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// RUN: mlir-opt %s -test-linalg-transform-patterns=test-tile-and-distribute-options -split-input-file | FileCheck %s
func.func @gemm1(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute1"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c: memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm1(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK: scf.for %[[ARG3:.*]] =
// CHECK: %[[OFFSETY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[OFFSETY_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[OFFSETY]], %[[ARG3]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG3]], %[[OFFSETX]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[OFFSETY_2]], %[[OFFSETX_2]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
func.func @gemm2(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute2"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c:memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm2(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK: %[[ITERY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[ITERX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[INBOUNDSY:.*]] = arith.cmpi slt, %[[ITERY]], %{{.*}}
// CHECK: %[[INBOUNDSX:.*]] = arith.cmpi slt, %[[ITERX]], %{{.*}}
// CHECK: %[[INBOUNDS:.*]] = arith.andi %[[INBOUNDSY]], %[[INBOUNDSX]]
// CHECK: scf.if %[[INBOUNDS]]
// CHECK: scf.for %[[ARG3:.*]] =
// CHECK: %[[OFFSETY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[OFFSETY_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[OFFSETY]], %[[ARG3]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG3]], %[[OFFSETX]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[OFFSETY_2]], %[[OFFSETX_2]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
func.func @gemm3(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute3"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c: memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm3(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[NBLOCKSY:.*]] = gpu.grid_dim y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK-DAG: %[[NBLOCKSX:.*]] = gpu.grid_dim x
// CHECK: %[[LBY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[STEPY:.*]] = affine.apply #[[MAP0]]()[%[[NBLOCKSY]]]
// CHECK: %[[LBX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[STEPX:.*]] = affine.apply #[[MAP0]]()[%[[NBLOCKSX]]]
// CHECK: scf.parallel (%[[ARG3:.*]], %[[ARG4:.*]]) = (%[[LBY]], %[[LBX]]) to (%{{.*}}, %{{.*}}) step (%[[STEPY]], %[[STEPX]])
// CHECK: scf.for %[[ARG5:.*]] =
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[ARG3]], %[[ARG5]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG5]], %[[ARG4]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[ARG3]], %[[ARG4]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
func.func @gemm4(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute4"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c: memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm4(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK: %[[LBX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[INBOUNDS:.*]] = arith.cmpi slt, %[[LBX]], %{{.*}}
// CHECK: scf.if %[[INBOUNDS]]
// CHECK: scf.for %[[ARG3:.*]] =
// CHECK: %[[OFFSETY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[OFFSETY_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETX_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[OFFSETY]], %[[ARG3]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG3]], %[[OFFSETX]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[OFFSETY_2]], %[[OFFSETX_2]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
func.func @gemm5(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute5"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c: memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm5(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK-DAG: %[[NBLOCKSX:.*]] = gpu.grid_dim x
// CHECK: %[[LBY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[LBX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[STEPX:.*]] = affine.apply #[[MAP0]]()[%[[NBLOCKSX]]]
// CHECK: %[[INBOUNDS:.*]] = arith.cmpi slt, %[[LBY]], %{{.*}}
// CHECK: scf.if %[[INBOUNDS]]
