/*!
 * \file op/parallel.cc
 * \brief Define Parallel for operator
 */

#include "parallel.h"

#include <tvm/tir/op.h>

#include "../layout/utils.h"
#include "../target/utils.h"
#include "../transform/loop_partition.h"
#include "../transform/loop_vectorize.h"

namespace tvm {
namespace tl {

using namespace tir;

namespace attr {
/*! \brief Mark that how the loop is vectorized. */
constexpr const char *coalesced_width = "coalesced_width";
} // namespace attr

// ProveFragmentContains checks whether the threads that access elements of a
// smaller fragment (small_frag) are a subset of the threads that access
// elements of a larger fragment (large_frag) for any given loop index. This
// function ensures that if the small fragment's layout corresponds to the loop
// itself, accessing the large fragment's elements is valid. Additionally, if
// small is updated to large, the originally valid access remains valid. The
// proof is performed by:
//
// 1. Defining a variable `rep_small` to represent the replicate index of the
//    small fragment that is being checked.
// 2. Using the `small_frag_indices` and `rep_small` to derive the thread
// accessing
//    the element in the small fragment.
// 3. Using `large_frag_indices` to derive the physical index of the large
// fragment
//    along with the thread information, and then feeding these into the inverse
//    of the large fragment to obtain the logical index and replicate index.
// 4. Verifying the mapping by checking whether the computed thread using the
// inverse
//    layout corresponds to the original thread calculated for the small
//    fragment. If they don't match, this indicates that the inverse layout's
//    domain does not include the thread and thus the access is invalid.
bool ProveFragmentContains(Fragment small_frag, Fragment large_frag,
                           Array<PrimExpr> small_frag_indices,
                           Array<PrimExpr> large_frag_indices,
                           arith::Analyzer &analyzer_) {
  Var rep_small("__checking_frag_contains_rep");
  analyzer_.Bind(rep_small,
                 Range(IntImm(small_frag->ReplicateExtent()->dtype, 0),
                       small_frag->ReplicateExtent()),
                 true); // Bind the replicate extent of small_frag.
  // Derive thread for small_frag.
  auto thread = small_frag->ForwardThread(small_frag_indices, rep_small);

  // Get physical index and thread for large_frag.
  auto large_frag_physical_and_thread = large_frag->Forward(large_frag_indices);
  // Add small_frag's thread to the large fragment's thread info.
  large_frag_physical_and_thread.push_back(thread);
  // Get the inverse of the large fragment.
  auto inv_large_frag = large_frag->Inverse();
  // Compute logical index and replicate index using inverse layout.
  auto inv_large_frag_logical_and_rep =
      inv_large_frag->Forward(large_frag_physical_and_thread);

  // Extract replicate index from the result.
  auto inv_large_frag_rep =
      inv_large_frag_logical_and_rep[inv_large_frag_logical_and_rep.size() - 1];

  // Calculate thread based on the logical index and replicate index.
  auto check_thread =
      large_frag->ForwardThread(large_frag_indices, inv_large_frag_rep);

  // Simplify the difference between the threads.
  auto diff = analyzer_.Simplify(thread - check_thread);
  // If the difference is zero, the threads match and the access is valid.
  return is_zero(diff);
}

class IfBufferRemapLoopGenerator : public StmtExprMutator {
public:
  static For run(Stmt stmt, Map<Buffer, Buffer> buffer_remap,
                 Map<Buffer, Layout> layout_map) {
    IfBufferRemapLoopGenerator generator(buffer_remap, layout_map);
    return Downcast<For>(generator(std::move(stmt)));
  }

private:
  IfBufferRemapLoopGenerator(Map<Buffer, Buffer> buffer_remap,
                             Map<Buffer, Layout> layout_map)
      : buffer_remap_(buffer_remap), layout_map_(layout_map) {}

  PrimExpr VisitExpr_(const BufferLoadNode *op) final {
    auto load = Downcast<BufferLoad>(StmtExprMutator::VisitExpr_(op));

    if (buffer_remap_.count(load->buffer)) {
      auto new_indices = layout_map_[load->buffer]->Forward(load->indices);
      auto new_buffer = buffer_remap_[load->buffer];

      return BufferLoad(new_buffer, new_indices);
    }
    return load;
  }

  Stmt VisitStmt_(const BufferStoreNode *op) final {
    auto store = Downcast<BufferStore>(StmtExprMutator::VisitStmt_(op));
    if (buffer_remap_.count(store->buffer)) {
      auto new_indices = layout_map_[store->buffer]->Forward(store->indices);
      auto new_buffer = buffer_remap_[store->buffer];
      return BufferStore(new_buffer, store->value, new_indices);
    }
    return store;
  }

