/*!
 * \file tl/op/gemm.cc
 *
 * Define gemm operator.
 */

#include "gemm.h"

#include "builtin.h"
#include <tvm/tir/builtin.h>
#include <tvm/tir/op.h>
#include <tvm/tir/op_attr_types.h>
#include <tvm/tir/transform.h>

#include "../target/utils.h"

namespace tvm {
namespace tl {

using namespace tir;

static std::vector<int> toPrimeFactors(int x) {
  int i = 2;
  std::vector<int> result;
  while (x > 1) {
    if (x % i == 0) {
      x /= i;
      result.push_back(i);
    } else {
      i++;
    }
  }
  return result;
}

Gemm::Gemm(Array<PrimExpr> args, BufferMap vmap) {
  ObjectPtr<GemmNode> node = make_object<GemmNode>();

  node->Aptr = args[0];
  node->Bptr = args[1];
  node->Cptr = args[2];
  node->A = vmap[GetVarFromAccessPtr(node->Aptr)];
  node->B = vmap[GetVarFromAccessPtr(node->Bptr)];
  node->C = vmap[GetVarFromAccessPtr(node->Cptr)];
  node->trans_A = args[3].as<Bool>().value();
  node->trans_B = args[4].as<Bool>().value();
  node->M = args[5].as<IntImm>().value()->value;
  node->N = args[6].as<IntImm>().value()->value;
  node->K = args[7].as<IntImm>().value()->value;
  node->policy =
      static_cast<GemmWarpPolicy>(args[8].as<IntImm>().value()->value);
  node->clear_accum = args[9].as<Bool>().value();
  node->stride_A = args[10].as<IntImm>().value()->value;
  node->stride_B = args[11].as<IntImm>().value()->value;
  node->offset_A = args[12].as<IntImm>().value()->value;
  node->offset_B = args[13].as<IntImm>().value()->value;
  if (args.size() > 14) {
    node->kPack = args[14].as<IntImm>().value()->value;
    if (node->kPack != 1 && node->kPack != 2) {
      ICHECK(false) << "kPack must be 1 or 2";
    }
  }
  if (args.size() > 15) {
    node->wg_wait = args[15].as<IntImm>().value()->value;
  }
  data_ = std::move(node);
}

TileOperator GemmNode::Clone() const {
  auto op = make_object<GemmNode>(*this);
  return Gemm(op);
}

GemmNode::GemmInst GemmNode::GetGemmInst(int block_size, Target target) const {
  int warp_size = TargetGetWarpSize(target);
  int num_warps = block_size / warp_size;
  bool allow_wgmma = TargetIsHopper(target) && (this->M >= 64) &&
                     (num_warps % 4 == 0) && CheckWGMMA();
  if (allow_wgmma) {
    return GemmInst::kWGMMA;
  } else if (TargetIsCDNA(target)) {
    return GemmInst::kMFMA;
  } else if (TargetIsCuda(target)) {
    return GemmInst::kMMA;
  } else {
    ICHECK(0) << "Unsupported target for gemm: " << target->str();
  }
}

