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/* Copyright 2018 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.
==============================================================================*/
#ifndef TENSORFLOW_COMPILER_TF2XLA_LIB_UTIL_H_
#define TENSORFLOW_COMPILER_TF2XLA_LIB_UTIL_H_
#include "tensorflow/compiler/xla/client/xla_client/xla_builder.h"
#include "tensorflow/compiler/xla/client/xla_client/xla_computation.h"
#include "tensorflow/compiler/xla/statusor.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
namespace tensorflow {
// Returns a zero-filled tensor with shape `shape`.
xla::XlaOp Zeros(xla::XlaBuilder* builder, const xla::Shape& shape);
// Returns a floating point scalar constant of 'type' with 'value'.
// If 'type' is complex, returns a real value with zero imaginary component.
xla::XlaOp FloatLiteral(xla::XlaBuilder* builder, xla::PrimitiveType type,
double value);
// Makes a 1D tensor [0, ..., x, y] from two tensors x and y with zeros
// prepended until the array is length n_dims.
xla::XlaOp PrependZerosInMajorDims(xla::XlaBuilder* builder,
gtl::ArraySlice<xla::XlaOp> starts);
// Returns a integer scalar constant of 'type' with 'value'.
// If 'type' is complex, returns a real value with zero imaginary component.
xla::XlaOp IntegerLiteral(xla::XlaBuilder* builder, xla::PrimitiveType type,
int64 value);
// Builds a vector of zeros of length rank(x) with the last two values being
// those in `starts`.
xla::StatusOr<xla::XlaOp> PrependZerosInMajorDims(
xla::XlaBuilder* builder, const xla::XlaOp& x,
const std::vector<xla::XlaOp>& starts);
// Performs a slice in the minor dimensions of a Tensor.
xla::StatusOr<xla::XlaOp> SliceInMinorDims(xla::XlaBuilder* builder,
const xla::XlaOp& x,
gtl::ArraySlice<int64> start,
gtl::ArraySlice<int64> end);
// Builds a 1-d vector out of a concatenation of `major_dims` and `starts`.
std::vector<int64> PrependMajorDims(xla::XlaBuilder* builder,
const gtl::ArraySlice<int64>& major_dims,
const gtl::ArraySlice<int64>& indices);
// Performs a dynamic slice in the minor dimensions of a Tensor.
xla::StatusOr<xla::XlaOp> DynamicSliceInMinorDims(
xla::XlaBuilder* builder, const xla::XlaOp& x,
const std::vector<xla::XlaOp>& starts, const gtl::ArraySlice<int64>& sizes);
// Updates a slice of 'x', i.e.,
// x[start[0], ..., start[n]] = update
xla::StatusOr<xla::XlaOp> UpdateSlice(xla::XlaBuilder* builder,
const xla::XlaOp& x,
const xla::XlaOp& update,
gtl::ArraySlice<int64> start);
// Updates a slice of 'x', where 'start' contains a list of minor dimensions:
// x[..., start[0], ..., start[n]] = update
xla::StatusOr<xla::XlaOp> UpdateSliceInMinorDims(xla::XlaBuilder* builder,
const xla::XlaOp& x,
const xla::XlaOp& update,
gtl::ArraySlice<int64> start);
xla::StatusOr<xla::XlaOp> DynamicUpdateSliceInMinorDims(
xla::XlaBuilder* builder, const xla::XlaOp& x, const xla::XlaOp& update,
const std::vector<xla::XlaOp>& starts);
// Transposes a stack of matrices `x` by swapping the last two dimensions.
xla::StatusOr<xla::XlaOp> TransposeInMinorDims(xla::XlaBuilder* builder,
const xla::XlaOp& x);
// Applies a complex conjugation operation if `a` is complex and `conjugate_a`
// is true, otherwise returns its argument.
xla::StatusOr<xla::XlaOp> MaybeConjugate(xla::XlaBuilder* builder,
const xla::XlaOp& x, bool conjugate);
} // namespace tensorflow
#endif // TENSORFLOW_COMPILER_TF2XLA_LIB_UTIL_H_
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