diff options
Diffstat (limited to 'tensorflow/compiler/tf2xla/op_registrations.cc')
| -rw-r--r-- | tensorflow/compiler/tf2xla/op_registrations.cc | 502 |
1 files changed, 502 insertions, 0 deletions
diff --git a/tensorflow/compiler/tf2xla/op_registrations.cc b/tensorflow/compiler/tf2xla/op_registrations.cc new file mode 100644 index 0000000000..d8a4dad4b3 --- /dev/null +++ b/tensorflow/compiler/tf2xla/op_registrations.cc @@ -0,0 +1,502 @@ +/* Copyright 2017 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. +==============================================================================*/ + +// Kernel registrations for XLA JIT devices. + +#include "tensorflow/compiler/tf2xla/xla_compilation_device.h" +#include "tensorflow/core/framework/op_kernel.h" + +namespace tensorflow { +namespace { + +// CPU JIT device registrations. + +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("_Arg").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("_ArrayToList")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("_ListToArray")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("_Retval").TypeConstraint("T", kCpuAllTypes)); + +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Abs").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Add").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("AddN").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("All")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("Any")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("AvgPool").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("AvgPoolGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("BatchMatMul").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("BiasAdd").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("BiasAddV1").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("BiasAddGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("BroadcastGradientArgs")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Cast") + .TypeConstraint("SrcT", kCpuAllTypes) + .TypeConstraint("DstT", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Ceil").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Concat").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("ConcatV2") + .TypeConstraint("T", kCpuAllTypes) + .TypeConstraint("Tidx", DT_INT32)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("ConcatOffset")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Conv2D").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_CPU_XLA_JIT, + Name("Conv2DBackpropFilter").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_CPU_XLA_JIT, + Name("Conv2DBackpropInput").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_CPU_XLA_JIT, + Name("DepthwiseConv2dNative").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Diag").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("DiagPart").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Div").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("DynamicStitch").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Equal").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Exp").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("ExpandDims").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Fill").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Floor").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("FloorDiv").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("FloorMod").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Greater").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("GreaterEqual").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Inv").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Reciprocal").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("InvertPermutation").TypeConstraint("T", DT_INT32)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("L2Loss").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Less").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("LessEqual").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("LinSpace").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Log").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("LogicalAnd")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("LogicalNot")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("LogicalOr")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("LogSoftmax").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("LRN").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("LRNGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Maximum").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("MatMul").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("MatrixDiag").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("MatrixDiagPart").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Max").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("MaxPool").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("MaxPoolGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Mean").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Min").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Minimum").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Mod").TypeConstraint("T", kCpuIntTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Mul").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Neg").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("NotEqual").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Pack").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Pad").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Pow").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("PreventGradient").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Prod").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Range").TypeConstraint("Tidx", kCpuNumericTypes)); +// TODO(b/31361304): disabled because of XLA bugs. +// REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("RandomStandardNormal")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("RandomUniform")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("RandomUniformInt")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("Rank")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("RealDiv").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Relu").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Relu6").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("ReluGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Relu6Grad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Reshape").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Rsqrt").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("RsqrtGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Select").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("Shape")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("ShapeN")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Sigmoid").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("SigmoidGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Sign").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("Size")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Slice").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Softmax").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_CPU_XLA_JIT, + Name("SoftmaxCrossEntropyWithLogits").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Softplus").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("SoftplusGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("SparseMatMul") + .TypeConstraint("Ta", kCpuFloatTypes) + .TypeConstraint("Tb", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Split").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("SplitV").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Square").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL( + DEVICE_CPU_XLA_JIT, + Name("SquaredDifference").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Squeeze").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Sqrt").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("StopGradient").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("StridedSlice").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("StridedSliceGrad").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Sub").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Sum").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, Name("SymbolicGradient")); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Tanh").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("TanhGrad").TypeConstraint("T", kCpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Tile").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Transpose").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("TruncateDiv").TypeConstraint("T", kCpuIntTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("TruncateMod").TypeConstraint("T", kCpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Unpack").