cg_impl.cpp 25.6 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
/**
 * \file src/core/impl/graph/cg_impl.cpp
 * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
 *
 * Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 */

#include "./cg_impl.h"
#include "./cg_impl_partial.h"
#include "./cg_impl_seq.h"

#include "megbrain/gopt/framework.h"
#include "megbrain/gopt/inference.h"
#include "megbrain/gopt/basic_arith.h"
#include "megbrain/gopt/misc.h"
20
#include "megbrain/graph/cg.h"
21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220
#include "megbrain/graph/event.h"
#include "megbrain/graph/exc_extra_info.h"
#include "megbrain/graph/helper.h"
#include "megbrain/opr/utility.h"


#if MGB_ENABLE_TENSOR_RT
#include "megbrain/tensorrt/opr_replace.h"
#endif

#if MGB_JIT
#include "megbrain/jit/fusion_pass.h"
#endif

#include "megbrain/gopt/weights_preprocess.h"

using namespace mgb;
using namespace cg;

namespace {
void check_opr_not_cross_mem(OperatorNodeBase* opr) {
    if (opr->node_prop().contain(
                OperatorNodeBase::NodeProp::Flag::CROSS_COMP_NODE_MEMORY))
        return;
    MemNode mem_node_id;
    bool first = true;
    auto check = [&](VarNode* var) {
        auto cur = var->comp_node().mem_node();
        mgb_assert(cur);
        if (first) {
            first = false;
            mem_node_id = cur;
        } else
            mgb_assert(mem_node_id == cur,
                       "for non cross-memory oprs, "
                       "all vars should reside on the same memory node");
    };
    for (auto i : opr->input()) {
        check(i);
    }
    for (auto i : opr->output()) {
        check(i);
    }
}

void update_output_shapes(static_infer::StaticInferManagerImpl& infer_mgr,
                          OperatorNodeBase* opr, bool add_freeze_flag) {
    for (auto i : opr->output()) {
        if (add_freeze_flag) {
            i->add_flag(VarNode::Flag::FLAG_FREEZED);
        }

        if (!i->contain_flag(VarNode::Flag::VOLATILE_CONTENT)) {
            using namespace static_infer;
            if (infer_mgr.get_infer_type(i).shape &
                (InferType::CONST | InferType::RT_STATIC)) {
                auto shp = infer_mgr.infer_shape_fallible(i);
                if (shp) {
                    i->shape(*shp);
                } else {
                    i->shape({});
                }
            } else {
                i->shape({});
            }
        }
    }
}

}  // anonymous namespace

/* ========================== global helpers ========================== */
void cg::update_output_var_shapes(OperatorNodeBase* opr) {
    update_output_shapes(static_cast<static_infer::StaticInferManagerImpl&>(
                                 opr->owner_graph()->static_infer_manager()),
                         opr, false);
}

/* ========================= DeviceMemoryAllocator ========================= */
void DeviceMemoryAllocator::alloc_static(ComputingGraph*,
                                         DeviceTensorStorage& dest,
                                         size_t size) {
    dest.ensure_size(size);
}

void DeviceMemoryAllocator::alloc_dynamic(VarNode*, DeviceTensorStorage& dest,
                                          size_t size) {
    dest.ensure_size(size);
}

void DeviceMemoryAllocator::defrag_prealloc_contig(ComputingGraph* graph,
                                                   CompNode comp_node,
                                                   size_t size){
        MGB_TRY{comp_node.free_device(comp_node.alloc_device(size));
}
MGB_CATCH(MemAllocError&, {})
}

size_t DeviceMemoryAllocator::static_alloc_version(ComputingGraph*) const {
    return 0;
}

/* ========================== ComputingGraph ========================== */
ComputingGraph::ComputingGraph() {
    static std::atomic_size_t tot_id{0};
    m_id = (tot_id++);
}

void ComputingGraph::assert_destroy(std::shared_ptr<ComputingGraph>& ptr) {
    mgb_assert(ptr.use_count() == 1, "unexpected use_count: %zu",
               size_t(ptr.use_count()));
    ptr.reset();
}

