/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_CORE_UTIL_TENSOR_OPS_UTIL_H_
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#define TENSORFLOW_CORE_UTIL_TENSOR_OPS_UTIL_H_
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#define EIGEN_USE_THREADS
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/register_types.h"
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#include "tensorflow/core/framework/tensor.h"
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#include "tensorflow/core/framework/types.h"
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#include "tensorflow/core/framework/variant_op_registry.h"
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#include "tensorflow/core/lib/core/status.h"
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namespace tensorflow {
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typedef Eigen::ThreadPoolDevice CPUDevice;
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typedef Eigen::GpuDevice GPUDevice;
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template <typename Device>
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Status ZerosLikeTensor(OpKernelContext* ctx, const Tensor& x, Tensor* out) {
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AllocatorAttributes attr;
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if (x.dtype() == DT_VARIANT) {
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attr.set_on_host(true);
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}
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TF_RETURN_IF_ERROR(ctx->allocate_temp(x.dtype(), x.shape(), out, attr));
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switch (out->dtype()) {
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#define DTYPE_CASE(dtype) \
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case DataTypeToEnum<dtype>::value: \
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/* TODO(skyewm): use SetZeroFunctor like in ZerosLikeOp? */ \
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out->flat<dtype>().device(ctx->eigen_device<Device>()) = \
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out->flat<dtype>().constant(dtype(0)); \
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break;
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TF_CALL_POD_TYPES(DTYPE_CASE)
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#undef DTYPE_CASE
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case DT_INVALID: {
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*out = Tensor(DT_INVALID);
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break;
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}
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case DataTypeToEnum<Variant>::value: {
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Variant* out_variant = out->scalar<Variant>().data();
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TF_RETURN_IF_ERROR(
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UnaryOpVariant<Device>(ctx, ZEROS_LIKE_VARIANT_UNARY_OP,
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x.scalar<Variant>()(), out_variant));
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break;
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}
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default:
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return errors::InvalidArgument(
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"Trying to compute zeros_like for unsupported dtype ",
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DataTypeString(out->dtype()));
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}
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return Status::OK();
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}
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template <typename Device>
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Status BinaryAddTensors(OpKernelContext* ctx, const Tensor& a, const Tensor& b,
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Tensor* out) {
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if (a.dtype() == DT_INVALID) {
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*out = b;
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return Status::OK();
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}
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if (b.dtype() == DT_INVALID) {
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*out = a;
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return Status::OK();
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}
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if (a.dtype() != b.dtype()) {
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return errors::InvalidArgument(
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"Trying to add two tensors with incompatible element types. ",
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"One is ", DataTypeString(a.dtype()), " and the other is ",
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DataTypeString(b.dtype()));
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}
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if (a.shape() != b.shape()) {
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// TODO(apassos) support broadcasting additions here?
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return errors::InvalidArgument(
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"Trying to add two tensors with incompatible element shapes. ",
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"One is ", a.shape().DebugString(), " and the other is ",
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b.shape().DebugString());
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}
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AllocatorAttributes attr;
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if (a.dtype() == DT_VARIANT) {
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attr.set_on_host(true);
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}
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TF_RETURN_IF_ERROR(ctx->allocate_temp(a.dtype(), a.shape(), out, attr));
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switch (out->dtype()) {
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#define DTYPE_CASE(dtype) \
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case DataTypeToEnum<dtype>::value: \
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out->flat<dtype>().device(ctx->eigen_device<Device>()) = \
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a.flat<dtype>() + b.flat<dtype>(); \
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break;
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TF_CALL_NUMBER_TYPES(DTYPE_CASE)
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#undef DTYPE_CASE
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case DataTypeToEnum<Variant>::value: {
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Variant* out_variant = out->scalar<Variant>().data();
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TF_RETURN_IF_ERROR(BinaryOpVariants<Device>(
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ctx, ADD_VARIANT_BINARY_OP, a.scalar<Variant>()(),
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b.scalar<Variant>()(), out_variant));
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break;
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}
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default:
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return errors::InvalidArgument("Trying to add unsupported dtype ",
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out->dtype());
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}
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return Status::OK();
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}
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} // namespace tensorflow
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#endif // TENSORFLOW_CORE_UTIL_TENSOR_OPS_UTIL_H_
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