表批处理嵌入操作符¶
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std::tuple<at::Tensor, at::Tensor, std::optional<at::Tensor>> get_unique_indices_cuda(const at::Tensor &linear_indices, const int64_t max_indices, const bool compute_count)¶
索引去重。
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std::tuple<at::Tensor, at::Tensor, std::optional<at::Tensor>, std::optional<at::Tensor>> get_unique_indices_with_inverse_cuda(const at::Tensor &linear_indices, const int64_t max_indices, const bool compute_count, const bool compute_inverse_indices)¶
索引去重。
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std::tuple<at::Tensor, at::Tensor, std::optional<at::Tensor>> lru_cache_find_uncached_cuda(at::Tensor unique_indices, at::Tensor unique_indices_length, int64_t max_indices, at::Tensor lxu_cache_state, int64_t time_stamp, at::Tensor lru_state, bool gather_cache_stats, at::Tensor uvm_cache_stats, bool lock_cache_line, at::Tensor lxu_cache_locking_counter, const bool compute_inverse_indices)¶
查找 LRU 缓存以查找未缓存的索引,然后根据集合对它们进行排序。
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int64_t host_lxu_cache_slot(int64_t h_in, int64_t C)¶
将索引映射到 cache_set。h_in:线性索引;C:缓存集数量。
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at::Tensor linearize_cache_indices_cuda(const at::Tensor &cache_hash_size_cumsum, const at::Tensor &indices, const at::Tensor &offsets, const std::optional<at::Tensor> &B_offsets, const int64_t max_B, const int64_t indices_base_offset)¶
将所有表的索引线性化以使其唯一
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at::Tensor linearize_cache_indices_from_row_idx_cuda(at::Tensor cache_hash_size_cumsum, at::Tensor update_table_indices, at::Tensor update_row_indices)¶
将所有表的索引线性化以使其唯一。注意 update_table_indices 和 update_row_indices 来自用于原地更新的行索引格式。
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at::Tensor direct_mapped_lxu_cache_lookup_cuda(at::Tensor linear_cache_indices, at::Tensor lxu_cache_state, int64_t invalid_index, bool gather_cache_stats, std::optional<at::Tensor> uvm_cache_stats)¶
LRU 缓存:从
weights
中获取与linear_cache_indices
对应的行,并在时间步time_stamp
将它们插入缓存中。. void lru_cache_populate_cuda(
at::Tensor weights,
at::Tensor hash_size_cumsum,
int64_t total_cache_hash_size,
at::Tensor cache_index_table_map,
at::Tensor weights_offsets,
at::Tensor D_offsets,
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
at::Tensor lxu_cache_weights,
int64_t time_stamp,
at::Tensor lru_state,
bool stochastic_rounding,
bool gather_cache_stats,
std::optional<at::Tensor> uvm_cache_stats,
bool lock_cache_line,
std::optional<at::Tensor> lxu_cache_locking_counter);
// LRU 缓存:从
weights
中获取与linear_cache_indices
对应的行,并在时间步time_stamp
将它们插入缓存中。. // weights 和 lxu_cache_weights 的元素类型为 “uint8_t” 字节 void lru_cache_populate_byte_cuda(
at::Tensor weights,
at::Tensor hash_size_cumsum,
int64_t total_cache_hash_size,
at::Tensor cache_index_table_map,
at::Tensor weights_offsets,
at::Tensor weights_tys,
at::Tensor D_offsets,
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
at::Tensor lxu_cache_weights,
int64_t time_stamp,
at::Tensor lru_state,
int64_t row_alignment,
bool gather_cache_stats,
std::optional<at::Tensor> uvm_cache_stats);
// direct-mapped (assoc=1) 版本的 lru_cache_populate_byte_cuda void direct_mapped_lru_cache_populate_byte_cuda(
at::Tensor weights,
at::Tensor hash_size_cumsum,
int64_t total_cache_hash_size,
at::Tensor cache_index_table_map,
at::Tensor weights_offsets,
at::Tensor weights_tys,
at::Tensor D_offsets,
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
at::Tensor lxu_cache_weights,
int64_t time_stamp,
at::Tensor lru_state,
at::Tensor lxu_cache_miss_timestamp,
int64_t row_alignment,
bool gather_cache_stats,
std::optional<at::Tensor> uvm_cache_stats);
// LFU 缓存:从
weights
中获取与linear_cache_indices
对应的行并将它们插入缓存中。 void lfu_cache_populate_cuda(
at::Tensor weights,
at::Tensor cache_hash_size_cumsum,
int64_t total_cache_hash_size,
at::Tensor cache_index_table_map,
at::Tensor weights_offsets,
at::Tensor D_offsets,
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
at::Tensor lxu_cache_weights,
at::Tensor lfu_state,
bool stochastic_rounding);
// LFU 缓存:从
weights
中获取与linear_cache_indices
对应的行并将它们插入缓存中。 // weights 和 lxu_cache_weights 的元素类型为 “uint8_t” 字节 void lfu_cache_populate_byte_cuda(
at::Tensor weights,
at::Tensor cache_hash_size_cumsum,
int64_t total_cache_hash_size,
at::Tensor cache_index_table_map,
at::Tensor weights_offsets,
at::Tensor weights_tys,
at::Tensor D_offsets,
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
at::Tensor lxu_cache_weights,
at::Tensor lfu_state,
int64_t row_alignment);
// 查找 LRU/LFU 缓存:查找所有索引的缓存权重位置。// 在缓存中查找与
linear_cache_indices
对应的槽位,并对缺失项使用哨兵值。 at::Tensor lxu_cache_lookup_cuda(
at::Tensor linear_cache_indices,
at::Tensor lxu_cache_state,
int64_t invalid_index,
bool gather_cache_stats,
std::optional<at::Tensor> uvm_cache_stats,
std::optional<at::Tensor> num_uniq_cache_indices,
std::optional<at::Tensor> lxu_cache_locations_output);
at::Tensor emulate_cache_miss(
at::Tensor lxu_cache_locations,
const int64_t enforced_misses_per_256,
const bool gather_cache_stats,
at::Tensor uvm_cache_stats);
// 查找 LRU/LFU 缓存:查找所有索引的缓存权重位置。// 在缓存中查找与
linear_cache_indices
对应的槽位,并对缺失项使用哨兵值。
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void lxu_cache_flush_cuda(at::Tensor uvm_weights, at::Tensor cache_hash_size_cumsum, at::Tensor cache_index_table_map, at::Tensor weights_offsets, at::Tensor D_offsets, int64_t total_D, at::Tensor lxu_cache_state, at::Tensor lxu_cache_weights, bool stochastic_rounding)¶
刷新缓存:将缓存中的权重存储到后备存储中。
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void reset_weight_momentum_cuda(at::Tensor dev_weights, at::Tensor uvm_weights, at::Tensor lxu_cache_weights, at::Tensor weights_placements, at::Tensor weights_offsets, at::Tensor momentum1_dev, at::Tensor momentum1_uvm, at::Tensor momentum1_placements, at::Tensor momentum1_offsets, at::Tensor D_offsets, at::Tensor pruned_indices, at::Tensor pruned_indices_offsets, at::Tensor logical_table_ids, at::Tensor buffer_ids, at::Tensor cache_hash_size_cumsum, at::Tensor lxu_cache_state, int64_t total_cache_hash_size)¶