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PiperOrigin-RevId: 306921449
Change-Id: I4e2c6f31d38dcb821ace207c12a17232813e9fa5
This commit is contained in:
A. Unique TensorFlower 2020-04-16 14:27:08 -07:00 committed by TensorFlower Gardener
parent 1e5d6adc00
commit 339eab07e8
7 changed files with 13 additions and 15 deletions
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2
tensorflow/core/kernels/cwise_op_gpu_maximum.cu.cc
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@ -19,7 +19,7 @@ limitations under the License.
namespace tensorflow { namespace tensorflow {
namespace functor { namespace functor {
DEFINE_BINARY5(maximum, Eigen::half, float, double, int16, int64); DEFINE_BINARY4(maximum, Eigen::half, float, double, int64);
} // namespace functor } // namespace functor
} // namespace tensorflow } // namespace tensorflow

2
tensorflow/core/kernels/cwise_op_gpu_minimum.cu.cc
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@ -19,7 +19,7 @@ limitations under the License.
namespace tensorflow { namespace tensorflow {
namespace functor { namespace functor {
DEFINE_BINARY5(minimum, Eigen::half, float, double, int16, int64); DEFINE_BINARY4(minimum, Eigen::half, float, double, int64);
} // namespace functor } // namespace functor
} // namespace tensorflow } // namespace tensorflow

8
tensorflow/core/kernels/cwise_op_maximum.cc
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@ -16,11 +16,11 @@ limitations under the License.
#include "tensorflow/core/kernels/cwise_ops_common.h" #include "tensorflow/core/kernels/cwise_ops_common.h"
namespace tensorflow { namespace tensorflow {
REGISTER7(BinaryOp, CPU, "Maximum", functor::maximum, float, Eigen::half, REGISTER6(BinaryOp, CPU, "Maximum", functor::maximum, float, Eigen::half,
bfloat16, double, int16, int32, int64); bfloat16, double, int32, int64);
#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
REGISTER5(BinaryOp, GPU, "Maximum", functor::maximum, float, Eigen::half, REGISTER4(BinaryOp, GPU, "Maximum", functor::maximum, float, Eigen::half,
double, int16, int64); double, int64);
// A special GPU kernel for int32. // A special GPU kernel for int32.
// TODO(b/25387198): Also enable int32 in device memory. This kernel // TODO(b/25387198): Also enable int32 in device memory. This kernel

8
tensorflow/core/kernels/cwise_op_minimum.cc
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@ -16,11 +16,11 @@ limitations under the License.
#include "tensorflow/core/kernels/cwise_ops_common.h" #include "tensorflow/core/kernels/cwise_ops_common.h"
namespace tensorflow { namespace tensorflow {
REGISTER7(BinaryOp, CPU, "Minimum", functor::minimum, float, Eigen::half, REGISTER6(BinaryOp, CPU, "Minimum", functor::minimum, float, Eigen::half,
bfloat16, double, int16, int32, int64); bfloat16, double, int32, int64);
#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM #if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
REGISTER5(BinaryOp, GPU, "Minimum", functor::minimum, float, Eigen::half, REGISTER4(BinaryOp, GPU, "Minimum", functor::minimum, float, Eigen::half,
double, int16, int64); double, int64);
// A special GPU kernel for int32. // A special GPU kernel for int32.
// TODO(b/25387198): Also enable int32 in device memory. This kernel // TODO(b/25387198): Also enable int32 in device memory. This kernel

4
tensorflow/core/ops/math_ops.cc
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@ -549,7 +549,7 @@ REGISTER_OP("Maximum")
.Input("x: T") .Input("x: T")
.Input("y: T") .Input("y: T")
.Output("z: T") .Output("z: T")
.Attr("T: {bfloat16, half, float, double, int16, int32, int64}") .Attr("T: {bfloat16, half, float, double, int32, int64}")
.SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn); .SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn);
// Note: This op is not commutative w.r.t. to all its inputs. // Note: This op is not commutative w.r.t. to all its inputs.
@ -573,7 +573,7 @@ REGISTER_OP("Minimum")
.Input("x: T") .Input("x: T")
.Input("y: T") .Input("y: T")
.Output("z: T") .Output("z: T")
.Attr("T: {bfloat16, half, float, double, int16, int32, int64}") .Attr("T: {bfloat16, half, float, double, int32, int64}")
.SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn); .SetShapeFn(shape_inference::BroadcastBinaryOpShapeFn);
REGISTER_OP("Mod") REGISTER_OP("Mod")

2
tensorflow/core/ops/ops.pbtxt
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@ -23709,7 +23709,6 @@ op {
type: DT_HALF type: DT_HALF
type: DT_FLOAT type: DT_FLOAT
type: DT_DOUBLE type: DT_DOUBLE
type: DT_INT16
type: DT_INT32 type: DT_INT32
type: DT_INT64 type: DT_INT64
} }
@ -23965,7 +23964,6 @@ op {
type: DT_HALF type: DT_HALF
type: DT_FLOAT type: DT_FLOAT
type: DT_DOUBLE type: DT_DOUBLE
type: DT_INT16
type: DT_INT32 type: DT_INT32
type: DT_INT64 type: DT_INT64
} }

2
tensorflow/python/kernel_tests/cwise_ops_test.py
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@ -733,7 +733,7 @@ class MinMaxOpTest(test.TestCase):
def testBasic(self): def testBasic(self):
x = np.random.rand(1, 3, 2) * 100. x = np.random.rand(1, 3, 2) * 100.
y = np.random.rand(1, 3, 2) * 100. y = np.random.rand(1, 3, 2) * 100.
for t in [np.float16, np.float32, np.float64, np.int16, np.int32, np.int64]: for t in [np.float16, np.float32, np.float64, np.int32, np.int64]:
self._compare(x.astype(t), y.astype(t), use_gpu=False) self._compare(x.astype(t), y.astype(t), use_gpu=False)
self._compare(x.astype(t), y.astype(t), use_gpu=True) self._compare(x.astype(t), y.astype(t), use_gpu=True)