  Map<Buffer, Buffer> buffer_remap_;
  Map<Buffer, Layout> layout_map_;
};

void ParallelLoopNestVisitor::VisitStmt_(const ForNode *op) {
  ICHECK(op->kind == ForKind::kParallel);
  p->loop_vars_.push_back(
      IterVar(Range(op->min, op->extent), op->loop_var, IterVarType::kDataPar));
  p->analyzer_.Bind(op->loop_var, Range::FromMinExtent(op->min, op->extent));
  auto reducer_info_map =
      op->annotations.Get(attr::kReducerInfo)->as<Map<Var, ReducerInfo>>();
  if (reducer_info_map) {
    for (auto &&[buffer, info] : reducer_info_map.value())
      p->reducer_info_map_.Set(buffer, info);
  }
  StmtExprVisitor::VisitStmt_(op);
}

void ParallelLoopNestVisitor::VisitStmt_(const BufferStoreNode *op) {
  if (op->buffer.scope() == "local.fragment") {
    if (p->indice_map_.find(op->buffer) != p->indice_map_.end()) {
      ICHECK(StructuralEqual()(p->indice_map_.at(op->buffer), op->indices))
          << op->buffer << ": " << op->indices << " and "
          << p->indice_map_.at(op->buffer);
    } else {
      p->indice_map_.Set(op->buffer, op->indices);
    }
    p->buffer_is_write_.insert(op->buffer);
  }
  StmtExprVisitor::VisitStmt_(op);
}

/**
 * @brief Visit a BufferLoad node and record/validate index mapping for
 * fragment-local buffers.
 *
 * If the loaded buffer's scope is "local.fragment", this records the load
 * indices in the visitor's indice_map_ when seen for the first time. If an
 * entry already exists, the previously recorded indices are asserted
 * structurally equal to the current indices.
 *
 * This ensures all accesses to the same fragment-local buffer within the
 * parallel loop use a consistent index map. The function then continues
 * standard expression visitation.
 */
void ParallelLoopNestVisitor::VisitExpr_(const BufferLoadNode *op) {
  if (op->buffer.scope() == "local.fragment") {
    if (p->indice_map_.find(op->buffer) != p->indice_map_.end()) {
      ICHECK(StructuralEqual()(p->indice_map_.at(op->buffer), op->indices))
          << op->buffer << ": " << op->indices << " and "
          << p->indice_map_.at(op->buffer);
    } else {
      p->indice_map_.Set(op->buffer, op->indices);
    }
  }
  StmtExprVisitor::VisitExpr_(op);
}

/**
 * @brief Construct a ParallelOpNode from a parallel loop nest root.
 *
 * Initializes the node with the given For loop as the root of the parallel
 * operator and immediately runs the internal ParallelLoopNestVisitor to collect
 * loop and buffer access information from the nested body.
 *
 * @param root The root For node representing the parallel loop nest to be
 * analyzed.
 */
ParallelOpNode::ParallelOpNode(For root) : root_(root), V(this) {
  V.VisitStmt(root);
}

/**
 * @brief Create a copy of this ParallelOpNode wrapped as a TileOperator.
 *
 * Returns a new TileOperator that holds a deep copy of this ParallelOpNode.
 *
 * @return TileOperator A TileOperator owning a copy of this node.
 */
TileOperator ParallelOpNode::Clone() const {
  auto op = make_object<ParallelOpNode>(*this);
  return ParallelOp(op);
}

/**
 * @brief No-op lowering: return the stored root statement unchanged.
 *
 * This implementation does not perform any transformation and returns the
 * operator's original root For statement as-is.
 *
 * @param T Lowering arguments (unused).
 * @return Stmt The original root statement held by this ParallelOpNode.
 */
Stmt ParallelOpNode::Lower(const LowerArgs &T,
                           arith::Analyzer *analyzer) const {
  return root_;
}