#if !MGB_THREAD_SAFE
size_t ComputingGraph::prealloc_static_storage(size_t size) {
    // note that in single-threaded mode, all cpus map to the same comp node
    static int version = 0;
    auto cn = CompNode::load("cpu0");
    mgb_assert(cn == CompNode::load("cpu1"));
    auto inst = StaticDeviceMemoryManager::make_default_impl();
    auto ret = inst->get_size(cn);
    inst->alloc(nullptr, cn, size, version).ptr();
    version = inst->version(nullptr);
    return ret;
}
#endif

/* ========================== CallbackCaller ========================== */
MGB_DEFINE_OPR_CLASS(ComputingGraphImpl::CallbackCaller,
                           SingleCNOperatorNodeBase) // {
    std::vector<ComputingGraph::Callback> m_cb;

    void scn_do_execute() override {
        auto&& dv = input(0)->dev_tensor();
        for (auto&& i : m_cb) {
            // const cast for backward API compatibility
            i(const_cast<DeviceTensorND&>(dv));
        }
    }

    void init_output_static_infer_desc() override {
        using namespace cg::static_infer;
        owner_graph()->static_infer_manager().register_shape_infer(
                output(0), ShapeInferDesc::make_const({}));
    }

    void add_input_layout_constraint() override {
        if (owner_graph()->options().comp_node_seq_record_level) {
            // the user callback usually copies from device to host, which
            // involves tmp alloc if input is not contiguous
            input(0)->add_layout_constraint_contiguous();
        }
    }

    NodeProp* do_make_node_prop() const override {
        auto ret = Super::do_make_node_prop();
        ret->add_dep_type_existing_var(input(0),
                                       NodeProp::DepType::VALUE_ALLOW_EMPTY);
        return ret;
    }

    bool update_priority() const override {
        node_prop().attribute().priority = std::numeric_limits<int>::min();
        return true;
    }

public:
    CallbackCaller(VarNode* inp)
            : Super{inp->owner_graph(), {}, "callback", {inp}} {
        add_input({inp});
        using F = VarNode::Flag;
        add_output(None)
                ->add_flag(F::ALLOW_EMPTY_SHAPE)
                .add_flag(F::VOLATILE_CONTENT);
    }

    static SymbolVar make(SymbolVar inp) {
        return inp.insert_single_output_opr<CallbackCaller>(inp.node());
    }

    void add_callback(const ComputingGraph::Callback& cb) {
        mgb_assert(cb);
        m_cb.push_back(cb);
    }

    void clear_callback() { m_cb.clear(); }
};
MGB_DYN_TYPE_OBJ_FINAL_IMPL(ComputingGraphImpl::CallbackCaller);

/* ========================== ComputingGraphImpl ========================== */

ComputingGraphImpl::Components::Components(ComputingGraphImpl* owner)
        : topo_sorter{owner},
          var_node_mem_manager{owner},
          seq_comp_node_opt{owner},
          static_infer_manager{owner},
          static_infer_comp_seq_manager{owner},
          grad_manager{owner},
#if MGB_ENABLE_SUBLINEAR
221 222
          seq_modifier_for_sublinear_memory{owner,
              &(owner->options().sublinear_mem_cofig)},
223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475
#endif
#if MGB_ENABLE_MEMORY_SWAP
          memory_swap_support{owner},
#endif
          eager_eval_manager{owner}

{
}

ComputingGraphImpl::ComputingGraphImpl() {
    auto ptr = new (&m_components_storage) Components{this};
    mgb_assert(ptr == &components());
}