/**
 * @brief Compute how warps are partitioned between the M and N GEMM dimensions.
 *
 * Determines the number of warps assigned to the M (rows) and N (columns)
 * dimensions for a block given the selected GEMM implementation and target.
 * The function enforces constraints required by the implementations (e.g.,
 * per-warp tile sizes) and adapts the partition according to the configured
 * GemmWarpPolicy (FullRow, FullCol, Square).
 *
 * @param block_size Total number of threads in the block (used to derive
 * num_warps).
 * @param gemm_inst The chosen GEMM implementation (e.g., kWGMMA, kMFMA, kMMA).
 * @param target Target device information (used for warp size and
 * target-specific rules).
 * @return std::pair<int, int> {m_warp, n_warp} where m_warp * n_warp ==
 * num_warps.
 *
 * Constraints and behavior:
 * - Each warp is assumed to cover 16 rows (M) and 8 columns (N). The function
 *   checks that M % 16 == 0 and N % 8 == 0.
 * - num_warps is computed as block_size / warp_size(target).
 * - For WGMMA (kWGMMA):
 *   - num_warps must be a multiple of 4 (warp-groups of 4).
 *   - m_warp is always a multiple of 4.
 *   - The warp partition respects the GemmWarpPolicy:
 *     - FullRow: maximize warps on M (in multiples of 4) while keeping
 * divisibility.
 *     - FullCol: maximize warps on N, but if N is not evenly divisible, move
 *       whole warp-groups to M to achieve feasibility.
 *     - Square: choose a multiple-of-4 m_warp that best balances per-warp work
 *       between M and N.
 * - For non-WGMMA implementations:
 *   - FullRow: favor allocating warps to M first; if M cannot use all warps,
 *     remaining warps are placed on N.
 *   - FullCol: favor allocating warps to N first; if N cannot use all warps,
 *     remaining warps are placed on M.
 *   - Square: search for the m/n split that best balances per-warp work given
 *     integer warp counts and the per-warp tile sizes.
 *
 * Error handling:
 * - The function performs internal checks (ICHECK) and will fail if required
 *   divisibility or policy conditions are not met (e.g., M/N tile divisibility,
 *   invalid policy, or WGMMA-specific warp-group requirements).
 */
std::pair<int, int> GemmNode::ComputeWarpPartition(int block_size,
                                                   GemmInst gemm_inst,
                                                   Target target) const {
  int num_warps = block_size / TargetGetWarpSize(target);
  int m_warp = 1, n_warp = 1;
  constexpr int kMPerWarp = 16; // Rows processed by a single warp
  constexpr int kNPerWarp = 8;  // Columns processed by a single warp

  ICHECK(this->M % kMPerWarp == 0)
      << "M must be divisible by " << kMPerWarp << ", but got " << this->M;
  ICHECK(this->N % kNPerWarp == 0)
      << "N must be divisible by " << kNPerWarp << ", but got " << this->N;
  if (gemm_inst == GemmInst::kWGMMA) {
    ICHECK(num_warps % 4 == 0) << "Warp-Group MMA requires 128×k threads.";

    constexpr int kGroup = 4; // Number of warps in a warp-group

    m_warp = kGroup; // Initially, only one warp-group on M dimension
    n_warp = num_warps / m_warp; // Rest all on N dimension

    if (this->policy == GemmWarpPolicy::kFullRow) {
      // Try to put as many warp-groups as possible on M dimension
      // (decreasing multiples of 4, ensuring divisibility by M)
      for (int cand = num_warps; cand >= kGroup; cand -= kGroup) {
        if (this->M % (cand * kMPerWarp) == 0) {
          m_warp = cand;
          n_warp = num_warps / m_warp;
          break;
        }
      }
    } else if (this->policy == GemmWarpPolicy::kFullCol) {
      // Try to use warps on N dimension; if N is not divisible, split excess
      // groups to M
      int cand_n = n_warp;                       // Initially assume all on N
      if (this->N % (cand_n * kNPerWarp) != 0) { // N direction division fails
        int max_n = this->N / kNPerWarp;
        // Find a feasible n_warp from max possible downwards, ensuring
        // num_warps/n_warp is multiple of 4
        for (int n = std::min(cand_n, max_n); n >= 1; --n) {
          if (num_warps % n == 0 && (num_warps / n) % kGroup == 0) {
            n_warp = n;
            m_warp = num_warps / n_warp;
            break;
          }
        }
      }
    } else if (this->policy == GemmWarpPolicy::kSquare) {
      // Exhaustive search, but m must be multiple of 4
      int max_m = this->M / kMPerWarp;
      int max_n = this->N / kNPerWarp;

      float ideal = this->N > 0 ? static_cast<float>(this->M) / this->N : 1.f;

      float best_score = std::numeric_limits<float>::max();
      int best_m = kGroup, best_n = n_warp;

      for (int m = kGroup; m <= num_warps && m <= max_m; m += kGroup) {
        if (num_warps % m)
          continue;
        int n = num_warps / m;
        if (n > max_n)
          continue;

        float m_per_warp = static_cast<float>(this->M) / (m * kMPerWarp);
        float n_per_warp = static_cast<float>(this->N) / (n * kNPerWarp);
        float score = std::abs(m_per_warp / n_per_warp - ideal);

        if (score < best_score) {
          best_score = score;
          best_m = m;
          best_n = n;
        }
      }
      m_warp = best_m;
      n_warp = best_n;
    } else {
      ICHECK(0) << "Unknown GemmWarpPolicy";
    }

