mirror of https://github.com/llvm/torch-mlir
894 lines
66 KiB
MLIR
894 lines
66 KiB
MLIR
// RUN: torch-mlir-opt -torch-decompose-complex-ops -split-input-file %s | FileCheck %s
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// CHECK-LABEL: func @matmul_no_decompose
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// CHECK: torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor
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func @matmul_no_decompose(%arg0: !torch.vtensor<[?,?,?,?,?],f32>, %arg1: !torch.vtensor<[?,?,?],f32>) -> !torch.tensor {
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%0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor
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return %0 : !torch.tensor
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}
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// -----
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// CHECK-LABEL: func @matmul_decompose_2d
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// CHECK: torch.aten.mm %arg0, %arg1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.tensor
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func @matmul_decompose_2d(%arg0: !torch.vtensor<[?,?],f32>, %arg1: !torch.vtensor<[?,?],f32>) -> !torch.tensor {
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%0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.tensor
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return %0 : !torch.tensor
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}
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// -----
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// CHECK-LABEL: func @matmul_decompose_3d(
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// CHECK: torch.aten.bmm %arg0, %arg1 : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor
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func @matmul_decompose_3d(%arg0: !torch.vtensor<[?,?,?],f32>, %arg1: !torch.vtensor<[?,?,?],f32>) -> !torch.tensor {
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%0 = torch.aten.matmul %arg0, %arg1 : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.tensor
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return %0 : !torch.tensor
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}
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// -----
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// CHECK-LABEL: func @torch.aten.softmax.int(
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// CHECK-SAME: %[[T:.*]]: !torch.tensor<[2,3],f32>,
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// CHECK-SAME: %[[DIM:.*]]: !torch.int) -> !torch.tensor<[2,3],f32> {
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// CHECK: %[[DTYPE:.*]] = torch.constant.none
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// CHECK: %[[KEEP_DIM0:.*]] = torch.constant.bool true
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[T]], %[[DIM]], %[[KEEP_DIM0]] :
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// CHECK-SAME: !torch.tensor<[2,3],f32>, !torch.int, !torch.bool -> !torch.tensor<[?,?],f32>, !torch.tensor<[?,?],si64>
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// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
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// CHECK: %[[SUB:.*]] = torch.aten.sub.Tensor %[[T]], %[[VAL]], %[[FLOAT1]] : !torch.tensor<[2,3],f32>,
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// CHECK-SAME: !torch.tensor<[?,?],f32>, !torch.float -> !torch.tensor<[2,3],f32>
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// CHECK: %[[EXP:.*]] = torch.aten.exp %[[SUB]] : !torch.tensor<[2,3],f32> -> !torch.tensor<[2,3],f32>
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// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
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// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
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// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
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// CHECK-SAME: !torch.tensor<[2,3],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.tensor<[?,?],f32>
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// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[2,3],f32>, !torch.tensor<[?,?],f32> -> !torch.tensor<[2,3],f32>
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// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[2,3],f32> to !torch.tensor<[2,3],f32>
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// CHECK: return %[[RET]] : !torch.tensor<[2,3],f32>
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func @torch.aten.softmax.int(%t: !torch.tensor<[2,3],f32>, %dim: !torch.int) -> !torch.tensor<[2,3],f32> {
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%dtype = torch.constant.none
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%ret = torch.aten.softmax.int %t, %dim, %dtype: !torch.tensor<[2,3],f32>, !torch.int, !torch.none -> !torch.tensor<[2,3],f32>
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return %ret : !torch.tensor<[2,3],f32>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.softmax.int$cst_dim(
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// CHECK-SAME: %[[T:.*]]: !torch.tensor<[2,3],f32>) -> !torch.tensor<[2,3],f32> {
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// CHECK: %[[DTYPE:.*]] = torch.constant.none
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// CHECK: %[[DIM:.*]] = torch.constant.int 1
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// CHECK: %[[TRU:.*]] = torch.constant.bool true
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[T]], %[[DIM]], %[[TRU]] : !torch.tensor<[2,3],f32>, !torch.int, !torch.bool ->
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// CHECK-SAME: !torch.tensor<[2,1],f32>, !torch.tensor<[2,1],si64>
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// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
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// CHECK: %[[SUB:.*]] = torch.aten.sub.Tensor %[[T]], %[[VAL]], %[[FLOAT1]] : !torch.tensor<[2,3],f32>,
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// CHECK-SAME: !torch.tensor<[2,1],f32>, !torch.float -> !torch.tensor<[2,3],f32>
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// CHECK: %[[EXP:.*]] = torch.aten.exp %[[SUB]] : !torch.tensor<[2,3],f32> -> !torch.tensor<[2,3],f32>
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// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
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// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
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// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
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// CHECK-SAME !torch.tensor<[2,3],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.tensor<[2,1],f32>
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// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[2,3],f32>, !torch.tensor<[2,1],f32> -> !torch.tensor<[2,3],f32>
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// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[2,3],f32> to !torch.tensor<[2,3],f32>
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// CHECK: return %[[RET]] : !torch.tensor<[2,3],f32>
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func @torch.aten.softmax.int$cst_dim(%t: !torch.tensor<[2,3],f32>) -> !torch.tensor<[2,3],f32> {