ComputingGraphImpl::~ComputingGraphImpl() {
    if (!is_finalized()) {
        cleanup();
    }
}

std::shared_ptr<void> ComputingGraphImpl::on_comp_node_finalize() {
    // hold a reference because the object itself may be deleted by user data or
    // oprs
    std::shared_ptr<void> ref = shared_from_this();
    cleanup();
    return ref;
}

void ComputingGraphImpl::cleanup() {
    if (m_recorded_seq_level2_dtor_chk) {
        m_recorded_seq_level2_dtor_chk->enable();
    }
    // clear device memory storage and return them to comp node
    clear_device_memory();

    // so opr dtors would incur no overhead when deleting vars
    m_var_node_pool.disable_freelist();

    // TODO: call this after each graph exec when we have faster impl
    CompNode::try_coalesce_all_free_memory();

    options().user_data.clear_all_user_data();
    components().~Components();
    m_var_receiver.clear();
    m_opr_refkeeper.clear();
}

OperatorNodeBase* ComputingGraphImpl::insert_opr(
        std::unique_ptr<OperatorNodeBase> opr_uniqp) {
    auto opr = opr_uniqp.get();

    if (opr->inserted_in_graph()) {
        // FIXME: it's just a trick used for re-evaluation in eager evaluation
        // mode. Since comp_graph has already taken an ownership of the opr,
        // we can release it directly.
        mgb_throw_if(
#if MGB_BUILD_SLIM_SERVING
            true,
#else
            !options().eager_evaluation,
#endif
            GraphError, "an inserted opr %s re-insert into graph"
            "with eager evaluation mode OFF.", opr->cname());
        opr_uniqp.release();
        // No need to do the insert_post under eager mode
        eager_eval_manager().on_opr_insert(opr);
        return opr;
    }

    auto&& infer_mgr = static_infer_manager_impl();
    auto cleanup = [&]() {
        infer_mgr.set_register_allowed_opr(nullptr);
        for (auto i : opr->output()) {
            infer_mgr.clear_tag_handler(i);
            var_node_mem_manager().remove_var_node_mem_trait(i);
        }
    };

    if (auto ret = graph_optimizer().insert_pre(opr)) {
        bool should_update_shape = true;
#if !MGB_BUILD_SLIM_SERVING
        // in normal mode, we update the shape in deduplication in case shape
        // changes; in eager evaluation mode, shape is set by EagerEvalManager
        // and should not be modified
        should_update_shape = !options().eager_evaluation;
#endif
        if (should_update_shape) {
            update_output_shapes(infer_mgr, ret, false);
        }
        cleanup();
        event().signal_inplace<cg::event::OprInserted>(true, ret, nullptr);
        ret = graph_optimizer().insert_post(ret);
        eager_eval_manager().on_opr_insert(ret);
        return ret;
    }

    // record opr early, since exceptions may refer to the opr
    m_opr_refkeeper.emplace_back(std::move(opr_uniqp));

    MGB_TRY {
        mgb_assert(!opr->inserted_in_graph());
        mgb_assert(!opr->output().empty(),
                   "operator must have at least one output");
        opr->set_inserted_in_graph();

        // basic init
        opr->init_output_comp_node();
        opr->init_output_dtype();
        opr->init_output_format();

        // check output initialized
        for (auto i : opr->output()) {
            mgb_assert(i->comp_node().valid() && i->dtype().valid());
        }

        // register static infer
        {
            auto old = infer_mgr.set_register_allowed_opr(opr);
            opr->init_output_static_infer_desc();
            infer_mgr.set_register_allowed_opr(old);
        }

        // more init
        opr->init_rt_force_dynamic_mem_alloc_imply_chain();

        // freeze output flag and static infer shape eagerly
        update_output_shapes(infer_mgr, opr, true);

        check_opr_not_cross_mem(opr);
    }
    MGB_CATCH(MegBrainError & exc, {
        cleanup();
        if (!exc.extra_info())
            OperatorNodeExcExtraInfo::record(opr, exc);
        event().signal_inplace<cg::event::OprInserted>(false, opr, &exc);
        throw;
    })