/**
 * @brief Check whether a buffer is indexed by the loop's canonical (common)
 * iteration variables.
 *
 * Returns true if the recorded index mapping for `buffer` is structurally equal
 * to the sequence of loop iteration variables for this parallel op (i.e., the
 * buffer is accessed using the common access indices of the loop nest).
 *
 * @param buffer The buffer to check.
 * @return true if the buffer's index map equals the loop's iteration variables;
 * false otherwise.
 */
bool ParallelOpNode::IsCommonAccessIndice(const Buffer &buffer) const {
  auto common_indice = loop_vars_.Map([](const auto &iv) { return iv->var; });
  return StructuralEqual()(indice_map_[buffer], common_indice);
}

/**
 * @brief Infer buffer layouts for a Parallel operator based on the chosen
 * inference level.
 *
 * Attempts to compute a consistent LayoutMap for buffers accessed by a parallel
 * loop (root_) using explicit input layouts (T.layout_map), thread bounds
 * (T.thread_bounds), and optional buffer remapping/vectorization information in
 * T. Behavior depends on the supplied InferLevel:
 *  - kStrict: only accept pre-existing loop_layout_ (no inference).
 *  - kCommon: allow inference from explicit buffer fragments when available.
 *  - kFree: attempt more aggressive inference (derive loop partition from
 * read/write fragments, plan partitioning from vectorization/thread bounds, and
 * add predicates to constrain replication when necessary).
 *
 * This method may mutate the node's internal state (sets loop_layout_ when
 * inferred and registers predicates via AddPredicate) and consults analyzer_
 * for symbolic proofs.
 *
 * @param T Container of auxiliary inputs used for inference (buffer_remap,
 * layout_map, and thread_bounds). The function uses T.layout_map for source
 * fragments and T.thread_bounds to bind thread-range information in inferred
 * fragments.
 * @param level Controls inference aggressiveness (kStrict, kCommon, kFree).
 * @return LayoutMap A map of buffers to inferred Fragment layouts for buffers
 * that did not already have layouts in T.layout_map. Returns an empty map when
 *         no inference was performed.
 * @throws LayoutConflictException If a computed loop partition conflicts with
 * an existing buffer fragment (incompatible thread mappings).
 */
LayoutMap ParallelOpNode::InferLayout(const LayoutInferArgs &T,
                                      InferLevel level) const {
  if (loop_layout_.defined())
    return {};
  if (level == InferLevel::kStrict)
    return {};

  // Step 1: try to infer loop's partition from a source fragment
  Buffer source_buffer, read_source_buffer;
  for (const auto &[buffer, indices] : indice_map_) {
    if (T.layout_map.count(buffer)) {
      // skip reducers with rep=ALL
      if (auto info = reducer_info_map_.Get(buffer->data);
          info && info.value()->rep == ReducerRepType::ALL)
        continue;

      auto frag = T.layout_map[buffer].as<Fragment>().value();
      if (buffer_is_write_.count(buffer)) {
        source_buffer = buffer;
      } else {
        // Keep the buffer with largest number of indices
        // (which means the inference based on that buffer is more accurate)
        // as read_source_buffer to get more accurate layout
        if (!read_source_buffer.defined() ||
            indice_map_[buffer].size() >
                indice_map_[read_source_buffer].size()) {
          read_source_buffer = buffer;
        }
        // If the buffer is not replicated and shape is equal to the
        // source_buffer, use it as source_buffer because the layout inference
        // is more accurate
        if (is_one(frag->ReplicateExtent()) && !source_buffer.defined()) {
          source_buffer = buffer;
        }
      }
    }
  }
  auto compute_loop_layout_from_buffer = [&](const Buffer &buffer) {
    Fragment src_layout = T.layout_map[buffer].as<Fragment>().value();
    if (IsCommonAccessIndice(buffer)) {
      return src_layout;
    } else {
      Var rep;
      auto rep_iter = IterVar({0, src_layout->ReplicateExtent()}, rep,
                              IterVarType::kDataPar);
      PrimExpr loop_var_to_thread =
          src_layout->ForwardThread(indice_map_[buffer], rep);
      return Fragment(loop_vars_, {}, loop_var_to_thread, rep_iter)
          ->BindThreadRange(T.thread_bounds);
    }
  };
  if (source_buffer.defined()) {
    loop_layout_ = compute_loop_layout_from_buffer(source_buffer);
  } else if (level == InferLevel::kFree) {
    if (read_source_buffer.defined()) {
      loop_layout_ = compute_loop_layout_from_buffer(read_source_buffer);
      // // Loop don't need to be replicated.
      // if (!is_one(loop_layout_->ReplicateExtent()))
      //   loop_layout_ = loop_layout_->DeReplicate();