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%none = torch.constant.none
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%dim = torch.constant.int 1
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%ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<[2,3],f32>, !torch.int, !torch.none -> !torch.tensor<[2,3],f32>
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return %ret : !torch.tensor<[2,3],f32>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.softmax.int$dyn_shape(
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// CHECK-SAME: %[[T:.*]]: !torch.tensor<[?,?],f32>) -> !torch.tensor<[?,?],f32> {
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// CHECK: %[[DTYPE:.*]] = torch.constant.none
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// CHECK: %[[DIM:.*]] = torch.constant.int 1
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// CHECK: %[[TRU:.*]] = torch.constant.bool true
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[T]], %[[DIM]], %[[TRU]] : !torch.tensor<[?,?],f32>, !torch.int, !torch.bool ->
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// CHECK-SAME: !torch.tensor<[?,1],f32>, !torch.tensor<[?,1],si64>
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// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
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// CHECK: %[[SUB:.*]] = torch.aten.sub.Tensor %[[T]], %[[VAL]], %[[FLOAT1]] : !torch.tensor<[?,?],f32>,
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// CHECK-SAME: !torch.tensor<[?,1],f32>, !torch.float -> !torch.tensor<[?,?],f32>
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// CHECK: %[[EXP:.*]] = torch.aten.exp %[[SUB]] : !torch.tensor<[?,?],f32> -> !torch.tensor<[?,?],f32>
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// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
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// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
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// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
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// CHECK-SAME: !torch.tensor<[?,?],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.tensor<[?,1],f32>
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// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<[?,?],f32>, !torch.tensor<[?,1],f32> -> !torch.tensor<[?,?],f32>
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// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<[?,?],f32> to !torch.tensor<[?,?],f32>
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// CHECK: return %[[RET]] : !torch.tensor<[?,?],f32>
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func @torch.aten.softmax.int$dyn_shape(%t: !torch.tensor<[?,?],f32>) -> !torch.tensor<[?,?],f32> {
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%none = torch.constant.none
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%dim = torch.constant.int 1
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%ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<[?,?],f32>, !torch.int, !torch.none -> !torch.tensor<[?,?],f32>
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return %ret : !torch.tensor<[?,?],f32>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.softmax.int$unknown_shape(
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// CHECK-SAME: %[[T:.*]]: !torch.tensor<*,f32>) -> !torch.tensor<*,f32> {
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// CHECK: %[[DTYPE:.*]] = torch.constant.none
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// CHECK: %[[DIM:.*]] = torch.constant.int 1
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// CHECK: %[[TRU:.*]] = torch.constant.bool true
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[T]], %[[DIM]], %[[TRU]] : !torch.tensor<*,f32>, !torch.int, !torch.bool
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// CHECK-SAME: -> !torch.tensor<*,f32>, !torch.tensor<*,si64>
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// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
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// CHECK: %[[SUB:.*]] = torch.aten.sub.Tensor %[[T]], %[[VAL]], %[[FLOAT1]] : !torch.tensor<*,f32>, !torch.tensor<*,f32>,
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// CHECK-SAME: !torch.float -> !torch.tensor<*,f32>
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// CHECK: %[[EXP:.*]] = torch.aten.exp %[[SUB]] : !torch.tensor<*,f32> -> !torch.tensor<*,f32>
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// CHECK: %[[DIM_LIST:.*]] = torch.prim.ListConstruct %[[DIM]] : (!torch.int) -> !torch.list<int>
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// CHECK: %[[KEEP_DIM:.*]] = torch.constant.bool true
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// CHECK: %[[SUM_DTYPE:.*]] = torch.constant.none
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// CHECK: %[[SUM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[DIM_LIST]], %[[KEEP_DIM]], %[[SUM_DTYPE]] :
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// CHECK-SAME: !torch.tensor<*,f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.tensor<*,f32>
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// CHECK: %[[SOFTMAX:.*]] = torch.aten.div.Tensor %[[EXP]], %[[SUM]] : !torch.tensor<*,f32>, !torch.tensor<*,f32> -> !torch.tensor<*,f32>
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// CHECK: %[[RET:.*]] = torch.tensor_static_info_cast %[[SOFTMAX]] : !torch.tensor<*,f32> to !torch.tensor<*,f32>
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// CHECK: return %[[RET]] : !torch.tensor<*,f32>
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func @torch.aten.softmax.int$unknown_shape(%t: !torch.tensor<*,f32>) -> !torch.tensor<*,f32> {
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%none = torch.constant.none
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%dim = torch.constant.int 1
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%ret = torch.aten.softmax.int %t, %dim, %none : !torch.tensor<*,f32>, !torch.int, !torch.none -> !torch.tensor<*,f32>
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return %ret : !torch.tensor<*,f32>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.size(
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// CHECK-SAME: %[[T:.*]]: !torch.vtensor<[?,3],f32>) -> !torch.list<int> {
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// CHECK: %[[CST0:.*]] = torch.constant.int 0
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// CHECK: %[[DIM0:.*]] = torch.aten.size.int %[[T]], %[[CST0]] : !torch.vtensor<[?,3],f32>, !torch.int -> !torch.int
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// CHECK: %[[CST1:.*]] = torch.constant.int 1
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// CHECK: %[[DIM1:.*]] = torch.aten.size.int %[[T]], %[[CST1]] : !torch.vtensor<[?,3],f32>, !torch.int -> !torch.int
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// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[DIM0]], %[[DIM1]] : (!torch.int, !torch.int) -> !torch.list<int>
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// CHECK: return %[[SIZE]] : !torch.list<int>
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func @torch.aten.size(%arg0: !torch.vtensor<[?,3],f32>) -> !torch.list<int> {
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%0 = torch.aten.size %arg0 : !torch.vtensor<[?,3],f32> -> !torch.list<int>
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return %0 : !torch.list<int>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.arange() -> !torch.vtensor<[?],si64> {
