/* Copyright 2015 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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// A class to manage slices of a tensor. You can "register" set of slices for a
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// tensor and then "query" if we have data for a given slice.
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// TODO(yangke): consider moving it to a more private place so that we don't
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// need to expose the API.
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#ifndef TENSORFLOW_UTIL_TENSOR_SLICE_SET_H_
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#define TENSORFLOW_UTIL_TENSOR_SLICE_SET_H_
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#include <string> // for string
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#include <unordered_map>
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#include <vector>
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#include "tensorflow/core/framework/tensor_shape.h"
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#include "tensorflow/core/framework/tensor_slice.h"
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#include "tensorflow/core/framework/types.h"
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#include "tensorflow/core/lib/core/status.h" // for Status
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#include "tensorflow/core/lib/core/stringpiece.h" // for StringPiece
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#include "tensorflow/core/platform/types.h" // for int64
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namespace tensorflow {
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namespace checkpoint {
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class TensorSliceSet {
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public:
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TensorSliceSet(const TensorShape& shape, DataType type);
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virtual ~TensorSliceSet();
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const TensorShape& shape() const { return shape_; }
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const DataType type() const { return type_; }
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// Register a new slice for the tensor. The "tag" is an arbitrary string
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// associated with the slice (in one application it denotes the name of the
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// file that contains the slice); the "data" points to the data of the tensor
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// slice (it can be a nullptr).
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// We don't take the ownership of "data" and the caller needs to make sure
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// the data is always available during the life time of the tensor slice set
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// if it is not nullptr.
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Status Register(const TensorSlice& slice, const string& tag,
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const float* data);
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// Query about a new slice: checks if we have data for "slice" and if we have
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// the data and "data" is not nullptr, fill "data" with the slice data. The
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// caller needs to make sure "data" point to a large enough buffer.
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// TODO(yangke): avoid unnecessary copying by using a core::RefCounted
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// pointer.
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bool Query(const TensorSlice& slice, float* data) const;
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// Alternative way of querying about a new slice: instead of copying the
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// data, it returns a list of meta data about the stored slices that will
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// supply data for the slice.
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bool QueryMeta(
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const TensorSlice& slice,
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std::vector<std::pair<tensorflow::TensorSlice, string>>* results) const;
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struct SliceInfo {
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TensorSlice slice;
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const string tag;
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const float* data;
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int64 num_floats;
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};
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// Returns the map from slice string to SliceInfo.
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const std::unordered_map<string, SliceInfo>& Slices() const {
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return slices_;
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}
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private:
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const TensorShape shape_;
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const DataType type_;
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// We maintain a mapping from the slice string to the slice information.
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std::unordered_map<string, SliceInfo> slices_;
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// Minimal slice which contains all presented slices. Used for speeding up
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// overlap check when slices are being added consequently.
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TensorSlice slices_hull_;
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};
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// Registers "slice" in the TensorSliceSet stored in "tensor_slices", under key
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// "name". Other arguments are used for validations. Does not modify the map
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// or its values on non-OK.
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// REQUIRES: tensor_slices != nullptr
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Status RegisterTensorSlice(
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const string& name, const TensorShape& shape, DataType type,
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const string& tag, const TensorSlice& slice,
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std::unordered_map<string, TensorSliceSet*>* tensor_slices);
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} // namespace checkpoint
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} // namespace tensorflow
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#endif // TENSORFLOW_UTIL_TENSOR_SLICE_SET_H_
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