    // add to receiver list if above succeeds
    for (auto&& i : opr->input()) {
        auto iter = m_var_receiver.find(i);
        mgb_assert(iter != m_var_receiver.end());
        auto&& arr = iter->second;
        if (arr.empty() || arr.back() != opr) {
            // check if added, because opr may have identical inputs
            arr.push_back(opr);
        }
    }

    // alloc var receiver for the outputs
    for (auto&& i : opr->output()) {
        bool em = m_var_receiver[i].empty();
        mgb_assert(em);
    }

    event().signal_inplace<cg::event::OprInserted>(false, opr, nullptr);
    opr = graph_optimizer().insert_post(opr);
    eager_eval_manager().on_opr_insert(opr);
    return opr;
}

std::shared_ptr<ComputingGraph> ComputingGraph::make() {
    return std::make_shared<ComputingGraphImpl>();
}

std::unique_ptr<AsyncExecutable> ComputingGraphImpl::compile(
        const OutputSpec& out_spec) {
    return compile_commit(compile_prepare(out_spec));
}

SmallVector<std::unique_ptr<AsyncExecutable>>
ComputingGraphImpl::compile_multi_part(
        const SmallVector<OutputSpec>& out_specs) {
#if MGB_ENABLE_PARTIAL_EXECUTION
    return MultiPartCompiler{this}.compile(out_specs);
#else
    mgb_throw(MegBrainError, "partial execution disabled at compile time");
#endif
}

ComputingGraphImpl::CompileState ComputingGraphImpl::compile_prepare(
        const OutputSpec& out_spec) {
    auto&& cmpnt = components();
    mgb_throw_if(m_recorded_seq_level2_dtor_chk, GraphError,
                 "graphs with comp_node_seq_record_level==2 can only be "
                 "compiled once");

    mgb_throw_if(out_spec.empty(), GraphError,
                 "empty output spec given to ComputingGraph::compile");
    // topo sorter may have modified opr properties; restore them before this
    // new compiling
    topo_sorter().restore_opr_prop();
    cmpnt.seq_comp_node_opt.restore_comp_nodes();

    SpecialOprStat sopr_stat;
    auto dest_vars = get_dest_vars_from_out_spec(out_spec, sopr_stat);

#if MGB_ENABLE_SUBLINEAR
    if (options().enable_sublinear_memory_opt) {
        if (!sopr_stat.has_virtual_grad) {
            mgb_log_warn(
                    "no virtual grad var; sublinear memory may produce "
                    "unsatisfying result");
        }
        seq_modifier_for_sublinear_memory().set_priority_before_opt(
                dest_vars);
    }
#else
    mgb_assert(!options().enable_sublinear_memory_opt);
#endif  //  MGB_ENABLE_SUBLINEAR

#if !MGB_BUILD_SLIM_SERVING
    mgb_assert(!options().eager_evaluation,
               "attempt to compile eager_evaluation graph");

    {
        bool need_opt = std::abs(options().graph_opt_level) >= 2;
        gopt::GraphOptimizer optimizer;
        optimizer.verbosity(options().log_level);
        optimizer.enable_check_result(options().graph_opt_level < 0);
        if (sopr_stat.has_virtual_grad) {
            if (need_opt)
                optimizer.add_preset_passes(false, nullptr, &options());
            optimizer.add_pass<gopt::ExpandVirtualGradPass>();
        }
        if (need_opt)
            optimizer.add_preset_passes(true, nullptr, &options());
        optimizer.apply_inplace(dest_vars);
    }
#endif

#if MGB_ENABLE_TENSOR_RT
    if (options().graph_opt.tensorrt) {
        options().graph_opt.tensorrt = false;
        tensorrt::transform_dest_vars_inplace(dest_vars);
    }
#endif

    if (options().graph_opt.winograd_transform) {
        options().graph_opt.winograd_transform = false;
        gopt::transform_vars_inplace_with_winograd(dest_vars);
    }