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// CHECK: %[[CST5:.*]] = torch.constant.int 5
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// CHECK: %[[CSTN:.*]] = torch.constant.none
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// CHECK: %[[CST0:.*]] = torch.constant.int 0
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// CHECK: %[[CST1:.*]] = torch.constant.int 1
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// CHECK: %[[RESULT:.*]] = torch.aten.arange.start_step %[[CST0]], %[[CST5]], %[[CST1]], %[[CSTN]], %[[CSTN]], %[[CSTN]], %[[CSTN]] :
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// CHECK-SAME: !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
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// CHECK: return %[[RESULT]] : !torch.vtensor<[?],si64>
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func @torch.aten.arange() -> !torch.vtensor<[?],si64> {
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%int5 = torch.constant.int 5
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%none = torch.constant.none
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%0 = torch.aten.arange %int5, %none, %none, %none, %none : !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
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return %0 : !torch.vtensor<[?],si64>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.arange.start() -> !torch.vtensor<[?],si64> {
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// CHECK: %[[CST10:.*]] = torch.constant.int 10
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// CHECK: %[[CST0:.*]] = torch.constant.int 0
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// CHECK: %[[CSTN:.*]] = torch.constant.none
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// CHECK: %[[CST1:.*]] = torch.constant.int 1
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// CHECK: %[[RESULT:.*]] = torch.aten.arange.start_step %[[CST0]], %[[CST10]], %[[CST1]], %[[CSTN]], %[[CSTN]], %[[CSTN]], %[[CSTN]] :
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// CHECK-SAME: !torch.int, !torch.int, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?],si64>
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// CHECK: return %[[RESULT]] : !torch.vtensor<[?],si64>
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func @torch.aten.arange.start() -> !torch.vtensor<[?],si64> {
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%int10 = torch.constant.int 10
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%int0 = torch.constant.int 0
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%none = torch.constant.none
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%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>
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return %0 : !torch.vtensor<[?],si64>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.argmax(
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// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[1,?],si64> {
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// CHECK: %[[CST0:.*]] = torch.constant.int 0
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// CHECK: %[[TRUE:.*]] = torch.constant.bool true
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[INP]], %[[CST0]], %[[TRUE]] :
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// CHECK-SAME: !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,?],f32>, !torch.vtensor<[1,?],si64>
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// CHECK: return %[[IND]] : !torch.vtensor<[1,?],si64>
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func @torch.aten.argmax(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[1,?],si64> {
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%int0 = torch.constant.int 0
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%true = torch.constant.bool true
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%0 = torch.aten.argmax %arg0, %int0, %true : !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,?],si64>
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return %0 : !torch.vtensor<[1,?],si64>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.argmax$reduceall(
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// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[],si64> {
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// CHECK: %[[NONE:.*]] = torch.constant.none
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// CHECK: %[[FALSE:.*]] = torch.constant.bool false
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// CHECK: %[[CST0:.*]] = torch.constant.int 0
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// CHECK: %[[CST1:.*]] = torch.constant.int 1
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// CHECK: %[[FLATTEN:.*]] = torch.aten.flatten.using_ints %[[INP]], %[[CST0]], %[[CST1]] :
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// CHECK-SAME: !torch.vtensor<[?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?],f32>
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// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[FLATTEN]], %[[CST0]], %[[FALSE]] :
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// CHECK-SAME: !torch.vtensor<[?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[],f32>, !torch.vtensor<[],si64>
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// CHECK: return %[[IND]] : !torch.vtensor<[],si64>
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func @torch.aten.argmax$reduceall(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[],si64> {
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%none = torch.constant.none
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%false = torch.constant.bool false
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%0 = torch.aten.argmax %arg0, %none, %false : !torch.vtensor<[?,?],f32>, !torch.none, !torch.bool -> !torch.vtensor<[],si64>
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return %0 : !torch.vtensor<[],si64>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.square(
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// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
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// CHECK: %[[SQUARE:.*]] = torch.aten.mul.Tensor %[[INPUT]], %[[INPUT]] :
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// CHECK-SAME: !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
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// CHECK: return %[[SQUARE]] : !torch.vtensor<[?,?,?],f32>
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func @torch.aten.square(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
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%0 = torch.aten.square %arg0 : !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
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return %0 : !torch.vtensor<[?,?,?],f32>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.var$unbiased(
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// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
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// CHECK: %[[UNBIASED:.*]] = torch.constant.bool true
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// CHECK: %[[DTYPE:.*]] = torch.constant.none
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// CHECK: %[[SUM:.*]] = torch.aten.sum %[[INPUT]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