    ICHECK(m_warp * n_warp == num_warps)
        << "m_warp * n_warp must equal num_warps";
    return {m_warp, n_warp};
  }

  if (this->policy == GemmWarpPolicy::kFullRow) {
    // Try to partition M first
    m_warp = num_warps;
    n_warp = 1;

    // If M cannot be evenly divided by m_warp*16, try to split remaining warps
    // to N
    if (this->M % (m_warp * kMPerWarp) != 0) {
      // Calculate how many warps we can use for M
      int max_m_warps = this->M / kMPerWarp;
      m_warp = max_m_warps;
      // Use remaining warps for N
      n_warp = num_warps / m_warp;
      if (n_warp == 0)
        n_warp = 1;
    }
  } else if (this->policy == GemmWarpPolicy::kFullCol) {
    // Try to partition N first
    m_warp = 1;
    n_warp = num_warps;

    // If N cannot be evenly divided by n_warp*8, try to split remaining warps
    // to M
    if (this->N % (n_warp * kNPerWarp) != 0) {
      // Calculate how many warps we can use for N
      int max_n_warps = this->N / kNPerWarp;
      n_warp = max_n_warps;
      // Use remaining warps for M
      m_warp = num_warps / n_warp;
      if (m_warp == 0)
        m_warp = 1;
    }
  } else if (this->policy == GemmWarpPolicy::kSquare) {
    // First calculate the maximum possible warps for each dimension
    int max_m_warps =
        this->M / kMPerWarp; // Each warp needs at least 16 elements in M
    int max_n_warps =
        this->N / kNPerWarp; // Each warp needs at least 8 elements in N

    // Calculate the ideal ratio of M/N warps based on the matrix dimensions
    float ideal_ratio = 1.0f;
    if (this->N > 0) {
      ideal_ratio = static_cast<float>(this->M) / this->N;
    }

    // Start with a balanced initial guess
    m_warp = 1;
    n_warp = 1;

    // Try to find the best balanced partition
    int best_m = 1;
    int best_n = 1;
    float best_balance = std::numeric_limits<float>::max();

    // Try all possible combinations that satisfy the constraints
    for (int m = 1; m <= max_m_warps && m <= num_warps; m++) {
      int n = num_warps / m;

      // Calculate how balanced this partition is
      float m_per_warp = static_cast<float>(this->M) / (m * kMPerWarp);
      float n_per_warp = static_cast<float>(this->N) / (n * kNPerWarp);
      float balance = std::abs(m_per_warp / n_per_warp - ideal_ratio);

      if (balance < best_balance) {
        best_balance = balance;
        best_m = m;
        best_n = n;
      }
    }

    m_warp = best_m;
    n_warp = best_n;
  } else {
    ICHECK(0) << "Unknown GemmWarpPolicy";
  }
  return {m_warp, n_warp};
}

/**
 * @brief Checks whether WGMMA (warp-group MMA) can be used for this GEMM.
 *
 * Evaluates device-memory placement, data-type combinations, transpose flags,
 * and K divisibility constraints required for the Hopper WGMMA code path.
 *
 * The check returns true only when:
 * - B resides in shared memory ("shared" or "shared.dyn"); and
 * - (C, A, B) dtypes match one of the supported combinations below and K
 *   satisfies the required alignment; and
 * - for combinations that require specific orientations, A is not transposed
 *   and B is transposed.
 *
 * Supported combinations and constraints:
 * - C=float16:
 *   - A=float16, B=float16: K % 16 == 0
 *   - Various float8 mixes (e4m3/e5m2): require (!trans_A && trans_B) and K %
 * 32 == 0
 * - C=float32:
 *   - A=float16, B=float16: K % 16 == 0
 *   - A=bfloat16, B=bfloat16: K % 16 == 0
 *   - A=float32, B=float32: require (!trans_A && trans_B) and K % 8 == 0
 *   - Various float8 mixes: require (!trans_A && trans_B) and K % 32 == 0
 * - C=int32:
 *   - 8-bit integer combinations (Int8/UInt8): require (!trans_A && trans_B)
 * and K % 32 == 0
 *
 * @return true if WGMMA is supported for the current buffers, dtypes, and
 *         transpose/shape constraints; false otherwise.
 */
bool GemmNode::CheckWGMMA() const {
  if (B.scope() != "shared.dyn" && B.scope() != "shared") {
    return false;
  }