      // For free layout inference
      // If replication exists and buffer has cross-thread shared memory access,
      // add predicate
      bool has_cross_thread_access = false;
      PostOrderVisit(root_, [&](const ObjectRef &obj) {
        if (const auto *store = obj.as<BufferStoreNode>()) {
          // check if scope is shared or global
          if (store->buffer.scope() == "shared" ||
              store->buffer.scope() == "shared.dyn" ||
              store->buffer.scope() == "global") {
            has_cross_thread_access = true;
          }
        } else if (const auto *load = obj.as<BufferLoadNode>()) {
          // check if scope is shared or global
          if (load->buffer.scope() == "shared" ||
              load->buffer.scope() == "shared.dyn" ||
              load->buffer.scope() == "global") {
            has_cross_thread_access = true;
          }
        }
      });

      // check if loop body contains a "pure" buffer store (i.e., direct
      // assignment, not compound update)
      bool has_pure_buffer_store = false;
      PostOrderVisit(root_, [&](const ObjectRef &obj) {
        if (const auto *store = obj.as<BufferStoreNode>()) {
          // Check if the value is a direct load from another buffer (i.e., b[i]
          // = a[i])
          if (const auto *load = store->value.as<BufferLoadNode>()) {
            has_pure_buffer_store = true;
          }
        }
      });

      if (!is_one(loop_layout_->ReplicateExtent()) && has_cross_thread_access &&
          !has_pure_buffer_store) {
        auto inv = loop_layout_->Inverse();
        Array<PrimExpr> fwd;
        for (size_t i = 0; i < loop_layout_->OutputDim(); i++)
          fwd.push_back(0);
        fwd.push_back(InputPlaceholder(0) - T.thread_bounds->min);
        auto rep = inv->Forward(fwd).back();
        AddPredicate(EQ(rep, 0));
      }
    } else {
      // Vectorize Size must be aware of the buffer_remap
      // As the pass will do post processing to the layout
      auto maybe_remapped_root_ =
          IfBufferRemapLoopGenerator::run(root_, T.buffer_remap, T.layout_map);
      int vector_size = GetVectorizeSize(maybe_remapped_root_);

      PrimExpr loop_total_size = 1;
      for (Stmt l = root_; l.as<For>().has_value();
           l = l.as<For>().value()->body)
        loop_total_size = loop_total_size * l.as<For>().value()->extent;
      while (!analyzer_.CanProve(
                 floormod(loop_total_size,
                          T.thread_bounds->extent * vector_size) == 0) &&
             vector_size > 1)
        vector_size /= 2;

      // Check if coalesced_width is defined
      if (auto coalesced_width =
              root_->annotations.Get(tl::attr::coalesced_width)) {
        if (const auto *imm = coalesced_width->as<IntImmNode>()) {
          int expected = imm->value;
          // Verify that vector_size is divisible by expected
          if (vector_size % expected != 0) {
            LOG(FATAL) << "Vector size " << vector_size
                       << " is not divisible by coalesced width " << expected;
          }
          vector_size = expected;
        } else {
          LOG(FATAL) << "coalesced_width should be an IntImmNode.";
        }
      }
      loop_layout_ = PlanLoopPartition(root_, vector_size, T.thread_bounds);
    }
  } else {
    return {};
  }

  PrimExpr loop_thread_extent = loop_layout_->ThreadExtent();

  auto block_size = T.thread_bounds->extent;
  if (loop_layout_.defined()) {
    if (loop_layout_->ThreadRange().defined()) {
      auto thread_range = loop_layout_->ThreadRange();
      block_size = thread_range->extent;
      AddPredicate(GE(InputPlaceholder(0), thread_range->min));
      AddPredicate(
          LT(InputPlaceholder(0), thread_range->min + thread_range->extent));
    }
  }

  if (!analyzer_.CanProveEqual(loop_thread_extent, block_size)) {
    AddPredicate(
        LT(InputPlaceholder(0), loop_thread_extent + T.thread_bounds->min));
  }