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// CHECK: %[[NUM_ELEMENTS:.*]] = torch.aten.numel %[[INPUT]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
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// CHECK: %[[MEAN:.*]] = torch.aten.div.Scalar %[[SUM]], %[[NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[ALPHA:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB_MEAN:.*]] = torch.aten.sub.Tensor %[[INPUT]], %[[MEAN]], %[[ALPHA]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE:.*]] = torch.aten.mul.Tensor %[[SUB_MEAN]], %[[SUB_MEAN]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_SUM:.*]] = torch.aten.sum %[[SUB_MEAN_SQUARE]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_NUM_ELEMENTS:.*]] = torch.aten.numel %[[SUB_MEAN_SQUARE]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[CST1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[NUM_ELEMENTS_SUB1:.*]] = torch.aten.sub.int %[[SUB_MEAN_SQUARE_NUM_ELEMENTS]], %[[CST1]] : !torch.int, !torch.int -> !torch.int
|
|
// CHECK: %[[UNBIASED_VAR:.*]] = torch.aten.div.Scalar %[[SUB_MEAN_SQUARE_SUM]], %[[NUM_ELEMENTS_SUB1]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: return %[[UNBIASED_VAR]] : !torch.vtensor<[],f32>
|
|
func @torch.aten.var$unbiased(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
%true = torch.constant.bool true
|
|
%0 = torch.aten.var %arg0, %true: !torch.vtensor<[?,?,?],f32>, !torch.bool -> !torch.vtensor<[],f32>
|
|
return %0 : !torch.vtensor<[],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.var$biased(
|
|
// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
// CHECK: %[[UNBIASED:.*]] = torch.constant.bool false
|
|
// CHECK: %[[DTYPE:.*]] = torch.constant.none
|
|
// CHECK: %[[SUM:.*]] = torch.aten.sum %[[INPUT]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[NUM_ELEMENTS:.*]] = torch.aten.numel %[[INPUT]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[MEAN:.*]] = torch.aten.div.Scalar %[[SUM]], %[[NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[ALPHA:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB_MEAN:.*]] = torch.aten.sub.Tensor %[[INPUT]], %[[MEAN]], %[[ALPHA]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE:.*]] = torch.aten.mul.Tensor %[[SUB_MEAN]], %[[SUB_MEAN]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_SUM:.*]] = torch.aten.sum %[[SUB_MEAN_SQUARE]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_NUM_ELEMENTS:.*]] = torch.aten.numel %[[SUB_MEAN_SQUARE]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[BIASED_VAR:.*]] = torch.aten.div.Scalar %[[SUB_MEAN_SQUARE_SUM]], %[[SUB_MEAN_SQUARE_NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: return %[[BIASED_VAR]] : !torch.vtensor<[],f32>
|
|
func @torch.aten.var$biased(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
%false = torch.constant.bool false
|
|
%0 = torch.aten.var %arg0, %false: !torch.vtensor<[?,?,?],f32>, !torch.bool -> !torch.vtensor<[],f32>
|
|
return %0 : !torch.vtensor<[],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.std$unbiased(
|
|
// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
// CHECK: %[[UNBIASED:.*]] = torch.constant.bool true
|
|
// CHECK: %[[DTYPE:.*]] = torch.constant.none
|
|
// CHECK: %[[SUM:.*]] = torch.aten.sum %[[INPUT]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[NUM_ELEMENTS:.*]] = torch.aten.numel %[[INPUT]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[MEAN:.*]] = torch.aten.div.Scalar %[[SUM]], %[[NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[ALPHA:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB_MEAN:.*]] = torch.aten.sub.Tensor %[[INPUT]], %[[MEAN]], %[[ALPHA]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE:.*]] = torch.aten.mul.Tensor %[[SUB_MEAN]], %[[SUB_MEAN]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_SUM:.*]] = torch.aten.sum %[[SUB_MEAN_SQUARE]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_NUM_ELEMENTS:.*]] = torch.aten.numel %[[SUB_MEAN_SQUARE]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[CST1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[NUM_ELEMENTS_SUB1:.*]] = torch.aten.sub.int %[[SUB_MEAN_SQUARE_NUM_ELEMENTS]], %[[CST1]] : !torch.int, !torch.int -> !torch.int
|
|
// CHECK: %[[UNBIASED_VAR:.*]] = torch.aten.div.Scalar %[[SUB_MEAN_SQUARE_SUM]], %[[NUM_ELEMENTS_SUB1]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[UNBIASED_STD:.*]] = torch.aten.sqrt %[[UNBIASED_VAR]] : !torch.vtensor<[],f32> -> !torch.vtensor<[],f32>
|
|
// CHECK: return %[[UNBIASED_STD]] : !torch.vtensor<[],f32>
|
|
func @torch.aten.std$unbiased(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
%true = torch.constant.bool true
|
|
%0 = torch.aten.std %arg0, %true: !torch.vtensor<[?,?,?],f32>, !torch.bool -> !torch.vtensor<[],f32>
|
|
return %0 : !torch.vtensor<[],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.std$biased(
|
|
// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
// CHECK: %[[UNBIASED:.*]] = torch.constant.bool false
|
|
// CHECK: %[[DTYPE:.*]] = torch.constant.none
|
|
// CHECK: %[[SUM:.*]] = torch.aten.sum %[[INPUT]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[NUM_ELEMENTS:.*]] = torch.aten.numel %[[INPUT]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[MEAN:.*]] = torch.aten.div.Scalar %[[SUM]], %[[NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[ALPHA:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB_MEAN:.*]] = torch.aten.sub.Tensor %[[INPUT]], %[[MEAN]], %[[ALPHA]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE:.*]] = torch.aten.mul.Tensor %[[SUB_MEAN]], %[[SUB_MEAN]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_SUM:.*]] = torch.aten.sum %[[SUB_MEAN_SQUARE]], %[[DTYPE]] : !torch.vtensor<[?,?,?],f32>, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[SUB_MEAN_SQUARE_NUM_ELEMENTS:.*]] = torch.aten.numel %[[SUB_MEAN_SQUARE]] : !torch.vtensor<[?,?,?],f32> -> !torch.int
|
|
// CHECK: %[[BIASED_VAR:.*]] = torch.aten.div.Scalar %[[SUB_MEAN_SQUARE_SUM]], %[[SUB_MEAN_SQUARE_NUM_ELEMENTS]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[BIASED_STD:.*]] = torch.aten.sqrt %[[BIASED_VAR]] : !torch.vtensor<[],f32> -> !torch.vtensor<[],f32>
|
|
// CHECK: return %[[BIASED_STD]] : !torch.vtensor<[],f32>
|
|
func @torch.aten.std$biased(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[],f32> {
|
|
%false = torch.constant.bool false
|
|
%0 = torch.aten.std %arg0, %false: !torch.vtensor<[?,?,?],f32>, !torch.bool -> !torch.vtensor<[],f32>
|
|
return %0 : !torch.vtensor<[],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten._unsafe_view$static
|
|
// CHECK-SAME: (%[[ARG0:.*]]: !torch.vtensor<[1,512,32],f32>)
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct
|
|
// CHECK-NOT: torch.aten._unsafe_view
|
|
// CHECK-NEXT: %[[RES:.*]] = torch.aten.view %[[ARG0]], %[[LIST]]
|
|
// CHECK-NEXT: return
|
|
func @torch.aten._unsafe_view$static(%arg0: !torch.vtensor<[1,512,32],f32>) -> !torch.vtensor<[1,2,256,32],f32> {
|
|
%c1 = torch.constant.int 1
|
|
%c2 = torch.constant.int 2
|
|
%c256 = torch.constant.int 256
|
|
%c32 = torch.constant.int 32
|
|
%0 = torch.prim.ListConstruct %c1, %c2, %c256, %c32 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten._unsafe_view %arg0, %0 : !torch.vtensor<[1,512,32],f32>, !torch.list<int> -> !torch.vtensor<[1,2,256,32],f32>
|
|
return %1 : !torch.vtensor<[1,2,256,32],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten._reshape_alias$static
|
|
// CHECK-SAME: (%[[ARG0:.*]]: !torch.vtensor<[1],f32>)
|
|
// CHECK: %[[LIST1:.*]] = torch.prim.ListConstruct
