79 lines
3.6 KiB
C++
79 lines
3.6 KiB
C++
/* Copyright 2017 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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// Utilities for working with XLA Literals.
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#ifndef TENSORFLOW_COMPILER_TF2XLA_LITERAL_UTIL_H_
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#define TENSORFLOW_COMPILER_TF2XLA_LITERAL_UTIL_H_
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#include "absl/types/span.h"
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#include "tensorflow/compiler/xla/literal.h"
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#include "tensorflow/compiler/xla/xla_data.pb.h"
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#include "tensorflow/core/framework/tensor.h"
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#include "tensorflow/core/lib/core/status.h"
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namespace tensorflow {
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// Returns a BorrowingLiteral that utilizes the same underlying buffer owned by
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// 'host_tensor'.
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Status HostTensorToBorrowingLiteral(const Tensor& host_tensor,
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xla::BorrowingLiteral* literal);
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// Similar as above, except the literal shape is explicitly provided and used
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// instead of obtaining it from the 'host_tensor'. The provided literal shape
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// 'xla_shape' must be compatible with the shape of 'host_tensor'.
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Status HostTensorToBorrowingLiteral(const xla::Shape& xla_shape,
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const Tensor& host_tensor,
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xla::BorrowingLiteral* literal);
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// Returns a Literal with the contents of 'host_tensor', backed by its own
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// storage (i.e., not reusing 'host_tensor's buffers.)
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xla::StatusOr<xla::Literal> HostTensorToLiteral(const Tensor& host_tensor);
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// Returns a MutableBorrowingLiteral that utilizes the same underlying buffer
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// owned by 'host_tensor', but is mutable via the xla::Literal methods.
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Status HostTensorToMutableBorrowingLiteral(
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Tensor* host_tensor, xla::MutableBorrowingLiteral* literal);
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// Similar as above, except the literal shape is explicitly provided and used
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// instead of obtaining it from the 'host_tensor'. The provided literal shape
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// 'xla_shape' must be compatible with the shape of 'host_tensor'.
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Status HostTensorToMutableBorrowingLiteral(
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const xla::Shape& xla_shape, Tensor* host_tensor,
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xla::MutableBorrowingLiteral* literal);
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// Returns a BorrowingLiteral tuple that utilizes the same underlying buffers
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// owned by 'host_tensors'.
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Status HostTensorsToBorrowingLiteralTuple(absl::Span<const Tensor> host_tensors,
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xla::BorrowingLiteral* literal);
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// Copies 'literal' to freshly allocated 'host_tensor', which is allocated of
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// type <target_type>.
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// Fails if the literal's primitive type !=
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// DataTypeToPrimitiveType(target_type). Note that <target_type> is not
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// derivable from the type of <literal>, because multiple tensorflow types map
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// to the same XLA type (e.g. INT32 and QINT32 both map to INT32 in
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// XLA).
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Status LiteralToHostTensor(const xla::LiteralSlice& literal,
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DataType target_type, Tensor* host_tensor);
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// Copies the contents of 'literal' to a previously allocated tensor
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// 'host_tensor'. The tensor and the literal must have the same number of
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// elements and the same type.
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Status CopyLiteralToHostTensor(const xla::LiteralSlice& literal,
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Tensor* host_tensor);
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} // namespace tensorflow
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#endif // TENSORFLOW_COMPILER_TF2XLA_LITERAL_UTIL_H_
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