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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include "tensor_buffer_type_mapper.h"
#include "tensor_buffer_operations.h"
#include <algorithm>
#include <cmath>
#include <limits>
namespace search::tensor {
TensorBufferTypeMapper::TensorBufferTypeMapper()
: vespalib::datastore::ArrayStoreTypeMapper(),
_ops(nullptr)
{
}
TensorBufferTypeMapper::TensorBufferTypeMapper(uint32_t max_small_subspaces_type_id, double grow_factor, size_t max_buffer_size, TensorBufferOperations* ops)
: vespalib::datastore::ArrayStoreTypeMapper(),
_ops(ops)
{
_array_sizes.reserve(max_small_subspaces_type_id + 1);
_array_sizes.emplace_back(0); // type id 0 uses LargeSubspacesBufferType
uint32_t num_subspaces = _ops->is_dense() ? 1 : 0;
size_t prev_array_size = 0u;
size_t array_size = 0u;
for (uint32_t type_id = 1; type_id <= max_small_subspaces_type_id; ++type_id) {
if (type_id > 1) {
num_subspaces = std::max(num_subspaces + 1, static_cast<uint32_t>(std::floor(num_subspaces * grow_factor)));
}
array_size = _ops->get_buffer_size(num_subspaces);
while (array_size <= prev_array_size) {
++num_subspaces;
array_size = _ops->get_buffer_size(num_subspaces);
}
if (array_size > std::numeric_limits<uint32_t>::max() ||
array_size >= 2 * max_buffer_size) {
break;
}
_array_sizes.emplace_back(array_size);
if (_ops->is_dense()) {
break;
}
prev_array_size = array_size;
}
}
TensorBufferTypeMapper::~TensorBufferTypeMapper() = default;
}
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