|
|
// CHECK: %[[LIST2:.*]] = torch.prim.ListConstruct
|
|
// CHECK-NOT: torch.aten._reshape_alias
|
|
// CHECK-NEXT: %[[RES:.*]] = torch.aten.view %[[ARG0]], %[[LIST1]]
|
|
// CHECK-NEXT: return
|
|
func @torch.aten._reshape_alias$static(%arg0: !torch.vtensor<[1],f32>) -> !torch.vtensor<[12,32],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%int32 = torch.constant.int 32
|
|
%int12 = torch.constant.int 12
|
|
%0 = torch.prim.ListConstruct %int12, %int32 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.prim.ListConstruct %int32, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%2 = torch.aten._reshape_alias %arg0, %0, %1 : !torch.vtensor<[1],f32>, !torch.list<int>, !torch.list<int> -> !torch.vtensor<[12,32],f32>
|
|
return %2 : !torch.vtensor<[12,32],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten._unsafe_view$dynamic
|
|
// CHECK-SAME: (%[[ARG0:.*]]: !torch.vtensor<[?,?,?],f32>)
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct
|
|
// CHECK-NOT: torch.aten._unsafe_view
|
|
// CHECK-NEXT: %[[RES:.*]] = torch.aten.view %[[ARG0]], %[[LIST]]
|
|
// CHECK-NEXT: return
|
|
func @torch.aten._unsafe_view$dynamic(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[512,32],f32> {
|
|
%c256 = torch.constant.int 512
|
|
%c32 = torch.constant.int 32
|
|
%0 = torch.prim.ListConstruct %c256, %c32 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten._unsafe_view %arg0, %0 : !torch.vtensor<[?,?,?],f32>, !torch.list<int> -> !torch.vtensor<[512,32],f32>
|
|
return %1 : !torch.vtensor<[512,32],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten._log_softmax(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[TRUE:.*]] = torch.constant.bool true
|
|
// CHECK: %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[INP]], %[[INT0]], %[[TRUE]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[1,?,?],f32>, !torch.vtensor<[1,?,?],si64>
|
|
// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB:.*]] = torch.aten.sub.Tensor %[[INP]], %[[VAL]], %[[FLOAT1]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[1,?,?],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[EXP:.*]] = torch.aten.exp %[[SUB]] : !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[PRIM:.*]] = torch.prim.ListConstruct %[[INT0]] : (!torch.int) -> !torch.list<int>
|
|
// CHECK: %[[TRU:.*]] = torch.constant.bool true
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[SUM_DIM:.*]] = torch.aten.sum.dim_IntList %[[EXP]], %[[PRIM]], %[[TRU]], %[[NONE]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],f32>, !torch.list<int>, !torch.bool, !torch.none -> !torch.vtensor<[1,?,?],f32>
|
|
// CHECK: %[[LOG:.*]] = torch.aten.log %[[SUM_DIM]] : !torch.vtensor<[1,?,?],f32> -> !torch.vtensor<[1,?,?],f32>
|
|
// CHECK: %[[FLOAT_1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[SUB1:.*]] = torch.aten.sub.Tensor %[[SUB]], %[[LOG]], %[[FLOAT_1]] : !torch.vtensor<[?,?,?],f32>,
|
|
// CHECK-SAME: !torch.vtensor<[1,?,?],f32>, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: return %[[SUB1]] : !torch.vtensor<[?,?,?],f32>
|
|
func @torch.aten._log_softmax(%arg0: !torch.vtensor<[?,?,?],f32> loc(unknown)) -> !torch.vtensor<[?,?,?],f32> {
|
|
%int0 = torch.constant.int 0
|
|
%false = torch.constant.bool false
|
|
%0 = torch.aten._log_softmax %arg0, %int0, %false : !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.bernoulli
|
|
// CHECK-SAME: (%[[INP:.*]]: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT7:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_0:.*]] = torch.constant.none
|
|
// CHECK: %[[CON2FLOAT:.*]] = torch.aten.to.dtype %[[INP]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],f64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[NONE_1:.*]] = torch.constant.none
|
|
// CHECK: %[[NONE_2:.*]] = torch.constant.none
|
|
// CHECK: %[[FLOAT0:.*]] = torch.constant.float 0.000000e+00
|
|
// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[UNF:.*]] = torch.valsem.aten.uniform %[[CON2FLOAT]], %[[FLOAT0]], %[[FLOAT1]], %[[NONE_2]] : !torch.vtensor<[?,?,?],f64>, !torch.float, !torch.float, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CMP:.*]] = torch.aten.lt.Tensor %[[UNF]], %[[INP]] : !torch.vtensor<[?,?,?],f64>, !torch.vtensor<[?,?,?],f64> -> !torch.vtensor<[?,?,?],i1>
|
|
// CHECK: %[[INT7_2:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE_2:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_3:.*]] = torch.constant.none
|
|
// CHECK: %[[TODTYPE:.*]] = torch.aten.to.dtype %[[CMP]], %[[INT7_2]], %[[FALSE_2]], %[[FALSE_2]], %[[NONE_3]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CAST:.*]] = torch.tensor_static_info_cast %[[TODTYPE]] : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
// CHECK: return %[[CAST]] : !torch.vtensor
|
|
func @torch.aten.bernoulli(%arg0: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
%none = torch.constant.none
|
|
%0 = torch.aten.bernoulli %arg0, %none : !torch.vtensor<[?,?,?],f64>, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
%1 = torch.tensor_static_info_cast %0 : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
return %1 : !torch.vtensor
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.valsem.aten.bernoulli.float
|
|
// CHECK-SAME: (%[[INP:.*]]: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[PROB:.*]] = torch.constant.float 4.000000e-01
|
|
// CHECK: %[[PROB_TENSOR:.*]] = torch.prim.NumToTensor.Scalar %[[PROB]] : !torch.float -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[INT7:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_0:.*]] = torch.constant.none
|
|
// CHECK: %[[CON2FLOAT:.*]] = torch.aten.to.dtype %[[INP]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],f64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[NONE_1:.*]] = torch.constant.none
|
|
// CHECK: %[[NONE_2:.*]] = torch.constant.none
|
|
// CHECK: %[[FLOAT0:.*]] = torch.constant.float 0.000000e+00
|
|
// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[UNF:.*]] = torch.valsem.aten.uniform %[[CON2FLOAT]], %[[FLOAT0]], %[[FLOAT1]], %[[NONE_2]] : !torch.vtensor<[?,?,?],f64>, !torch.float, !torch.float, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CMP:.*]] = torch.aten.lt.Tensor %[[UNF]], %[[PROB_TENSOR]] : !torch.vtensor<[?,?,?],f64>, !torch.vtensor<[],f64> -> !torch.vtensor<[?,?,?],i1>
|
|
// CHECK: %[[INT7_2:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE_2:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_3:.*]] = torch.constant.none
|
|
// CHECK: %[[TODTYPE:.*]] = torch.aten.to.dtype %[[CMP]], %[[INT7_2]], %[[FALSE_2]], %[[FALSE_2]], %[[NONE_3]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CAST:.*]] = torch.tensor_static_info_cast %[[TODTYPE]] : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
// CHECK: return %[[CAST]] : !torch.vtensor
|
|
func @torch.valsem.aten.bernoulli.float(%arg0: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
%none = torch.constant.none
|
|
%prob = torch.constant.float 4.000000e-01
|
|
%0 = torch.valsem.aten.bernoulli.float %arg0, %prob, %none : !torch.vtensor<[?,?,?],f64>, !torch.float, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
%1 = torch.tensor_static_info_cast %0 : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
return %1 : !torch.vtensor
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.valsem.aten.bernoulli.Tensor(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?,?],f64>,
|
|
// CHECK-SAME: %[[PROB:.*]]: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT7:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_0:.*]] = torch.constant.none
