Lines Matching full:matmul

5     %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
20   %0 = linalg.matmul  ins(%arg0, %arg1: tensor<25x34xf32>, tensor<34x25xf32>)
37 // CHECK:           %[[MATMUL:.+]] = linalg.matmul ins(%[[XSIN19]], %[[IN2]] : tensor<9x34xf32>, tensor<34x25xf32>) outs(%[[XSOUT9]] : tensor<9x25xf32>) -> tensor<9x25xf32>
38 // CHECK:           %[[INS9:.+]] = tensor.insert_slice %[[MATMUL]] into %[[XSOUT18ARG]][%[[IDX]], 0] [9, 25] [1, 1] : tensor<9x25xf32> into tensor<18x25xf32>
46 // CHECK:         %[[R1:.+]] = linalg.matmul ins(%[[XS3]], %[[IN2]] : tensor<4x34xf32>, tensor<34x25xf32>) outs(%[[XS4]] : tensor<4x25xf32>) -> tensor<4x25xf32>
52 // CHECK:         %[[R2:.+]] = linalg.matmul ins(%[[XS8]], %[[IN2]] : tensor<2x34xf32>, tensor<34x25xf32>) outs(%[[XS9]] : tensor<2x25xf32>) -> tensor<2x25xf32>
56 // CHECK:         %[[R3:.+]] = linalg.matmul ins(%[[XS11]], %[[IN2]] : tensor<1x34xf32>, tensor<34x25xf32>) outs(%[[XS12]] : tensor<1x25xf32>) -> tensor<1x25xf32>
66     %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
81   %0 = linalg.matmul  ins(%arg0, %arg1: tensor<25x34xf32>, tensor<34x25xf32>)
98 // CHECK:           %[[MATMUL:.+]] = linalg.matmul ins(%[[XSIN19]], %[[IN2]] : tensor<9x34xf32>, tensor<34x25xf32>) outs(%[[XSOUT9]] : tensor<9x25xf32>) -> tensor<9x25xf32>
99 // CHECK:           %[[INS9:.+]] = tensor.insert_slice %[[MATMUL]] into %[[XSOUT18ARG]][%[[IDX]], 0] [9, 25] [1, 1] : tensor<9x25xf32> into tensor<18x25xf32>
107 // CHECK:         %[[R1:.+]] = linalg.matmul ins(%[[XS3]], %[[IN2]] : tensor<4x34xf32>, tensor<34x25xf32>) outs(%[[XS4]] : tensor<4x25xf32>) -> tensor<4x25xf32>
113 // CHECK:         %[[R2:.+]] = linalg.matmul ins(%[[XS8]], %[[IN2]] : tensor<2x34xf32>, tensor<34x25xf32>) outs(%[[XS9]] : tensor<2x25xf32>) -> tensor<2x25xf32>
117 // CHECK:         %[[R3:.+]] = linalg.matmul ins(%[[XS11]], %[[IN2]] : tensor<1x34xf32>, tensor<34x25xf32>) outs(%[[XS12]] : tensor<1x25xf32>) -> tensor<1x25xf32>
127     %0 = transform.structured.match ops{["linalg.matmul"]} in %arg1 : (!transform.any_op) -> !transform.any_op
142   %0 = linalg.matmul  ins(%arg0, %arg1: tensor<?x?xf32>, tensor<?x?xf32>)
163 // CHECK:       %[[MM:.+]] = linalg.matmul ins(%{{.*}}, %{{.*}} : tensor<?x?xf32>, tensor<?x?xf32>) outs(%{{.*}} : tensor<?x?xf32>) -> tensor<?x?xf32>
167 // CHECK:       %[[MM:.+]] = linalg.matmul ins(%{{.*}}, %{{.*}} : tensor<?x?xf32>, tensor<?x?xf32>) outs(%{{.*}} : tensor<?x?xf32>) -> tensor<?x?xf32>
171 // CHECK:       %[[MM:.+]] = linalg.matmul ins(%{{.*}}, %{{.*}} : tensor<?x?xf32>, tensor<?x?xf32>) outs(%{{.*}} : tensor<?x?xf32>) -> tensor<?x?xf32>
175 // CHECK:       %[[MM:.+]] = linalg.matmul ins(%{{.*}}, %{{.*}} : tensor<?x?xf32>, tensor<?x?xf32>) outs(%{{.*}} : tensor<?x?xf32>) -> tensor<?x?xf32>
179 // CHECK:       %[[MM:.+]] = linalg.matmul ins(%{{.*}}, %{{.*}} : tensor<1x?xf32>, tensor<?x?xf32>) outs(%{{.*}} : tensor<1x?xf32>) -> tensor<1x?xf32>