#if MGB_JIT
    if (std::abs(options().graph_opt_level) == 0 && options().graph_opt.jit) {
        setenv("MGB_JIT_BACKEND","NVRTC",1);
        gopt::GraphOptimizer optimizer;
        optimizer.add_pass<gopt::JITFusionPass>(
                          sopr_stat.has_virtual_grad,
                          std::max<uint8_t>(options().graph_opt.jit, 1));
        optimizer.apply_inplace(dest_vars);
    }
#endif
476 477 478 479
    gopt::GraphOptimizer optimizer;
    optimizer.apply_optimize_options(options().graph_opt);
    options().graph_opt.reset();
    optimizer.apply_inplace(dest_vars);
480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730

    const OprNodeArray* opr_seq = nullptr;
    CompSeqExtraInfo extra_info;
    cmpnt.seq_comp_node_opt.optimize_comp_nodes(dest_vars);

    auto init_opr_seq = [&]() {
        ThinHashMap<VarNode*, CallbackCaller*> var2cb_caller;
        for (size_t i = 0; i < out_spec.size(); ++i) {
            auto&& cb = out_spec[i].second;
            if (cb) {
                auto var = dest_vars[i];
                auto&& cb_caller = var2cb_caller[var];
                if (!cb_caller) {
                    auto dvar = CallbackCaller::make(var);
                    cb_caller = &dvar.node()
                                         ->owner_opr()
                                         ->cast_final_safe<CallbackCaller>();
                    ++extra_info.var2recvinfo[dvar.node()].nr_direct_comp_req;
                    cb_caller->clear_callback();
                }
                cb_caller->add_callback(cb);
                dest_vars[i] = cb_caller->output(0);
            }
        }
        opr_seq = topo_sorter().get_comp_seq(extra_info, dest_vars);
    };

#if MGB_ENABLE_MEMORY_SWAP
    bool enable_swap_memory_after_sublinear =
            options().enable_sublinear_memory_opt &&
            options().enable_memory_swap;

    bool enable_swap_memory_without_sublinear =
            !(options().enable_sublinear_memory_opt) &&
            options().enable_memory_swap;

    if (enable_swap_memory_without_sublinear) {
        components().memory_swap_support.modify_dest_var_inplace(dest_vars);
    }
#else
    mgb_assert(!options().enable_memory_swap);
#endif

#if MGB_ENABLE_SUBLINEAR
    if (options().enable_sublinear_memory_opt) {
        MGB_TRY {
            seq_modifier_for_sublinear_memory().modify_endpoint_vars(
                    dest_vars);
#if MGB_ENABLE_MEMORY_SWAP
            if (enable_swap_memory_after_sublinear) {
                cmpnt.memory_swap_support.modify_dest_var_inplace(dest_vars);
            }
#endif

            init_opr_seq();
        }
        MGB_FINALLY(

                /*
                 * restore graph option immediately because it may be
                 * read/modified by user
                 */
                seq_modifier_for_sublinear_memory().restore_graph_option());
        seq_modifier_for_sublinear_memory().sanity_check(*opr_seq);
    } else {
        init_opr_seq();
    }
#else
    init_opr_seq();
#endif  //  MGB_ENABLE_SUBLINEAR

    return {std::move(extra_info), opr_seq};
}

std::unique_ptr<AsyncExecutable> ComputingGraphImpl::compile_commit(
        CompileState state) {
    auto comp_seq = std::make_unique<ComputingSequence>(shared_from_this());
    comp_seq->extra_info = std::move(state.extra_info);
    auto opr_seq = state.opr_seq;
    auto&& cmpnt = components();

    comp_seq->setup_opr_seq(opr_seq);
    for (auto&& i : *opr_seq) {
        for (auto&& j : i->node_prop().dep_map()) {
            if (OperatorNodeBase::NodeProp::is_device_value_dep(j.second)) {
                comp_seq->extra_info.var2recvinfo.at(j.first)
                        .last_dev_value_reader = i;
            }
        }
    }
    comp_seq->attach_to_graph();