|
|
// CHECK: %[[CON2FLOAT:.*]] = torch.aten.to.dtype %[[INP]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],f64>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[NONE_1:.*]] = torch.constant.none
|
|
// CHECK: %[[NONE_2:.*]] = torch.constant.none
|
|
// CHECK: %[[FLOAT0:.*]] = torch.constant.float 0.000000e+00
|
|
// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[UNF:.*]] = torch.valsem.aten.uniform %[[CON2FLOAT]], %[[FLOAT0]], %[[FLOAT1]], %[[NONE_2]] : !torch.vtensor<[?,?,?],f64>, !torch.float, !torch.float, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CMP:.*]] = torch.aten.lt.Tensor %[[UNF]], %[[PROB]] : !torch.vtensor<[?,?,?],f64>, !torch.vtensor<[?,?,?],f64> -> !torch.vtensor<[?,?,?],i1>
|
|
// CHECK: %[[INT7_2:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE_2:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_3:.*]] = torch.constant.none
|
|
// CHECK: %[[TODTYPE:.*]] = torch.aten.to.dtype %[[CMP]], %[[INT7_2]], %[[FALSE_2]], %[[FALSE_2]], %[[NONE_3]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?,?],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: %[[CAST:.*]] = torch.tensor_static_info_cast %[[TODTYPE]] : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
// CHECK: return %[[CAST]] : !torch.vtensor
|
|
func @torch.valsem.aten.bernoulli.Tensor(%arg0: !torch.vtensor<[?,?,?],f64>, %arg1: !torch.vtensor<[?,?,?],f64>) -> !torch.vtensor {
|
|
%none = torch.constant.none
|
|
%0 = torch.valsem.aten.bernoulli.Tensor %arg0, %arg1, %none : !torch.vtensor<[?,?,?],f64>, !torch.vtensor<[?,?,?],f64>, !torch.none -> !torch.vtensor<[?,?,?],f64>
|
|
%1 = torch.tensor_static_info_cast %0 : !torch.vtensor<[?,?,?],f64> to !torch.vtensor
|
|
return %1 : !torch.vtensor
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.select.int(
|
|
// CHECK-SAME: %[[T:.*]]: !torch.vtensor<[?,?],si64>) -> !torch.vtensor<[?],si64> {
|
|
// CHECK: %[[CST0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[CST1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[END:.*]] = torch.aten.add.int %[[CST0]], %[[CST1]] : !torch.int, !torch.int -> !torch.int
|
|
// CHECK: %[[SLICE:.*]] = torch.aten.slice.Tensor %[[T]], %[[CST0]], %[[CST0]], %[[END]], %[[CST1]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?],si64>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[1,?],si64>
|
|
// CHECK: %[[SELECT:.*]] = torch.aten.squeeze.dim %[[SLICE]], %[[CST0]] :
|
|
// CHECK-SAME: !torch.vtensor<[1,?],si64>, !torch.int -> !torch.vtensor<[?],si64>
|
|
// CHECK: return %[[SELECT]] : !torch.vtensor<[?],si64>
|
|
func @torch.aten.select.int(%arg0: !torch.vtensor<[?,?],si64>) -> !torch.vtensor<[?],si64> {
|
|
%int0 = torch.constant.int 0
|
|
%0 = torch.aten.select.int %arg0, %int0, %int0 : !torch.vtensor<[?,?],si64>, !torch.int, !torch.int -> !torch.vtensor<[?],si64>
|
|
return %0 : !torch.vtensor<[?],si64>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.hardsigmoid(
|
|
// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[CST1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[CST2:.*]] = torch.constant.int 3
|
|
// CHECK: %[[CST6:.*]] = torch.constant.int 6
|
|
// CHECK: %[[ADD:.*]] = torch.aten.add.Scalar %[[INPUT]], %[[CST2]], %[[CST1]] : !torch.vtensor<[?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[DIV:.*]] = torch.aten.div.Scalar %[[ADD]], %[[CST6]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[CST0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[SIZES:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[EMPTY:.*]] = torch.aten.empty.memory_format %[[SIZES]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] :
|
|
// CHECK-SAME: !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[CST1_TENSOR:.*]] = torch.valsem.aten.fill.Scalar %[[EMPTY]], %[[CST1]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[MIN:.*]] = torch.aten.minimum %[[CST1_TENSOR]], %[[DIV]] : !torch.vtensor<[],f32>, !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[SIZES:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE_1:.*]] = torch.constant.none
|
|
// CHECK: %[[EMPTY_1:.*]] = torch.aten.empty.memory_format %[[SIZES]], %[[NONE_1]], %[[NONE_1]], %[[NONE_1]], %[[NONE_1]], %[[NONE_1]] :
|
|
// CHECK-SAME: !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[CST0_TENSOR:.*]] = torch.valsem.aten.fill.Scalar %[[EMPTY_1]], %[[CST0]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[RET:.*]] = torch.aten.maximum %[[CST0_TENSOR]], %[[MIN]] : !torch.vtensor<[],f32>, !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: return %[[RET]] : !torch.vtensor<[?,?],f32>
|
|
// CHECK: }
|
|
func @torch.aten.hardsigmoid(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%0 = torch.aten.hardsigmoid %arg0 : !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.hardswish(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[INT3:.*]] = torch.constant.int 3
|
|
// CHECK: %[[INT6:.*]] = torch.constant.int 6
|
|
// CHECK: %[[ADD:.*]] = torch.aten.add.Scalar %[[INP]], %[[INT3]], %[[INT1]] : !torch.vtensor<[?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[RELU:.*]] = torch.aten.relu %[[ADD]] : !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[INT6_:.*]] = torch.constant.int 6
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[MEM:.*]] = torch.aten.empty.memory_format %[[LIST]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] :
|
|
// CHECK-SAME: !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[FILL:.*]] = torch.valsem.aten.fill.Scalar %[[MEM]], %[[INT6_]] : !torch.vtensor<[],f32>, !torch.int -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[MIN:.*]] = torch.aten.minimum %[[RELU]], %[[FILL]] : !torch.vtensor<[?,?],f32>, !torch.vtensor<[],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[DIV:.*]] = torch.aten.div.Scalar %[[MIN]], %[[INT6]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[MUL:.*]] = torch.aten.mul.Tensor %[[DIV]], %[[INP]] : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: return %[[MUL]] : !torch.vtensor<[?,?],f32>
|
|
func @torch.aten.hardswish(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%0 = torch.aten.hardswish %arg0 : !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.hardtanh(
|
|
// CHECK-SAME: %[[INPUT:.*]]: !torch.vtensor<[?],f32>,
|
|
// CHECK-SAME: %[[MIN_VAL:.*]]: !torch.float,
|
|
// CHECK-SAME: %[[MAX_VAL:.*]]: !torch.float) -> !torch.vtensor<[?],f32> {
|
|
// CHECK: %[[SIZES:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[EMPTY:.*]] = torch.aten.empty.memory_format %[[SIZES]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] :
|
|
// CHECK-SAME: !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[MIN_TENSOR:.*]] = torch.valsem.aten.fill.Scalar %[[EMPTY]], %[[MIN_VAL]] : !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[MIN:.*]] = torch.aten.maximum %[[INPUT]], %[[MIN_TENSOR]] : !torch.vtensor<[?],f32>, !torch.vtensor<[],f32> -> !torch.vtensor<[?],f32>
|
|
// CHECK: %[[SIZES:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[VAL_10:.*]] = torch.aten.empty.memory_format %[[SIZES]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] :
|
|
// CHECK-SAME: !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[MAX_TENSOR:.*]] = torch.valsem.aten.fill.Scalar %[[VAL_10]], %[[MAX_VAL]] : !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[RET:.*]] = torch.aten.minimum %[[MAX_TENSOR]], %[[MIN]] : !torch.vtensor<[],f32>, !torch.vtensor<[?],f32> -> !torch.vtensor<[?],f32>
|
|
// CHECK: return %[[RET]] : !torch.vtensor<[?],f32>
|
|
func @torch.aten.hardtanh(%arg0: !torch.vtensor<[?],f32>, %min: !torch.float, %max: !torch.float) -> !torch.vtensor<[?],f32> {