  if (C->dtype == DataType::Float(16)) {
    if (A->dtype == DataType::Float(16) && B->dtype == DataType::Float(16))
      return K % 16 == 0;
    else if (A->dtype.is_float8_e4m3() && B->dtype.is_float8_e4m3())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e4m3() && B->dtype.is_float8_e5m2())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e5m2() && B->dtype.is_float8_e4m3())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e5m2() && B->dtype.is_float8_e5m2())
      return (!trans_A) && trans_B && K % 32 == 0;
    else
      return false;
  } else if (C->dtype == DataType::Float(32)) {
    if (A->dtype == DataType::Float(16) && B->dtype == DataType::Float(16))
      return K % 16 == 0;
    else if (A->dtype == DataType::BFloat(16) &&
             B->dtype == DataType::BFloat(16))
      return K % 16 == 0;
    else if (A->dtype == DataType::Float(32) && B->dtype == DataType::Float(32))
      return (!trans_A) && trans_B && K % 8 == 0;
    else if (A->dtype.is_float8_e4m3() && B->dtype.is_float8_e4m3())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e4m3() && B->dtype.is_float8_e5m2())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e5m2() && B->dtype.is_float8_e4m3())
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype.is_float8_e5m2() && B->dtype.is_float8_e5m2())
      return (!trans_A) && trans_B && K % 32 == 0;
    else
      return false;
  } else if (C->dtype == DataType::Int(32)) {
    if (A->dtype == DataType::Int(8) && B->dtype == DataType::Int(8))
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype == DataType::Int(8) && B->dtype == DataType::UInt(8))
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype == DataType::UInt(8) && B->dtype == DataType::Int(8))
      return (!trans_A) && trans_B && K % 32 == 0;
    else if (A->dtype == DataType::UInt(8) && B->dtype == DataType::UInt(8))
      return (!trans_A) && trans_B && K % 32 == 0;
    else
      return false;
  } else {
    return false;
  }
}

static int GetArchInt(Target target) {
  int arch_int = 0;
  auto s = target->GetAttr<String>("arch");
  ICHECK(s.defined());
  const char *arch_str = s.value().c_str();
  if (arch_str[0] == 's' && arch_str[1] == 'm' && arch_str[2] == '_') {
    arch_int = atoi(&arch_str[3]);
  } else {
    arch_int = 0;
  }
  return arch_int;
}

Stmt GemmNode::Lower(const LowerArgs &T, arith::Analyzer *analyzer) const {
  auto block_size = *as_const_int(T.thread_bounds->extent);
  GemmInst gemm_inst = GetGemmInst(block_size, T.target);
  auto [warp_m, warp_n] = ComputeWarpPartition(block_size, gemm_inst, T.target);

  std::stringstream ss;
  std::string op_name = "tl::gemm_ss";
  if (A.scope() == "local.fragment") {
    ICHECK(B.scope() != "local.fragment");
    op_name = "tl::gemm_rs";
  } else if (B.scope() == "local.fragment") {
    op_name = "tl::gemm_sr";
  }
  ss << op_name << "<" << M << ", " << N << ", " << K << ", ";
  ss << warp_m << ", " << warp_n << ", ";
  ss << trans_A << ", " << trans_B;
  ss << ", " << clear_accum;
  if (TargetIsCuda(T.target) && (GetArchInt(T.target) >= 75)) {
    ss << ", " << stride_A << ", " << stride_B;
    ss << ", " << offset_A << ", " << offset_B;
  }
  if (TargetIsCDNA(T.target)) {
    // for cdna gemm, we need to specify kPack
    ss << ", " << kPack;
  } else if (TargetIsHopper(T.target)) {
    ss << ", " << (gemm_inst == GemmInst::kWGMMA ? "true" : "false");
  }
  if (wg_wait != 0) {
    ss << ", " << wg_wait;
  }
  ss << ">";

  auto new_call = Call(DataType::Handle(), tl::tl_gemm(),
                       Array<PrimExpr>{StringImm(ss.str()), Aptr, Bptr, Cptr});
  return Evaluate(new_call);
}

