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Subtensor propagation reused in loop specific iterations handler
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28 changes: 28 additions & 0 deletions
28
src/common/snippets/include/snippets/lowered/pass/propagate_subtensors.hpp
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| // Copyright (C) 2023 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #pragma once | ||
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| #include "snippets/lowered/linear_ir.hpp" | ||
| #include "snippets/lowered/pass/pass.hpp" | ||
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| namespace ov { | ||
| namespace snippets { | ||
| namespace lowered { | ||
| namespace pass { | ||
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| class UpdateSubtensors : public pass::SubgraphPass { | ||
| public: | ||
| UpdateSubtensors(size_t tail_size); | ||
| OPENVINO_RTTI("UpdateSubtensors", "Pass") | ||
| bool run(const LinearIR& linear_ir, LinearIR::constExprIt begin, LinearIR::constExprIt end) override; | ||
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| private: | ||
| size_t m_tail_size; | ||
| }; | ||
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| } // namespace pass | ||
| } // namespace lowered | ||
| } // namespace snippets | ||
| } // namespace ov |
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148 changes: 148 additions & 0 deletions
148
src/common/snippets/src/lowered/pass/propagate_subtensors.cpp
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| @@ -0,0 +1,148 @@ | ||
| // Copyright (C) 2023 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #include "snippets/lowered/pass/propagate_subtensors.hpp" | ||
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| #include "snippets/lowered/linear_ir.hpp" | ||
| #include "snippets/lowered/loop_manager.hpp" | ||
| #include "snippets/snippets_isa.hpp" | ||
| #include "snippets/utils.hpp" | ||
| #include "snippets/itt.hpp" | ||
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| namespace ov { | ||
| namespace snippets { | ||
| namespace lowered { | ||
| namespace pass { | ||
| namespace { | ||
| void propagate_updated_subtensor_through_loop(const LinearIR& linear_ir, | ||
| const LinearIR::LoopManager::LoopInfoPtr& loop_info, | ||
| LinearIR::container::const_iterator begin, | ||
| LinearIR::container::const_iterator end, | ||
| const size_t new_dim_value) { | ||
| std::map<lowered::PortDescriptorPtr, snippets::VectorDims> original_shapes; | ||
| static constexpr size_t existing_subtensor_value = SIZE_MAX; | ||
| // First step: set new dim value to the corresponding entry_points' dimensions | ||
| if (new_dim_value != existing_subtensor_value) { | ||
| for (const auto& port : loop_info->get_entry_points()) { | ||
| if (port.is_incremented) { | ||
| const auto& expr = port.expr_port->get_expr(); | ||
| const auto node = expr->get_node(); | ||
| auto desc = port.expr_port->get_descriptor_ptr(); | ||
| auto subtensor = desc->get_subtensor(); | ||
| if (port.dim_idx < subtensor.size()) { | ||
| *(subtensor.rbegin() + port.dim_idx) = new_dim_value; | ||
| desc->set_subtensor(subtensor); | ||
| } | ||
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| const auto parent_desc = expr->get_input_port_connector(port.expr_port->get_index())->get_source().get_descriptor_ptr(); | ||
| const auto& layout = parent_desc->get_layout(); | ||
| const auto& shape = parent_desc->get_shape(); | ||
| if (original_shapes.find(parent_desc) == original_shapes.end()) { | ||
| original_shapes[parent_desc] = shape; | ||
| } | ||
| auto new_shape = shape; | ||
| new_shape[*(layout.rbegin() + port.dim_idx)] = new_dim_value; | ||
| parent_desc->set_shape(new_shape); | ||
| } | ||
| } | ||
| } | ||
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| auto update_only_dim_idx_with_subtensor_value = [&](const LinearIR::LoopManager::LoopPort& port) { | ||
| if (port.is_incremented) { | ||
| auto desc = port.expr_port->get_descriptor_ptr(); | ||
| const auto expr = port.expr_port->get_expr(); | ||
| const auto parent_desc = expr->get_input_port_connector(port.expr_port->get_index())->get_source().get_descriptor_ptr(); | ||
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| const auto& layout = parent_desc->get_layout(); | ||
| const auto& shape = parent_desc->get_shape(); | ||
| const auto& desc_subtensor = desc->get_subtensor(); | ||
| if (port.dim_idx < desc_subtensor.size()) { | ||
| if (original_shapes.find(parent_desc) == original_shapes.end()) { | ||