// CHECK: scf.parallel (%[[ARG3:.*]]) = (%[[LBX]]) to (%{{.*}}) step (%[[STEPX]])
// CHECK: scf.for %[[ARG4:.*]] =
// CHECK: %[[OFFSETY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[OFFSETY_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[OFFSETY]], %[[ARG4]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG4]], %[[ARG3]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[OFFSETY_2]], %[[ARG3]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
func.func @gemm6(%a : memref<?x?xf32>, %b : memref<?x?xf32>, %c : memref<?x?xf32>)
{
linalg.matmul {__internal_linalg_transform__ = "distribute6"}
ins(%a, %b: memref<?x?xf32>, memref<?x?xf32>)
outs(%c: memref<?x?xf32>)
return
}
// CHECK-DAG: #[[MAP0:.*]] = affine_map<()[s0] -> (s0 * 8)>
// CHECK: func @gemm6(
// CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]*]]: memref<?x?xf32>
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[NBLOCKSY:.*]] = gpu.grid_dim y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK: %[[LBY:.*]] = affine.apply #[[MAP0]]()[%[[BIDY]]]
// CHECK: %[[STEPY:.*]] = affine.apply #[[MAP0]]()[%[[NBLOCKSY]]]
// CHECK: scf.parallel (%[[ARG3:.*]]) = (%[[LBY]]) to (%{{.*}}) step (%[[STEPY]])
// CHECK: scf.for %[[ARG4:.*]] =
// CHECK: %[[OFFSETX:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[OFFSETX_2:.*]] = affine.apply #[[MAP0]]()[%[[BIDX]]]
// CHECK: %[[SV1:.*]] = memref.subview %[[ARG0]][%[[ARG3]], %[[ARG4]]]
// CHECK: %[[SV2:.*]] = memref.subview %[[ARG1]][%[[ARG4]], %[[OFFSETX]]]
// CHECK: %[[SV3:.*]] = memref.subview %[[ARG2]][%[[ARG3]], %[[OFFSETX_2]]]
// CHECK: linalg.matmul ins(%[[SV1]], %[[SV2]]{{.*}} outs(%[[SV3]]
// -----
// CHECK: #[[MULMAP:.+]] = affine_map<()[s0, s1] -> (s0 * s1)>
// CHECK: #[[ADDMAP:.+]] = affine_map<()[s0, s1] -> (s0 + s1)>
// CHECK: func @matmul_tensors(
// CHECK-SAME: %[[TA:[0-9a-z]+]]: tensor<?x?xf32>
// CHECK-SAME: %[[TB:[0-9a-z]+]]: tensor<?x?xf32>
// CHECK-SAME: %[[TC:[0-9a-z]+]]: tensor<?x?xf32>) -> tensor<?x?xf32> {
func.func @matmul_tensors(
%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, %arg2: tensor<?x?xf32>)
-> tensor<?x?xf32> {
// CHECK-DAG: %[[C8:.*]] = arith.constant 8 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[BIDY:.*]] = gpu.block_id y
// CHECK-DAG: %[[NBLOCKSY:.*]] = gpu.grid_dim y
// CHECK-DAG: %[[BIDX:.*]] = gpu.block_id x
// CHECK-DAG: %[[NBLOCKSX:.*]] = gpu.grid_dim x
// CHECK: %[[MUL:.+]] = affine.apply #[[MULMAP]]()[%[[BIDY]], %[[C8]]]
// CHECK: %[[LBY:.+]] = affine.apply #[[ADDMAP]]()[%[[MUL]], %[[C0]]]
// CHECK: %[[STEPY:.+]] = affine.apply #[[MULMAP]]()[%[[NBLOCKSY]], %[[C8]]]
// CHECK: %[[TD0:.*]] = scf.for {{.*}} to {{.*}} step {{.*}} iter_args(%[[TC0:.*]] = %[[TC]]) -> (tensor<?x?xf32>) {
// CHECK: %[[MUL:.+]] = affine.apply #[[MULMAP]]()[%[[BIDX]], %[[C8]]]
// CHECK: %[[LBX:.+]] = affine.apply #[[ADDMAP]]()[%[[MUL]], %[[C0]]]
// CHECK: %[[STEPX:.+]] = affine.apply #[[MULMAP]]()[%[[NBLOCKSX]], %[[C8]]]
// CHECK: %[[TD1:.*]] = scf.for {{.*}} to {{.*}} step {{.*}} iter_args(%[[TC1:.*]] = %[[TC0]]) -> (tensor<?x?xf32>) {
// CHECK: %[[TD2:.*]] = scf.for {{.*}} to {{.*}} step {{.*}} iter_args(%[[TC2:.*]] = %[[TC1]]) -> (tensor<?x?xf32>) {
// CHECK: %[[sTA:.*]] = tensor.extract_slice %[[TA]][{{.*}}] : tensor<?x?xf32> to tensor<?x?xf32>
// CHECK: %[[sTB:.*]] = tensor.extract_slice %[[TB]][{{.*}}] : tensor<?x?xf32> to tensor<?x?xf32>
// CHECK: %[[sTC:.*]] = tensor.extract_slice %[[TC2]][{{.*}}] : tensor<?x?xf32> to tensor<?x?xf32>
// CHECK: %[[sTD:.*]] = linalg.matmul ins(%[[sTA]], %[[sTB]] : tensor<?x?xf32>, tensor<?x?xf32>)
// CHECK-SAME: outs(%[[sTC]] : tensor<?x?xf32>) -> tensor<?x?xf32>
// CHECK: %[[TD:.*]] = tensor.insert_slice %[[sTD]] into %[[TC2]][{{.*}}] : tensor<?x?xf32> into tensor<?x?xf32>
// CHECK: scf.yield %[[TD]] : tensor<?x?xf32>
// CHECK: scf.yield %[[TD2]] : tensor<?x?xf32>
// CHECK: scf.yield %[[TD1]] : tensor<?x?xf32>
%0 = linalg.matmul {__internal_linalg_transform__ = "tensors_distribute1"}
ins(%arg0, %arg1: tensor<?x?xf32>, tensor<?x?xf32>)
outs(%arg2: tensor<?x?xf32>)
-> tensor<?x?xf32>
// CHECK: return %[[TD0]] : tensor<?x?xf32>
return %0 : tensor<?x?xf32>
}
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