    MGB_TRY {
        var_node_mem_manager().reset_opr_seq(comp_seq->extra_info, opr_seq);
        static_infer_comp_seq_manager().reset_dest(comp_seq->extra_info);
        cmpnt.seq_comp_node_opt.init_ready_event(comp_seq->extra_info, *opr_seq);

        if (options().allocate_static_mem_after_graph_compile)
            var_node_mem_manager().alloc_var_node_mem_static();
    }
    MGB_FINALLY({ var_node_mem_manager().on_graph_compile_finished(); });

    event().signal_inplace<event::CompSeqOrderDetermined>(this, comp_seq.get());

    if (options().comp_node_seq_record_level > 1) {
        mgb_assert(options().comp_node_seq_record_level <= 2,
                   "invalid comp_node_seq_record_level: %u",
                   options().comp_node_seq_record_level);
        mgb_assert(!options().fake_next_exec &&
                           !options().var_sanity_check_first_run,
                   "both fake_next_exec and var_sanity_check_first_run "
                   "must be false when comp_node_seq_record_level is 2");
        return comp_seq->as_recorded_seq();
    }
    return comp_seq;
}

VarNodeArray ComputingGraphImpl::get_dest_vars_from_out_spec(
        const OutputSpec& spec, SpecialOprStat& sopr_stat) {
    SymbolVarArray sym_vars;
    for (auto&& i : spec) {
        sym_vars.push_back(i.first);
    }
    return to_var_node_array(
            get_dest_vars_with_extra_deps(sym_vars, &sopr_stat));
}

const ComputingGraph::VarReceiverInfo&
ComputingGraphImpl::var_receiver_in_current_comp_seq(const VarNode* var) const {
    static VarReceiverInfo empty;
    if (auto ret = components().eager_eval_manager.var_receiver_info(var)) {
        return *ret;
    }
    if (!m_current_comp_seq)
        return empty;
    auto cseq = static_cast<ComputingSequence*>(m_current_comp_seq);
    auto iter = cseq->extra_info.var2recvinfo.find(var);
    if (iter == cseq->extra_info.var2recvinfo.end())
        return empty;
    return iter->second;
}

VarNode* ComputingGraphImpl::find_var_by_id(size_t id) const {
    for (auto&& i : m_opr_refkeeper) {
        for (auto j : i->output()) {
            if (j->id() == id)
                return j;
        }
    }
    for (auto&& i : m_subgraphs) {
        auto sub = i->find_var_by_id(id);
        if (sub)
            return sub;
    }
    return nullptr;
}

#if MGB_ENABLE_SUBLINEAR
SeqModifierForSublinearMemory&
ComputingGraphImpl::seq_modifier_for_sublinear_memory() {
    return components().seq_modifier_for_sublinear_memory;
}
#endif

void ComputingGraphImpl::share_device_memory_with(ComputingGraph& other) {
    mgb_assert(
            !m_current_comp_seq,
            "share_device_memory_with must be called before compiling graph");
    auto&& oimpl = static_cast<ComputingGraphImpl&>(other);
    var_node_mem_manager().static_device_memory_manager(
            oimpl.var_node_mem_manager().static_device_memory_manager());
}

void ComputingGraphImpl::set_device_memory_allocator(
        std::shared_ptr<DeviceMemoryAllocator> allocator) {
    var_node_mem_manager().static_device_memory_manager()->set_allocator(
            std::move(allocator));
}

size_t ComputingGraphImpl::get_device_memory_size(CompNode cn) {
    return var_node_mem_manager().static_device_memory_manager()->get_size(cn);
}

size_t ComputingGraphImpl::clear_device_memory() {
#if !MGB_BUILD_SLIM_SERVING
    if (options().eager_evaluation) {
        for (auto& opr : m_opr_refkeeper) {
            if (!opr->same_type<mgb::opr::SharedDeviceTensor>() &&
                !opr->same_type<mgb::opr::ImmutableTensor>()) {
                for (auto& var : opr->output()) {
                    if (var->mem_plan().valid())
                        var->mem_plan().release_chunk();
                }
            }
        }
    }
#endif
    return var_node_mem_manager().clear_static_device_memory();
}