/**
 * @brief Infer memory/layout mappings for A, B, and C buffers for this GEMM op.
 *
 * Generates and returns a LayoutMap that binds buffer A, B, and C to
 * target- and architecture-specific fragment or shared-memory layouts based
 * on the current target, thread bounds, warp partitioning, data types, and
 * transpose flags. This performs target dispatch (Volta, Ampere/Turing/SM120,
 * Hopper, CDNA), selects the appropriate fragment or shared layout creators,
 * and binds fragment layouts to the thread range when buffers are local
 * fragments.
 *
 * Preconditions:
 * - C.scope() must be "local.fragment".
 *
 * Postconditions / side effects:
 * - Marks the operator's layout inference as completed (sets completed_ =
 * true).
 * - May abort via ICHECK on unsupported targets, invalid buffer scopes, or
 *   incompatible shape constraints.
 *
 * @param T Layout inference inputs (thread bounds and target).
 * @param level Inference level (unused for side effects but retained for API).
 * @return LayoutMap mapping each of A, B, and C to their inferred layouts.
 */
LayoutMap GemmNode::InferLayout(const LayoutInferArgs &T,
                                InferLevel level) const {
  if (completed_)
    return {};
  LayoutMap results;
  ICHECK(C.scope() == "local.fragment");
  auto thread_range = T.thread_bounds;
  auto block_size = *as_const_int(thread_range->extent);
  GemmInst gemm_inst = GetGemmInst(block_size, T.target);
  auto [warp_m, warp_n] = ComputeWarpPartition(block_size, gemm_inst, T.target);

  if (TargetIsVolta(T.target)) {
    auto fragment =
        makeGemmVoltaFragmentC(M, N, M / warp_m, N / warp_n, C->dtype.bits());
    results.Set(C, fragment->BindThreadRange(thread_range));
    if (A.scope() == "shared" || A.scope() == "shared.dyn") {
      int dim_A = A->shape.size();
      results.Set(A, makeGemmVoltaABLayout(*as_const_int(A->shape[dim_A - 2]),
                                           *as_const_int(A->shape[dim_A - 1]),
                                           true, trans_A ? 1 : 2));
    } else if (A.scope() == "local.fragment") {
      ICHECK(trans_A == false);
      auto fragment = makeGemmVoltaFragmentA(M, N, K, M / warp_m, N / warp_n);
      results.Set(A, fragment->BindThreadRange(thread_range));
    } else {
      ICHECK(0);
    }

    ICHECK(B.scope() == "shared" || B.scope() == "shared.dyn");
    int dim_B = B->shape.size();
    results.Set(B, makeGemmVoltaABLayout(*as_const_int(B->shape[dim_B - 2]),
                                         *as_const_int(B->shape[dim_B - 1]),
                                         false, trans_B ? 2 : 1));
  } else if (TargetIsAmpere(T.target) || TargetIsTuring(T.target) ||
             TargetIsSM120(T.target)) {
    auto fragment =
        makeGemmFragmentC(M, N, M / warp_m, N / warp_n, C->dtype.bits());
    results.Set(C, fragment->BindThreadRange(thread_range));