| original_shapes[parent_desc] = shape; | ||
| } | ||
| auto new_shape = shape; | ||
| new_shape[*(layout.rbegin() + port.dim_idx)] = *(desc_subtensor.rbegin() + port.dim_idx); | ||
| parent_desc->set_shape(new_shape); | ||
| } | ||
| } | ||
| }; | ||
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| auto update_subtensors = [](const std::vector<PortDescriptorPtr>& descs, bool is_input) { | ||
| for (const auto& desc : descs) { | ||
| const auto& subtensor = desc->get_subtensor(); | ||
| if (!subtensor.empty()) { | ||
| auto planar_dims = is_input ? snippets::utils::get_planar_vdims(desc->get_shape(), desc->get_layout()) | ||
| : snippets::utils::get_preordered_vdims(desc->get_shape(), desc->get_layout()); | ||
| const size_t subtensor_start = planar_dims.size() - subtensor.size(); | ||
| VectorDims new_subtensor(planar_dims.begin() + subtensor_start, planar_dims.end()); | ||
| for (size_t i = 0; i < new_subtensor.size(); ++i) { | ||
| new_subtensor[i] = std::min(new_subtensor[i], subtensor[i]); | ||
| } | ||
| desc->set_subtensor(new_subtensor); | ||
| } | ||
| } | ||
| }; | ||
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| auto shape_inference_end_it = end; | ||
| const bool loop_by_last_dim = loop_info->get_dim_idx() == 0; | ||
| // Subtensors are updated using shape inference infrastructure: | ||
| // For inner loops propagation function is called recursively | ||
| for (auto expr_it = begin; expr_it != end; expr_it++) { | ||
| const auto expr = *expr_it; | ||
| if (ov::is_type<snippets::op::LoopEnd>(expr->get_node())) | ||
| continue; | ||
| if (auto loop_begin = ov::as_type_ptr<snippets::op::LoopBegin>(expr->get_node())) { | ||
| const auto loop_end = loop_begin->get_loop_end(); | ||
| const auto inner_loop_info = linear_ir.get_loop_manager()->get_loop_info(loop_end->get_id()); | ||
| const auto inner_begin = std::next(expr_it); | ||
| const auto inner_end = linear_ir.find(linear_ir.get_expr_by_node(loop_end)); | ||
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| // The corresponding shapes of inner loops entry points must be updated using existing subtensor values | ||
| if (new_dim_value == existing_subtensor_value) { | ||
| for (const auto& port : loop_info->get_entry_points()) | ||
| update_only_dim_idx_with_subtensor_value(port); | ||
| } | ||
| propagate_updated_subtensor_through_loop(linear_ir, inner_loop_info, inner_begin, inner_end, existing_subtensor_value); | ||
| expr_it = inner_end; | ||
| continue; | ||
| } | ||
| if ((ov::is_type<snippets::op::BroadcastMove>(expr_it->get()->get_node()) || | ||
| ov::is_type<snippets::op::BroadcastLoad>(expr_it->get()->get_node())) && | ||
| loop_by_last_dim) { | ||
| // WA: we have to break subtensor propagation if we try to propagate new last dim through Broadcast nodes | ||
| // which broadcast last dim in original dimension value anyway | ||
| // This workaround might be avoided if blocked shape are used for tail size propagation | ||
| shape_inference_end_it = expr_it; | ||
| break; | ||
| } | ||
| expr->updateShapes(); | ||
| update_subtensors(expr->get_input_port_descriptors(), true); | ||
| update_subtensors(expr->get_output_port_descriptors(), false); | ||
| } | ||
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| // After subtensor propagation, the original shapes must be restored | ||
| for (const auto& elem : original_shapes) | ||
| elem.first->set_shape(elem.second); | ||
| for (auto expr_it = begin; expr_it != shape_inference_end_it; expr_it++) | ||
| (*expr_it)->updateShapes(); | ||
| } | ||
| } // namespace | ||
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| UpdateSubtensors::UpdateSubtensors(size_t tail_size) : SubgraphPass(), m_tail_size(tail_size) {} | ||
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| bool UpdateSubtensors::run(const LinearIR& linear_ir, LinearIR::constExprIt begin, LinearIR::constExprIt end) { | ||
| const auto& expr = *end; | ||
| const auto node = expr->get_node(); | ||
| const auto loop_end = ov::as_type_ptr<op::LoopEnd>(node); | ||
| const auto& loop_manager = linear_ir.get_loop_manager(); | ||
| const auto& loop_info = loop_manager->get_loop_info(loop_end->get_id()); | ||
| propagate_updated_subtensor_through_loop(linear_ir, loop_info, std::next(begin), end, m_tail_size); | ||
| return true; | ||
| } | ||
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| } // namespace pass | ||
| } // namespace lowered | ||
| } // namespace snippets | ||
| } // namespace ov | ||
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