Lines Matching full:matmul

5 // The list of split points is consumed by splitOp to split the linalg.matmul op
6 // along dimension 1 to produce as many split-up linalg.matmul ops.
9     %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
19   %0 = linalg.matmul  ins(%arg0, %arg1: tensor<25x34xf32>, tensor<34x25xf32>)
30 // CHECK       %[[MM0:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE]] : tensor<25x34xf32>, tensor<34x18xf32>) outs(%[[SLICE0]] : tensor<25x18xf32>) -> tensor<25x18xf32>
36 // CHECK       %[[MM1:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE3]] : tensor<25x34xf32>, tensor<34x4xf32>) outs(%[[SLICE4]] : tensor<25x4xf32>) -> tensor<25x4xf32>
42 // CHECK       %[[MM2:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE7]] : tensor<25x34xf32>, tensor<34x2xf32>) outs(%[[SLICE8]] : tensor<25x2xf32>) -> tensor<25x2xf32>
46 // CHECK       %[[MM3:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE9]] : tensor<25x34xf32>, tensor<34x1xf32>) outs(%[[SLICE10]] : tensor<25x1xf32>) -> tensor<25x1xf32>
59     %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
69   %0 = linalg.matmul  ins(%arg0, %arg1: tensor<25x34xf32>, tensor<34x25xf32>)
80 // CHECK       %[[MM0:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE]] : tensor<25x34xf32>, tensor<34x18xf32>) outs(%[[SLICE0]] : tensor<25x18xf32>) -> tensor<25x18xf32>
86 // CHECK       %[[MM1:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE3]] : tensor<25x34xf32>, tensor<34x4xf32>) outs(%[[SLICE4]] : tensor<25x4xf32>) -> tensor<25x4xf32>
92 // CHECK       %[[MM2:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE7]] : tensor<25x34xf32>, tensor<34x2xf32>) outs(%[[SLICE8]] : tensor<25x2xf32>) -> tensor<25x2xf32>
96 // CHECK       %[[MM3:.+]] = linalg.matmul ins(%[[IN1]], %[[SLICE9]] : tensor<25x34xf32>, tensor<34x1xf32>) outs(%[[SLICE10]] : tensor<25x1xf32>) -> tensor<25x1xf32>