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torch-mlir/test/Dialect/Torch/decompose-complex-ops.mlir

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// 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<!torch.int>
// 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.int>, !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$cst_dim(
// CHECK-SAME: %[[T:.*]]: !torch.tensor<[2,3],f32>) -> !torch.tensor<[2,3],f32> {
// CHECK: %[[DTYPE:.*]] = torch.constant.none
// CHECK: %[[DIM:.*]] = torch.constant.int 1
// CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<[2,3],f32> -> !torch.tensor<[2,3],f32>
// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<!torch.int>
// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
// CHECK-SAME !torch.tensor<[2,3],f32>, !torch.list<!torch.int>, !torch.bool, !torch.none -> !torch.tensor<[2,1],f32>
// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[2,3],f32>, !torch.tensor<[2,1],f32> -> !torch.tensor<[2,3],f32>
// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[2,3],f32> to !torch.tensor<[2,3],f32>
// CHECK: return %[[RET]] : !torch.tensor<[2,3],f32>
func @torch.aten.softmax.int$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$dyn_shape(
// CHECK-SAME: %[[T:.*]]: !torch.tensor<[?,?],f32>) -> !torch.tensor<[?,?],f32> {
// CHECK: %[[DTYPE:.*]] = torch.constant.none
// CHECK: %[[DIM:.*]] = torch.constant.int 1
// CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<[?,?],f32> -> !torch.tensor<[?,?],f32>
// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<!torch.int>
// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
// CHECK-SAME: !torch.tensor<[?,?],f32>, !torch.list<!torch.int>, !torch.bool, !torch.none -> !torch.tensor<[?,1],f32>
// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[?,?],f32>, !torch.tensor<[?,1],f32> -> !torch.tensor<[?,?],f32>
// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[?,?],f32> to !torch.tensor<[?,?],f32>
// CHECK: return %[[RET]] : !torch.tensor<[?,?],f32>
func @torch.aten.softmax.int$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$unknown_shape(
// CHECK-SAME: %[[T:.*]]: !torch.tensor<*,f32>) -> !torch.tensor<*,f32> {
// CHECK: %[[DTYPE:.*]] = torch.constant.none
// CHECK: %[[DIM:.*]] = torch.constant.int 1
// CHECK: %[[EXP:.*]] = torch.aten.exp %[[T]] : !torch.tensor<*,f32> -> !torch.tensor<*,f32>
// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<!torch.int>
// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
// CHECK-SAME: !torch.tensor<*,f32>, !torch.list<!torch.int>, !torch.bool, !torch.none -> !torch.tensor<*,f32>
// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<*,f32>, !torch.tensor<*,f32> -> !torch.tensor<*,f32>
// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<*,f32> to !torch.tensor<*,f32>
// CHECK: return %[[RET]] : !torch.tensor<*,f32>
func @torch.aten.softmax.int$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<!torch.int> {
// 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<!torch.int>
// CHECK: return %[[SIZE]] : !torch.list<!torch.int>
func @torch.aten.size(%arg0: !torch.vtensor<[?,3],f32>) -> !torch.list<!torch.int> {
%0 = torch.aten.size %arg0 : !torch.vtensor<[?,3],f32> -> !torch.list<!torch.int>
return %0 : !torch.list<!torch.int>
}
// ----
// CHECK-LABEL: func @torch.aten.arange() -> !torch.vtensor<[?],si64> {
// CHECK: %[[CST5:.*]] = torch.constant.int 5
// CHECK: %[[CSTN:.*]] = torch.constant.none
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[CST1:.*]] = torch.constant.int 1
// CHECK: %[[RESULT:.*]] = torch.aten.arange.start_step %[[CST0]], %[[CST5]], %[[CST1]], %[[CSTN]], %[[CSTN]], %[[CSTN]], %[[CSTN]] :
// CHECK-SAME: !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
// CHECK: return %[[RESULT]] : !torch.vtensor<[?],si64>
func @torch.aten.arange() -> !torch.vtensor<[?],si64> {
%int5 = torch.constant.int 5
%none = torch.constant.none
%0 = torch.aten.arange %int5, %none, %none, %none, %none : !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
return %0 : !torch.vtensor<[?],si64>
}
// ----
// CHECK-LABEL: func @torch.aten.arange.start() -> !torch.vtensor<[?],si64> {
// CHECK: %[[CST10:.*]] = torch.constant.int 10
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[CSTN:.*]] = torch.constant.none
// CHECK: %[[CST1:.*]] = torch.constant.int 1
// CHECK: %[[RESULT:.*]] = torch.aten.arange.start_step %[[CST0]], %[[CST10]], %[[CST1]], %[[CSTN]], %[[CSTN]], %[[CSTN]], %[[CSTN]] :
// CHECK-SAME: !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
// CHECK: return %[[RESULT]] : !torch.vtensor<[?],si64>
func @torch.aten.arange.start() -> !torch.vtensor<[?],si64> {
%int10 = torch.constant.int 10
%int0 = torch.constant.int 0
%none = torch.constant.none
%0 = torch.aten.arange.start %int0, %int10, %none, %none, %none, %none : !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
return %0 : !torch.vtensor<[?],si64>
}
// ----
// CHECK-LABEL: func @torch.aten.argmax(
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[1,?],si64> {
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[TRUE:.*]] = torch.constant.bool true
// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[INP]], %[[CST0]], %[[TRUE]] : !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,?],f32>, !torch.vtensor<[1,?],si64>
// CHECK: return %[[IND]] : !torch.vtensor<[1,?],si64>
func @torch.aten.argmax(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[1,?],si64> {
%int0 = torch.constant.int 0
%true = torch.constant.bool true
%0 = torch.aten.argmax %arg0, %int0, %true : !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,?],si64>
return %0 : !torch.vtensor<[1,?],si64>
}
// ----
// CHECK-LABEL: func @torch.aten.argmax$reduceall(
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[],si64> {
// CHECK: %[[NONE:.*]] = torch.constant.none
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
// CHECK: %[[CST0:.*]] = torch.constant.int 0
// CHECK: %[[CST1:.*]] = torch.constant.int 1
// CHECK: %[[FLATTEN:.*]] = torch.aten.flatten.using_ints %[[INP]], %[[CST0]], %[[CST1]] : !torch.vtensor<[?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?],f32>
// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[FLATTEN]], %[[CST0]], %[[FALSE]] : !torch.vtensor<[?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[],f32>, !torch.vtensor<[],si64>
// CHECK: return %[[IND]] : !torch.vtensor<[],si64>
func @torch.aten.argmax$reduceall(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[],si64> {
%none = torch.constant.none
%false = torch.constant.bool false
%0 = torch.aten.argmax %arg0, %none, %false : !torch.vtensor<[?,?],f32>, !torch.none, !torch.bool -> !torch.vtensor<[],si64>
return %0 : !torch.vtensor<[],si64>
}
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