void ComputingGraphImpl::set_as_subgraph(ComputingGraph& par_graph) {
    m_parent_graph = static_cast<ComputingGraphImpl*>(&par_graph);
    m_parent_graph->m_subgraphs.emplace_back(this);
    m_node_id_counter = m_parent_graph->m_node_id_counter;
    options().var_sanity_check_first_run =
            par_graph.options().var_sanity_check_first_run;
    par_graph.event().signal_inplace<event::SubgraphAssociated>(&par_graph,
                                                                this);
}

void ComputingGraphImpl::record_async_error(
        std::unique_ptr<MegBrainError> async_exc) {
    mgb_assert(m_current_comp_seq);
    static_cast<ComputingSequence*>(m_current_comp_seq)
            ->set_async_error(std::move(async_exc));
}

const CompSeqExtraInfo& ComputingGraphImpl::current_comp_seq_extra_info() {
    if (auto ret = eager_eval_manager().comp_seq_extra_info()) {
        return *ret;
    }
    mgb_assert(m_current_comp_seq);
    return static_cast<ComputingSequence*>(m_current_comp_seq)->extra_info;
}

GraphExecutable::ExecEnv* ComputingGraphImpl::current_exec_env() {
    if (auto ret = eager_eval_manager().exec_env()) {
        return ret;
    }
    if (m_current_comp_seq) {
        return &static_cast<ComputingSequence*>(m_current_comp_seq)->exec_env();
    }
    return nullptr;
}

Maybe<size_t> ComputingGraphImpl::opr_step_num_in_cur_comp_seq(
        OperatorNodeBase* opr) {
    mgb_assert(m_current_comp_seq && opr->owner_graph() == this);
    return static_cast<ComputingSequence*>(m_current_comp_seq)
            ->opr2stepnum(opr);
}

std::string ComputingGraphImpl::VarReceiverInfo::to_string() const {
    return mgb_ssprintf_log(
            "VarReceiverInfo("
            "nr_direct_comp_req=%zu dev_value=%zu, host_value=%zu, shape=%zu, "
            "allow_empty_value=%zu)",
            nr_direct_comp_req, dev_value, host_value, shape,
            allow_empty_value);
}

731
std::string ComputingGraphImpl::get_mem_allocation_info() const {
732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770
#if MGB_ENABLE_JSON
    auto make_var_json = [](VarNode* single_var) {
        auto &&cur_mem_plan = single_var->mem_plan();
        if (cur_mem_plan.valid())
            return json::Object::make({
                {"name", json::String::make(single_var->name())},
                {"memory", json::Number::make(cur_mem_plan.chunk().size())},
                {"dev_ptr", json::NumberInt::make(
                reinterpret_cast<size_t>(single_var->dev_tensor().raw_ptr()))}
            });
        else
            return json::Object::make({
                {"name", json::String::make(single_var->name())},
                {"memory", json::Null::make()},
                {"dev_ptr", json::Null::make()}
            });
    };

    auto objlist = json::Array::make();

    for(auto &opri: m_opr_refkeeper){
        auto cur_opr = opri.get();

        auto objptr = json::Object::make();
        auto &&objbody = *objptr;

        objbody["name"] = json::String::make(cur_opr->name());

        auto jvars = json::Array::make();
        for(auto &outputi: cur_opr->output()){
            jvars->add(make_var_json(outputi));
        }
        objbody["output"] = jvars;

        auto obj = json::Object::make({{std::to_string(cur_opr->id()), objptr}});

        objlist->add(obj);
    }

771
    return objlist->to_string();
772
#endif // MGB_ENABLE_JSON
773 774 775 776
    mgb_log_warn("mgb is not configured with MGB_ENABLE_JSON on,"
                 "get_mem_allocation_info returns null string");
    return std::string();
}
777

778
// vim: syntax=cpp.doxygen foldmethod=marker foldmarker=f{{{,f}}}