --- a/tensorflow/core/kernels/cwise_op_rint.cc +++ b/tensorflow/core/kernels/cwise_op_rint.cc @@ -16,7 +16,7 @@ limitations under the License. #include "tensorflow/core/kernels/cwise_ops_common.h" namespace tensorflow { -REGISTER3(UnaryOp, CPU, "Rint", functor::rint, float, double, int32); +REGISTER2(UnaryOp, CPU, "Rint", functor::rint, float, double); #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM REGISTER2(UnaryOp, GPU, "Rint", functor::rint, float, double); #endif diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc index 691f34ff307..ccdcf0b76e6 100644 --- a/tensorflow/core/ops/math_ops.cc +++ b/tensorflow/core/ops/math_ops.cc @@ -349,19 +349,19 @@ REGISTER_OP("Sign") REGISTER_OP("Floor") .Input("x: T") .Output("y: T") - .Attr("T: {bfloat16, half, float, double, int32}") + .Attr("T: {bfloat16, half, float, double}") .SetShapeFn(shape_inference::UnchangedShape); REGISTER_OP("Ceil") .Input("x: T") .Output("y: T") - .Attr("T: {bfloat16, half, float, double, int32}") + .Attr("T: {bfloat16, half, float, double}") .SetShapeFn(shape_inference::UnchangedShape); REGISTER_OP("Rint") .Input("x: T") .Output("y: T") - .Attr("T: {bfloat16, half, float, double, int32}") + .Attr("T: {bfloat16, half, float, double}") .SetShapeFn(shape_inference::UnchangedShape); // Declares cwise binary operations signature: 't, 't -> 't. diff --git a/tensorflow/python/ops/math_ops_test.py b/tensorflow/python/ops/math_ops_test.py index c1591791cbd..f49ba3dd2a3 100644 --- a/tensorflow/python/ops/math_ops_test.py +++ b/tensorflow/python/ops/math_ops_test.py @@ -179,48 +179,6 @@ class RoundTest(test_util.TensorFlowTestCase): self.assertAllClose(y_tf_np, y_np, atol=1e-2) -@test_util.run_all_in_graph_and_eager_modes -class FloorTest(test_util.TensorFlowTestCase): - - def testFloor(self): - x = np.arange(-5.0, 5.0, .25) - for dtype in [np.float32, np.double, np.int32]: - x_np = np.array(x, dtype=dtype) - x_tf = constant_op.constant(x_np, shape=x_np.shape) - y_tf = math_ops.floor(x_tf) - y_tf_np = self.evaluate(y_tf) - y_np = np.floor(x_np) - self.assertAllClose(y_tf_np, y_np, atol=1e-2) - - -@test_util.run_all_in_graph_and_eager_modes -class CeilTest(test_util.TensorFlowTestCase): - - def testCeil(self): - x = np.arange(-5.0, 5.0, .25) - for dtype in [np.float32, np.double, np.int32]: - x_np = np.array(x, dtype=dtype) - x_tf = constant_op.constant(x_np, shape=x_np.shape) - y_tf = math_ops.ceil(x_tf) - y_tf_np = self.evaluate(y_tf) - y_np = np.ceil(x_np) - self.assertAllClose(y_tf_np, y_np, atol=1e-2) - - -@test_util.run_all_in_graph_and_eager_modes -class RintTest(test_util.TensorFlowTestCase): - - def testRint(self): - x = np.arange(-5.0, 5.0, .25) - for dtype in [np.float32, np.double, np.int32]: - x_np = np.array(x, dtype=dtype) - x_tf = constant_op.constant(x_np, shape=x_np.shape) - y_tf = math_ops.rint(x_tf) - y_tf_np = self.evaluate(y_tf) - y_np = np.rint(x_np) - self.assertAllClose(y_tf_np, y_np, atol=1e-2) - - @test_util.run_all_in_graph_and_eager_modes class ModTest(test_util.TensorFlowTestCase):