|
|
%0 = torch.aten.hardtanh %arg0, %min, %max : !torch.vtensor<[?],f32>, !torch.float, !torch.float -> !torch.vtensor<[?],f32>
|
|
return %0 : !torch.vtensor<[?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.new_zeros
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[2,3],f32> {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[INT3:.*]] = torch.constant.int 3
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[INT2]], %[[INT3]] : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[INT6:.*]] = torch.constant.int 6
|
|
// CHECK: %[[RES:.*]] = torch.aten.zeros %[[SIZE]], %[[INT6]], %[[NONE]], %[[NONE]], %[[NONE]] : !torch.list<int>, !torch.int, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[2,3],f32>
|
|
// CHECK: }
|
|
func @torch.aten.new_zeros(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[2,3],f32> {
|
|
%none = torch.constant.none
|
|
%int2 = torch.constant.int 2
|
|
%int3 = torch.constant.int 3
|
|
%0 = torch.prim.ListConstruct %int2, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.new_zeros %arg0, %0, %none, %none, %none, %none : !torch.vtensor<[?,?],f32>, !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
return %1 : !torch.vtensor<[2,3],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.new_ones
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],si64>) -> !torch.vtensor<[3,4],si64> {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT3:.*]] = torch.constant.int 3
|
|
// CHECK: %[[INT4:.*]] = torch.constant.int 4
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[INT3]], %[[INT4]] : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[INT4_0:.*]] = torch.constant.int 4
|
|
// CHECK: %[[RES:.*]] = torch.aten.ones %[[SIZE]], %[[INT4_0]], %[[NONE]], %[[NONE]], %[[NONE]] : !torch.list<int>, !torch.int, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3,4],si64>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[3,4],si64>
|
|
// CHECK: }
|
|
func @torch.aten.new_ones(%arg0: !torch.vtensor<[?,?],si64>) -> !torch.vtensor<[3,4],si64> {
|
|
%none = torch.constant.none
|
|
%int3 = torch.constant.int 3
|
|
%int4 = torch.constant.int 4
|
|
%0 = torch.prim.ListConstruct %int3, %int4 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.new_ones %arg0, %0, %none, %none, %none, %none : !torch.vtensor<[?,?],si64>, !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[3,4],si64>
|
|
return %1 : !torch.vtensor<[3,4],si64>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.silu(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor {
|
|
// CHECK: %[[SIGMOID:.*]] = torch.aten.sigmoid %[[INP]] : !torch.vtensor<[?,?],f32> -> !torch.vtensor
|
|
// CHECK: %[[MUL:.*]] = torch.aten.mul.Tensor %[[SIGMOID]], %[[INP]] : !torch.vtensor, !torch.vtensor<[?,?],f32> -> !torch.vtensor
|
|
// CHECK: return %[[MUL]] : !torch.vtensor
|
|
func @torch.aten.silu(%arg0: !torch.vtensor<[?,?],f32> loc(unknown)) -> !torch.vtensor {
|
|
%0 = torch.aten.silu %arg0 : !torch.vtensor<[?,?],f32> -> !torch.vtensor
|
|
return %0 : !torch.vtensor
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.full
|
|
// CHECK-SAME: () -> !torch.vtensor<[2,3],f32> {
|
|
// CHECK: %[[FLOAT5:.*]] = torch.constant.float 5.000000e+00
|
|
// CHECK: %[[INT3:.*]] = torch.constant.int 3
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[INT2]], %[[INT3]] : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[MEM_FORMAT:.*]] = torch.constant.none
|
|
// CHECK: %[[EMPTY:.*]] = torch.aten.empty.memory_format %[[SIZE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[MEM_FORMAT]] : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
// CHECK: %[[RES:.*]] = torch.valsem.aten.fill.Scalar %[[EMPTY]], %[[FLOAT5]] : !torch.vtensor<[2,3],f32>, !torch.float -> !torch.vtensor<[2,3],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[2,3],f32>
|
|
func @torch.aten.full() -> !torch.vtensor<[2,3],f32> {
|
|
%float5.000000e00 = torch.constant.float 5.000000e+00
|
|
%int3 = torch.constant.int 3
|
|
%int2 = torch.constant.int 2
|
|
%none = torch.constant.none
|
|
%0 = torch.prim.ListConstruct %int2, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.full %0, %float5.000000e00, %none, %none, %none, %none : !torch.list<int>, !torch.float, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
return %1 : !torch.vtensor<[2,3],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.full_like(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[INT5:.*]] = torch.constant.int 5
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[DIM0:.*]] = torch.aten.size.int %[[INP]], %[[INT0]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[DIM1:.*]] = torch.aten.size.int %[[INP]], %[[INT1]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[DIM0]], %[[DIM1]] : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[EMPTY:.*]] = torch.aten.empty.memory_format %[[SIZE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[RES:.*]] = torch.valsem.aten.fill.Scalar %[[EMPTY]], %[[INT5]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[?,?],f32>
|
|
func @torch.aten.full_like(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%int5 = torch.constant.int 5
|
|
%none = torch.constant.none
|
|
%0 = torch.aten.full_like %arg0, %int5, %none, %none, %none, %none, %none : !torch.vtensor<[?,?],f32>, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.index_put(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?],f32>, %[[INDEX:.*]]: !torch.vtensor<[?],si64>,
|
|
// CHECK-SAME: %[[VALUES:.*]]: !torch.vtensor<[?],f32>,
|
|
// CHECK-SAME: %[[ACCUM:.*]]: !torch.bool) -> !torch.vtensor<[?],f32> {
|
|
// CHECK: %[[INDICES:.*]] = torch.prim.ListConstruct %[[INDEX]] : (!torch.vtensor<[?],si64>) -> !torch.list<vtensor>
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[RES:.*]] = torch.valsem.aten.index_put_impl %[[INP]], %[[INDICES]], %[[VALUES]], %[[ACCUM]], %[[FALSE]] : !torch.vtensor<[?],f32>, !torch.list<vtensor>, !torch.vtensor<[?],f32>, !torch.bool, !torch.bool -> !torch.vtensor<[?],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[?],f32>
|
|
func @torch.aten.index_put(%input: !torch.vtensor<[?],f32>, %index: !torch.vtensor<[?],si64>, %values: !torch.vtensor<[?],f32>, %accumulate : !torch.bool) -> !torch.vtensor<[?],f32> {
|
|
%indices = torch.prim.ListConstruct %index : (!torch.vtensor<[?],si64>) -> !torch.list<vtensor>
|
|
%0 = torch.aten.index_put %input, %indices, %values, %accumulate : !torch.vtensor<[?],f32>, !torch.list<vtensor>, !torch.vtensor<[?],f32>, !torch.bool -> !torch.vtensor<[?],f32>
|
|
return %0 : !torch.vtensor<[?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.expand_as(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,1,1],f32>, %[[OTHER:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[DIM0:.*]] = torch.aten.size.int %[[OTHER]], %[[INT0]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[DIM1:.*]] = torch.aten.size.int %[[OTHER]], %[[INT1]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[DIM2:.*]] = torch.aten.size.int %[[OTHER]], %[[INT2]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[DIM0]], %[[DIM1]], %[[DIM2]] : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[RES:.*]] = torch.aten.broadcast_to %[[INP]], %[[SIZE]] : !torch.vtensor<[?,1,1],f32>, !torch.list<int> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[?,?,?],f32>
|
|
func @torch.aten.expand_as(%arg0: !torch.vtensor<[?,1,1],f32>, %arg1: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