  // Step 2: Check that the loop's partition can correctly align with all source
  // fragment, and infer layout only when it's not yet layout-ed
  LayoutMap results;
  for (const auto &[buffer, _] : indice_map_) {
    if (T.layout_map.count(buffer)) {
      auto fragment = T.layout_map[buffer].as<Fragment>().value();
      auto vars =
          loop_vars_.Map([](const IterVar &iv) { return PrimExpr(iv->var); });
      if (!ProveFragmentContains(loop_layout_, fragment, vars,
                                 indice_map_[buffer], analyzer_)) {
        std::ostringstream oss;
        oss << "Layout infer conflict between " << buffer << " and "
            << source_buffer << " in T.Parallel loop:" << std::endl
            << "    loop " << loop_layout_->DebugOutput() << std::endl
            << "    fragment " << fragment->DebugOutput() << std::endl;
        throw LayoutConflictException(oss.str());
      }
    } else {
      auto dst_layout =
          CompleteBufferFragment(buffer)->BindThreadRange(T.thread_bounds);
      results.Set(buffer, dst_layout);
    }
  }
  return results;
}

/**
 * @brief Retrieve the loop's thread predicate with the thread variable
 * substituted.
 *
 * If a predicate is set for this ParallelOpNode, returns a copy of that
 * predicate where the placeholder input (InputPlaceholder(0)) is replaced by
 * the provided thread_var. If no predicate is defined, returns an empty
 * Optional.
 *
 * @param thread_var The thread loop variable to substitute for the predicate's
 * input placeholder.
 * @return Optional<PrimExpr> The substituted predicate expression, or
 * std::nullopt if none is defined.
 */
Optional<PrimExpr> ParallelOpNode::GetPredicate(Var thread_var) const {
  if (predicate_.defined()) {
    return Substitute(predicate_.value(), {{InputPlaceholder(0), thread_var}});
  } else {
    return std::nullopt;
  }
}

/**
 * @brief Construct the complete fragment layout for a buffer within the
 * parallel loop.
 *
 * Given a buffer referenced inside the parallel loop, return a Fragment that
 * maps the buffer's logical indices to the loop's thread space and replication
 * extent.
 *
 * Detailed behavior:
 * - Precondition: a loop layout (loop_layout_) must be defined.
 * - If the buffer uses the common access indices of the loop, the loop's
 * fragment is returned directly.
 * - Otherwise, the function:
 *   - Computes the buffer's bijective index by appending the flattened
 * replication expression for unused iterators.
 *   - Inverts that bijection to obtain the replication extent of the buffer's
 * index space and combines it with the loop's replication extent to produce the
 *     destination replication extent.
 *   - Builds forward index placeholders for the buffer elements and maps them
 * through the inverted layout and the loop layout to derive the thread binding.
 *   - Returns a Fragment with the computed thread binding and combined
 * replication extent, with replicate variables condensed.
 *
 * @return Fragment The completed fragment describing thread binding and
 * replication extent for `buffer`.
 */
Fragment ParallelOpNode::CompleteBufferFragment(const Buffer &buffer) const {
  ICHECK(loop_layout_.defined());
  if (IsCommonAccessIndice(buffer)) {
    return loop_layout_;
  }
  PrimExpr rep_b = MakeFlattenedExpression(
      DivideUnusedIterators(indice_map_[buffer], loop_vars_, &analyzer_));
  auto bijective_indice = indice_map_[buffer];
  bijective_indice.push_back(rep_b);
  Layout ind_inv = Layout(loop_vars_, bijective_indice)->Inverse();
  PrimExpr indice_rep_extent =
      ind_inv->InputShape().back(); // this is the size of rep_b
  PrimExpr loop_rep_extent = loop_layout_->ReplicateExtent();
  PrimExpr dest_buffer_rep_extent = indice_rep_extent * loop_rep_extent;
  Array<PrimExpr> fwd;
  for (size_t i = 0; i < buffer->shape.size(); i++) {
    fwd.push_back(InputPlaceholder(i));
  }
  fwd.push_back(FloorMod(ReplicationPlaceholder(), indice_rep_extent));
  PrimExpr thd_b = loop_layout_->ForwardThread(
      ind_inv->Forward(fwd),
      FloorDiv(ReplicationPlaceholder(), indice_rep_extent));
  return Fragment(buffer->shape, {}, thd_b, dest_buffer_rep_extent,
                  std::nullopt)
      ->CondenseReplicateVar();
}

} // namespace tl
} // namespace tvm