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// 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.
// =============================================================================
#ifndef TENSORFLOW_CONTRIB_BOOSTED_TREES_LIB_UTILS_BATCH_FEATURES_H_
#define TENSORFLOW_CONTRIB_BOOSTED_TREES_LIB_UTILS_BATCH_FEATURES_H_
#include <vector>
#include "tensorflow/contrib/boosted_trees/lib/utils/examples_iterable.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/util/sparse/sparse_tensor.h"
namespace tensorflow {
namespace boosted_trees {
namespace utils {
class BatchFeatures {
public:
// Constructs batch features with a fixed batch size.
explicit BatchFeatures(int64 batch_size) : batch_size_(batch_size) {}
// Disallow copy and assign.
BatchFeatures(const BatchFeatures& other) = delete;
BatchFeatures& operator=(const BatchFeatures& other) = delete;
// Method to initialize batch features from op kernel context.
Status Initialize(std::vector<Tensor> dense_float_features_list,
std::vector<Tensor> sparse_float_feature_indices_list,
std::vector<Tensor> sparse_float_feature_values_list,
std::vector<Tensor> sparse_float_feature_shapes_list,
std::vector<Tensor> sparse_int_feature_indices_list,
std::vector<Tensor> sparse_int_feature_values_list,
std::vector<Tensor> sparse_int_feature_shapes_list);
Status GetFeatureColumnSizes(int64* const num_dense_float_features,
int64* const num_sparse_float_features,
int64* const num_sparse_int_features) const {
QCHECK_NE(num_dense_float_features, (int64*) nullptr);
QCHECK_NE(num_sparse_float_features, (int64*) nullptr);
QCHECK_NE(num_sparse_int_features, (int64*) nullptr);
*num_dense_float_features = dense_float_feature_columns_.size();
*num_sparse_float_features = sparse_float_feature_columns_.size();
*num_sparse_int_features = sparse_int_feature_columns_.size();
if (*num_dense_float_features == 0 && *num_sparse_float_features == 0 &&
*num_sparse_int_features == 0) {
return errors::FailedPrecondition("Not initialized yet.");
}
return Status::OK();
}
// Creates an example iterable for the requested slice.
ExamplesIterable examples_iterable(int64 example_start,
int64 example_end) const {
QCHECK(example_start >= 0 && example_end >= 0);
QCHECK(example_start < batch_size_ && example_end <= batch_size_);
return ExamplesIterable(
dense_float_feature_columns_, sparse_float_feature_columns_,
sparse_int_feature_columns_, example_start, example_end);
}
// Returns the fixed batch size.
int64 batch_size() const { return batch_size_; }
private:
// Total number of examples in the batch.
const int64 batch_size_;
// Dense float feature columns.
std::vector<Tensor> dense_float_feature_columns_;
// Sparse float feature columns.
std::vector<sparse::SparseTensor> sparse_float_feature_columns_;
// Sparse int feature columns.
std::vector<sparse::SparseTensor> sparse_int_feature_columns_;
};
} // namespace utils
} // namespace boosted_trees
} // namespace tensorflow
#endif // TENSORFLOW_CONTRIB_BOOSTED_TREES_LIB_UTILS_BATCH_FEATURES_H_
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