// RUN: torch-mlir-opt -torch-decompose-complex-ops -split-input-file %s | FileCheck %s // CHECK-LABEL: func @matmul_no_decompose // CHECK: torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor func @matmul_no_decompose(%arg0: !torch.vtensor<[?,?,?,?,?],f32>, %arg1: !torch.vtensor<[?,?,?],f32>) -> !torch.tensor { %0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor return %0 : !torch.tensor } // ----- // CHECK-LABEL: func @matmul_decompose_2d // CHECK: torch.aten.mm %arg0, %arg1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.tensor func @matmul_decompose_2d(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) -> !torch.tensor { %0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.tensor return %0 : !torch.tensor } // ----- // CHECK-LABEL: func @matmul_decompose_3d( // CHECK: torch.aten.bmm %arg0, %arg1 : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor func @matmul_decompose_3d(%arg0: !torch.vtensor<[?,?,?],f32>, %arg1: !torch.vtensor<[?,?,?],f32>) -> !torch.tensor { %0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor return %0 : !torch.tensor } // ---- // CHECK-LABEL: func @torch.aten.softmax.int( // CHECK-SAME: %[[T:.*]]: !torch.tensor<[2,3],f32>, // CHECK-SAME: %[[DIM:.*]]: !torch.int) -> !torch.tensor<[2,3],f32> { // CHECK: %[[DTYPE:.*]] = torch.constant.none // CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<[2,3],f32> -> !torch.tensor<[2,3],f32> // CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list // CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true // CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none // CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] : // CHECK-SAME: !torch.tensor<[2,3],f32>, !torch.list, !torch.bool, !torch.none -> !torch.tensor<[?,?],f32> // CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[2,3],f32>, !torch.tensor<[?,?],f32> -> !torch.tensor<[2,3],f32> // CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[2,3],f32> to !torch.tensor<[2,3],f32> // CHECK: return %[[RET]] : !torch.tensor<[2,3],f32> func @torch.aten.softmax.int(%t: !torch.tensor<[2,3],f32>, %dim: !torch.int) -> !torch.tensor<[2,3],f32> { %dtype = torch.constant.none %ret = torch.aten.softmax.int %t, %dim, %dtype: !torch.tensor<[2,3],f32>, !torch.int, !torch.none -> !torch.tensor<[2,3],f32> return %ret : !torch.tensor<[2,3],f32> } // ---- // CHECK-LABEL: func @torch.aten.softmax.int$cst_dim( // CHECK-SAME: %[[T:.*]]: !torch.tensor<[2,3],f32>) -> !torch.tensor<[2,3],f32> { // CHECK: %[[DTYPE:.*]] = torch.constant.none // CHECK: %[[DIM:.*]] = torch.constant.int 1 // CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<[2,3],f32> -> !torch.tensor<[2,3],f32> // CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list // CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true // CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none // CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] : // CHECK-SAME !torch.tensor<[2,3],f32>, !torch.list, !torch.bool, !torch.none -> !torch.tensor<[2,1],f32> // CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[2,3],f32>, !torch.tensor<[2,1],f32> -> !torch.tensor<[2,3],f32> // CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[2,3],f32> to !torch.tensor<[2,3],f32> // CHECK: return %[[RET]] : !torch.tensor<[2,3],f32> func @torch.aten.softmax.int$cst_dim(%t: !torch.tensor<[2,3],f32>) -> !torch.tensor<[2,3],f32> { %none = torch.constant.none %dim = torch.constant.int 1 %ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<[2,3],f32>, !torch.int, !torch.none -> !torch.tensor<[2,3],f32> return %ret : !torch.tensor<[2,3],f32> } // ---- // CHECK-LABEL: func @torch.aten.softmax.int$dyn_shape( // CHECK-SAME: %[[T:.*]]: !torch.tensor<[?,?],f32>) -> !torch.tensor<[?,?],f32> { // CHECK: %[[DTYPE:.*]] = torch.constant.none // CHECK: %[[DIM:.*]] = torch.constant.int 1 // CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<[?,?],f32> -> !torch.tensor<[?,?],f32> // CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list // CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true // CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none // CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] : // CHECK-SAME: !torch.tensor<[?,?],f32>, !torch.list, !torch.bool, !torch.none -> !torch.tensor<[?,1],f32> // CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[?,?],f32>, !torch.tensor<[?,1],f32> -> !torch.tensor<[?,?],f32> // CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[?,?],f32> to !torch.tensor<[?,?],f32> // CHECK: return %[[RET]] : !torch.tensor<[?,?],f32> func @torch.aten.softmax.int$dyn_shape(%t: !torch.tensor<[?,?],f32>) -> !torch.tensor<[?,?],f32> { %none = torch.constant.none %dim = torch.constant.int 1 %ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<[?,?],f32>, !torch.int, !torch.none -> !torch.tensor<[?,?],f32> return %ret : !torch.tensor<[?,?],f32> } // ---- // CHECK-LABEL: func @torch.aten.softmax.int$unknown_shape( // CHECK-SAME: %[[T:.*]]: !torch.tensor<*,f32>) -> !torch.tensor<*,f32> { // CHECK: %[[DTYPE:.*]] = torch.constant.none // CHECK: %[[DIM:.*]] = torch.constant.int 1 // CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<*,f32> -> !torch.tensor<*,f32> // CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list // CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true // CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none // CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] : // CHECK-SAME: !torch.tensor<*,f32>, !torch.list, !torch.bool, !torch.none -> !torch.tensor<*,f32> // CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<*,f32>, !torch.tensor<*,f32> -> !torch.tensor<*,f32> // CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<*,f32> to !torch.tensor<*,f32> // CHECK: return %[[RET]] : !torch.tensor<*,f32> func @torch.aten.softmax.int$unknown_shape(%t: !torch.tensor<*,f32>) -> !torch.tensor<*,f32> { %none = torch.constant.none %dim = torch.constant.int 1 %ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<*,f32>, !torch.int, !torch.none -> !torch.tensor<*,f32> return %ret : !torch.tensor<*,f32> } // ---- // CHECK-LABEL: func @torch.aten.size( // CHECK-SAME: %[[T:.*]]: !torch.vtensor<[?,3],f32>) -> !torch.list { // CHECK: %[[CST0:.*]] = torch.constant.int 0 // CHECK: %[[DIM0:.*]] = torch.aten.size.int %[[T]], %[[CST0]] : !torch.vtensor<[?,3],f32>, !torch.int -> !torch.int // CHECK: %[[CST1:.*]] = torch.constant.int 1 // CHECK: %[[DIM1:.*]] = torch.aten.size.int %[[T]], %[[CST1]] : !torch.vtensor<[?,3],f32>, !torch.int -> !torch.int // CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[DIM0]], %[[DIM1]] : (!torch.int, !torch.int) -> !torch.list // CHECK: return %[[SIZE]] : !torch.list func @torch.aten.size(%arg0: !torch.vtensor<[?,3],f32>) -> !torch.list { %0 = torch.aten.size %arg0 : !torch.vtensor<[?,3],f32> -> !torch.list return %0 : !torch.list }