    if (A.scope() == "shared" || A.scope() == "shared.dyn") {
      int dim_A = A->shape.size();
      const int64_t mat_stride = *as_const_int(A->shape[dim_A - 2]);
      const int64_t mat_continuous = *as_const_int(A->shape[dim_A - 1]);
      results.Set(A,
                  makeGemmABLayout(mat_stride, mat_continuous, mat_continuous,
                                   A->dtype.bits(), trans_A ? 1 : 2));
    } else if (A.scope() == "local.fragment") {
      auto fragment = makeGemmFragmentA(M, N, K, M / warp_m, N / warp_n,
                                        A->dtype.bits(), trans_A);
      results.Set(A, fragment->BindThreadRange(thread_range));
    } else {
      ICHECK(0);
    }
    if (B.scope() == "shared" || B.scope() == "shared.dyn") {
      int dim_B = B->shape.size();
      const int64_t mat_stride = *as_const_int(B->shape[dim_B - 2]);
      const int64_t mat_continuous = *as_const_int(B->shape[dim_B - 1]);
      results.Set(B,
                  makeGemmABLayout(mat_stride, mat_continuous, mat_continuous,
                                   B->dtype.bits(), trans_B ? 2 : 1));
    } else if (B.scope() == "local.fragment") {
      auto fragment =
          makeGemmFragmentB(M, N, K, M / warp_m, N / warp_n, trans_B);
      results.Set(B, fragment->BindThreadRange(thread_range));
    } else {
      ICHECK(0);
    }
  } else if (TargetIsHopper(T.target)) {
    auto fragment =
        gemm_inst == GemmInst::kWGMMA
            ? makeGemmFragmentCHopper(M, N, M / warp_m, N / warp_n,
                                      C->dtype.bits())
            : makeGemmFragmentC(M, N, M / warp_m, N / warp_n, C->dtype.bits());
    results.Set(C, fragment->BindThreadRange(thread_range));
    if (A.scope() == "shared" || A.scope() == "shared.dyn") {
      int dim_A = A->shape.size();
      const int64_t mat_stride = *as_const_int(A->shape[dim_A - 2]);
      const int64_t mat_continuous = *as_const_int(A->shape[dim_A - 1]);
      const int64_t continuity =
          trans_A ? 4 * mat_continuous / warp_m : mat_continuous;
      auto ABLayout =
          gemm_inst == GemmInst::kWGMMA
              ? makeGemmABLayoutHopper(mat_stride, mat_continuous, continuity,
                                       A->dtype.bits(), trans_A ? 1 : 2)
              : makeGemmABLayout(mat_stride, mat_continuous, mat_continuous,
                                 A->dtype.bits(), trans_A ? 1 : 2);
      results.Set(A, ABLayout);
    } else {
      auto fragment = makeGemmFragmentA(M, N, K, M / warp_m, N / warp_n,
                                        A->dtype.bits(), trans_A);
      results.Set(A, fragment->BindThreadRange(thread_range));
    }
    if (B.scope() == "shared" || B.scope() == "shared.dyn") {
      int dim_B = B->shape.size();
      const int64_t mat_stride = *as_const_int(B->shape[dim_B - 2]);
      const int64_t mat_continuous = *as_const_int(B->shape[dim_B - 1]);
      const int64_t continuity =
          trans_B ? mat_continuous : mat_continuous / warp_n;
      auto ABLayout =
          gemm_inst == GemmInst::kWGMMA
              ? makeGemmABLayoutHopper(mat_stride, mat_continuous, continuity,
                                       B->dtype.bits(), trans_B ? 2 : 1)
              : makeGemmABLayout(mat_stride, mat_continuous, mat_continuous,
                                 B->dtype.bits(), trans_B ? 2 : 1);
      results.Set(B, ABLayout);
    } else {
      auto fragment =
          makeGemmFragmentB(M, N, K, M / warp_m, N / warp_n, trans_B);
      results.Set(B, fragment->BindThreadRange(thread_range));
    }
  } else if (TargetIsCDNA(T.target)) {
    auto fragment =
        makeGemmFragmentCCDNA(M, N, M / warp_m, N / warp_n, C->dtype.bits());
    results.Set(C, fragment->BindThreadRange(thread_range));

    if (A.scope() == "shared" || A.scope() == "shared.dyn") {
      int dim_A = A->shape.size();
      auto shared_layout = makeGemmABLayoutCDNA(
          *as_const_int(A->shape[dim_A - 2]),
          *as_const_int(A->shape[dim_A - 1]), A->dtype.bits(), kPack);
      results.Set(A, shared_layout);
    } else if (A.scope() == "local.fragment") {
      auto fragment = makeGemmFragmentACDNA(M, N, K, M / warp_m, N / warp_n,
                                            A->dtype.bits(), trans_A);
      results.Set(A, fragment->BindThreadRange(thread_range));
    } else {
      ICHECK(0);
    }
    if (B.scope() == "shared" || B.scope() == "shared.dyn") {
      int dim_B = B->shape.size();
      auto shared_layout = makeGemmABLayoutCDNA(
          *as_const_int(B->shape[dim_B - 2]),
          *as_const_int(B->shape[dim_B - 1]), B->dtype.bits(), kPack);

      results.Set(B, shared_layout);
    } else if (B.scope() == "local.fragment") {
      auto fragment =
          makeGemmFragmentB(M, N, K, M / warp_m, N / warp_n, trans_B);
      results.Set(B, fragment->BindThreadRange(thread_range));
    } else {
      ICHECK(0);
    }
  } else {
    ICHECK(0) << "Not supported " << T.target->str();
  }
  completed_ = true;
  return results;
}

TIR_REGISTER_TL_OP(Gemm, gemm)
    .set_num_inputs(5)
    .set_attr<TCallEffectKind>("TCallEffectKind",
                               Integer(CallEffectKind::kOpaque));

} // namespace tl
} // namespace tvm