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_CPU_XLA_JIT, + Name("ZerosLike").TypeConstraint("T", kCpuNumericTypes)); + +REGISTER_XLA_JIT_ONLY_KERNEL(DEVICE_CPU_XLA_JIT, + Name("Const").TypeConstraint("dtype", + kCpuAllTypes)); +REGISTER_XLA_JIT_ONLY_KERNEL( + DEVICE_CPU_XLA_JIT, Name("Identity").TypeConstraint("T", kCpuAllTypes)); +REGISTER_XLA_JIT_ONLY_KERNEL(DEVICE_CPU_XLA_JIT, Name("NoOp")); + +// GPU JIT device registrations + +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("_Arg").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("_ArrayToList")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("_ListToArray")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("_Retval").TypeConstraint("T", kGpuAllTypes)); + +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Abs").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Add").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("AddN").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("All")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("Any")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("AvgPool").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("AvgPoolGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("BatchMatMul").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("BiasAdd").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("BiasAddV1").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("BiasAddGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("BroadcastGradientArgs")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Cast") + .TypeConstraint("SrcT", kGpuAllTypes) + .TypeConstraint("DstT", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Ceil").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Concat").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("ConcatV2").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("ConcatOffset")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Conv2D").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_GPU_XLA_JIT, + Name("Conv2DBackpropFilter").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_GPU_XLA_JIT, + Name("Conv2DBackpropInput").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_GPU_XLA_JIT, + Name("DepthwiseConv2dNative").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Diag").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("DiagPart").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Div").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("DynamicStitch").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Equal").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Exp").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("ExpandDims").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Fill").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Floor").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("FloorDiv").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("FloorMod").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Greater").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("GreaterEqual").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Inv").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Reciprocal").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("InvertPermutation").TypeConstraint("T", DT_INT32)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("L2Loss").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Less").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("LessEqual").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("LinSpace").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Log").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("LogicalAnd")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("LogicalNot")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("LogicalOr")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("LogSoftmax").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("LRN").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("LRNGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Maximum").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("MatMul").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("MatrixDiag").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("MatrixDiagPart").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Max").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("MaxPool").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("MaxPoolGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Mean").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Min").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Minimum").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Mod").TypeConstraint("T", kGpuIntTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Mul").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Neg").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("NotEqual").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Pack").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Pad").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Pow").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("PreventGradient").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Prod").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Range").TypeConstraint("Tidx", kGpuNumericTypes)); +// TODO(b/31361304): disabled because of XLA bugs. +// REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("RandomStandardNormal")); +// REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("RandomUniform")); +// REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("RandomUniformInt")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("Rank")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("RealDiv").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Relu").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Relu6").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("ReluGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Relu6Grad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Reshape").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Rsqrt").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("RsqrtGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Select").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("Shape")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("ShapeN")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Sigmoid").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("SigmoidGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Sign").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("Size")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Slice").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Softmax").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL( + DEVICE_GPU_XLA_JIT, + Name("SoftmaxCrossEntropyWithLogits").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Softplus").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("SoftplusGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("SparseMatMul") + .TypeConstraint("Ta", kGpuFloatTypes) + .TypeConstraint("Tb", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Split").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("SplitV").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Square").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL( + DEVICE_GPU_XLA_JIT, + Name("SquaredDifference").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Squeeze").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Sqrt").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("StopGradient").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("StridedSlice").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("StridedSliceGrad").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Sub").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Sum").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, Name("SymbolicGradient")); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Tanh").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("TanhGrad").TypeConstraint("T", kGpuFloatTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Tile").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Transpose").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("TruncateDiv").TypeConstraint("T", kGpuIntTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("TruncateMod").TypeConstraint("T", kGpuNumericTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Unpack").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_KERNEL(DEVICE_GPU_XLA_JIT, + Name("ZerosLike").TypeConstraint("T", kGpuNumericTypes)); + +REGISTER_XLA_JIT_ONLY_KERNEL(DEVICE_GPU_XLA_JIT, + Name("Const").TypeConstraint("dtype", + kGpuAllTypes)); +REGISTER_XLA_JIT_ONLY_KERNEL( + DEVICE_GPU_XLA_JIT, Name("Identity").TypeConstraint("T", kGpuAllTypes)); +REGISTER_XLA_JIT_ONLY_KERNEL(DEVICE_GPU_XLA_JIT, Name("NoOp")); + +} // anonymous namespace +} // namespace tensorflow |