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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_store.h"
#include <vespa/document/util/serializableexceptions.h>
#include <vespa/eval/eval/value_codec.h>
#include <vespa/eval/streamed/streamed_value_builder_factory.h>
#include <vespa/vespalib/datastore/array_store.hpp>
#include <vespa/vespalib/datastore/buffer_type.hpp>
#include <vespa/vespalib/datastore/compaction_context.h>
#include <vespa/vespalib/datastore/compaction_strategy.h>
#include <vespa/vespalib/datastore/datastore.hpp>
#include <vespa/vespalib/util/size_literals.h>
using document::DeserializeException;
using vespalib::alloc::MemoryAllocator;
using vespalib::datastore::CompactionContext;
using vespalib::datastore::CompactionStrategy;
using vespalib::datastore::EntryRef;
using vespalib::eval::StreamedValueBuilderFactory;
using vespalib::eval::Value;
using vespalib::eval::ValueType;
namespace search::tensor {
namespace {
constexpr float ALLOC_GROW_FACTOR = 0.2;
}
TensorBufferStore::TensorBufferStore(const ValueType& tensor_type, std::shared_ptr<MemoryAllocator> allocator, uint32_t max_small_subspaces_type_id)
: TensorStore(ArrayStoreType::get_data_store_base(_array_store)),
_tensor_type(tensor_type),
_ops(_tensor_type),
_array_store(ArrayStoreType::optimizedConfigForHugePage(max_small_subspaces_type_id,
TensorBufferTypeMapper(max_small_subspaces_type_id, &_ops),
MemoryAllocator::HUGEPAGE_SIZE,
MemoryAllocator::PAGE_SIZE,
8_Ki, ALLOC_GROW_FACTOR),
std::move(allocator), TensorBufferTypeMapper(max_small_subspaces_type_id, &_ops))
{
}
TensorBufferStore::~TensorBufferStore() = default;
void
TensorBufferStore::holdTensor(EntryRef ref)
{
_array_store.remove(ref);
}
EntryRef
TensorBufferStore::move_on_compact(EntryRef ref)
{
if (!ref.valid()) {
return EntryRef();
}
auto buf = _array_store.get_writable(ref);
auto new_ref = _array_store.add(buf);
_ops.copied_labels(buf);
return new_ref;
}
vespalib::MemoryUsage
TensorBufferStore::update_stat(const CompactionStrategy& compaction_strategy)
{
auto array_store_address_space_usage = _store.getAddressSpaceUsage();
auto array_store_memory_usage = _store.getMemoryUsage();
_compaction_spec = compaction_strategy.should_compact(array_store_memory_usage, array_store_address_space_usage);
return array_store_memory_usage;
}
std::unique_ptr<vespalib::datastore::ICompactionContext>
TensorBufferStore::start_compact(const CompactionStrategy& compaction_strategy)
{
auto compacting_buffers = _store.start_compact_worst_buffers(_compaction_spec, compaction_strategy);
return std::make_unique<CompactionContext>(*this, std::move(compacting_buffers));
}
EntryRef
TensorBufferStore::store_tensor(const Value &tensor)
{
uint32_t num_subspaces = tensor.index().size();
auto array_size = _ops.get_array_size(num_subspaces);
auto ref = _array_store.allocate(array_size);
auto buf = _array_store.get_writable(ref);
_ops.store_tensor(buf, tensor);
return ref;
}
EntryRef
TensorBufferStore::store_encoded_tensor(vespalib::nbostream &encoded)
{
const auto &factory = StreamedValueBuilderFactory::get();
auto val = vespalib::eval::decode_value(encoded, factory);
if (!encoded.empty()) {
throw DeserializeException("Leftover bytes deserializing tensor attribute value.", VESPA_STRLOC);
}
return store_tensor(*val);
}
std::unique_ptr<Value>
TensorBufferStore::get_tensor(EntryRef ref) const
{
if (!ref.valid()) {
return {};
}
auto buf = _array_store.get(ref);
return _ops.make_fast_view(buf, _tensor_type);
}
bool
TensorBufferStore::encode_stored_tensor(EntryRef ref, vespalib::nbostream &target) const
{
if (!ref.valid()) {
return false;
}
auto buf = _array_store.get(ref);
_ops.encode_stored_tensor(buf, _tensor_type, target);
return true;
}
}
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