%0 = torch.aten.expand_as %arg0, %arg1 : !torch.vtensor<[?,1,1],f32>, !torch.vtensor<[?,?,?],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten._to_copy(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[DIM0:.*]] = torch.aten.size.int %[[INP]], %[[INT0]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[DIM1:.*]] = torch.aten.size.int %[[INP]], %[[INT1]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[DIM2:.*]] = torch.aten.size.int %[[INP]], %[[INT2]] : !torch.vtensor<[?,?,?],f32>, !torch.int -> !torch.int
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[DIM0]], %[[DIM1]], %[[DIM2]] : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[EMPTY:.*]] = torch.aten.empty.memory_format %[[SIZE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE]] : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: %[[RES:.*]] = torch.valsem.aten.copy %[[EMPTY]], %[[INP]], %[[FALSE]] : !torch.vtensor<[?,?,?],f32>, !torch.vtensor<[?,?,?],f32>, !torch.bool -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[?,?,?],f32>
|
|
func @torch.aten._to_copy(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
%false = torch.constant.bool false
|
|
%none = torch.constant.none
|
|
%0 = torch.aten._to_copy %arg0, %none, %none, %none, %none, %false, %none : !torch.vtensor<[?,?,?],f32>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.bool, !torch.none -> !torch.vtensor<[?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.dropout$eval(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[PROB:.*]] = torch.constant.float 1.000000e-01
|
|
// CHECK: %[[TRAIN:.*]] = torch.constant.bool false
|
|
// CHECK: return %[[INP:.*]] : !torch.vtensor<[?,?],f32>
|
|
func @torch.aten.dropout$eval(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%float1.000000e-01 = torch.constant.float 1.000000e-01
|
|
%false = torch.constant.bool false
|
|
%0 = torch.aten.dropout %arg0, %float1.000000e-01, %false : !torch.vtensor<[?,?],f32>, !torch.float, !torch.bool -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.dropout$train(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[PROB:.*]] = torch.constant.float 3.000000e-01
|
|
// CHECK: %[[TRAIN:.*]] = torch.constant.bool true
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[CST1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[ONEMINUSP:.*]] = torch.aten.sub.float %[[CST1]], %[[PROB]] : !torch.float, !torch.float -> !torch.float
|
|
// CHECK: %[[PROB_TENSOR:.*]] = torch.prim.NumToTensor.Scalar %[[ONEMINUSP]] : !torch.float -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[INT7:.*]] = torch.constant.int 7
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_0:.*]] = torch.constant.none
|
|
// CHECK: %[[CON2FLOAT:.*]] = torch.aten.to.dtype %[[INP]], %[[INT7]], %[[FALSE]], %[[FALSE]], %[[NONE_0]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?],f64>
|
|
// CHECK: %[[NONE_1:.*]] = torch.constant.none
|
|
// CHECK: %[[NONE_2:.*]] = torch.constant.none
|
|
// CHECK: %[[FLOAT0:.*]] = torch.constant.float 0.000000e+00
|
|
// CHECK: %[[FLOAT1:.*]] = torch.constant.float 1.000000e+00
|
|
// CHECK: %[[UNF:.*]] = torch.valsem.aten.uniform %[[CON2FLOAT]], %[[FLOAT0]], %[[FLOAT1]], %[[NONE_2]] : !torch.vtensor<[?,?],f64>, !torch.float, !torch.float, !torch.none -> !torch.vtensor<[?,?],f64>
|
|
// CHECK: %[[CMP:.*]] = torch.aten.lt.Tensor %[[UNF]], %[[PROB_TENSOR]] : !torch.vtensor<[?,?],f64>, !torch.vtensor<[],f64> -> !torch.vtensor<[?,?],i1>
|
|
// CHECK: %[[INT6:.*]] = torch.constant.int 6
|
|
// CHECK: %[[FALSE_2:.*]] = torch.constant.bool false
|
|
// CHECK: %[[NONE_3:.*]] = torch.constant.none
|
|
// CHECK: %[[BOOL_MASK:.*]] = torch.aten.to.dtype %[[CMP]], %[[INT6]], %[[FALSE_2]], %[[FALSE_2]], %[[NONE_3]] :
|
|
// CHECK-SAME: !torch.vtensor<[?,?],i1>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[MASK_INP:.*]] = torch.aten.mul.Tensor %[[BOOL_MASK]], %[[INP]] : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: %[[OUT:.*]] = torch.aten.div.Scalar %[[MASK_INP]], %[[ONEMINUSP]] : !torch.vtensor<[?,?],f32>, !torch.float -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?],f32>
|
|
func @torch.aten.dropout$train(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%float3.000000e-01 = torch.constant.float 3.000000e-01
|
|
%true = torch.constant.bool true
|
|
%0 = torch.aten.dropout %arg0, %float3.000000e-01, %true : !torch.vtensor<[?,?],f32>, !torch.float, !torch.bool -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.valsem.aten.zero(
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
// CHECK: %[[ZERO:.*]] = torch.constant.int 0
|
|
// CHECK: %[[OUT:.*]] = torch.valsem.aten.fill.Scalar %[[INP]], %[[ZERO]] : !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?],f32>
|
|
func @torch.valsem.aten.zero(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f32> {
|
|
%0 = torch.valsem.aten.zero %arg0 : !torch.vtensor<[?,?],f32> -> !torch.vtensor<[?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.new_empty
|
|
// CHECK-SAME: %[[INP:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[2,3],f32> {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[INT3:.*]] = torch.constant.int 3
|
|
// CHECK: %[[SIZE:.*]] = torch.prim.ListConstruct %[[INT2]], %[[INT3]] : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[NONE_0:.*]] = torch.constant.none
|
|
// CHECK: %[[INT6:.*]] = torch.constant.int 6
|
|
// CHECK: %[[RES:.*]] = torch.aten.empty.memory_format %[[SIZE]], %[[INT6]], %[[NONE]], %[[NONE]], %[[NONE]], %[[NONE_0]] : !torch.list<int>, !torch.int, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
// CHECK: return %[[RES]] : !torch.vtensor<[2,3],f32>
|
|
func @torch.aten.new_empty(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[2,3],f32> {
|
|
%none = torch.constant.none
|
|
%int2 = torch.constant.int 2
|
|
%int3 = torch.constant.int 3
|
|
%0 = torch.prim.ListConstruct %int2, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.new_empty %arg0, %0, %none, %none, %none, %none : !torch.vtensor<[?,?],f32>, !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[2,3],f32>
|
|
return %1 : !torch.vtensor<[2,3],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.where.Scalar(
|
|
// CHECK-SAME: %[[COND:.*]]: !torch.vtensor<[?,?,?],i1>) -> !torch.vtensor<[?,?,?],f32> {
|
|
// CHECK: %[[CST8:.*]] = torch.constant.float 8.000000e+00
|
|
// CHECK: %[[CST4:.*]] = torch.constant.float 4.000000e+00
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[ALLOC:.*]] = torch.aten.empty.memory_format %[[LIST]], %none, %none, %none, %none, %none : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[FILL_SELF:.*]] = torch.valsem.aten.fill.Scalar %[[ALLOC]], %[[CST4]] : !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[LIST2:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE2:.*]] = torch.constant.none
|
|
// CHECK: %[[ALLOC2:.*]] = torch.aten.empty.memory_format %[[LIST2]], %none_0, %none_0, %none_0, %none_0, %none_0 : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[FILL_OTHER:.*]] = torch.valsem.aten.fill.Scalar %[[ALLOC2]], %[[CST8]] : !torch.vtensor<[],f32>, !torch.float -> !torch.vtensor<[],f32>
|
|
// CHECK: %[[OUT:.*]] = torch.aten.where.self %[[COND]], %[[FILL_SELF]], %[[FILL_OTHER]] : !torch.vtensor<[?,?,?],i1>, !torch.vtensor<[],f32>, !torch.vtensor<[],f32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?,?],f32>
|
|
func @torch.aten.where.Scalar(%arg0: !torch.vtensor<[?,?,?],i1>) -> !torch.vtensor<[?,?,?],f32> {
|
|
%cst8 = torch.constant.float 8.000000e+00
|
|
%cst4 = torch.constant.float 4.000000e+00
|
|
%0 = torch.aten.where.Scalar %arg0, %cst4, %cst8 : !torch.vtensor<[?,?,?],i1>, !torch.float, !torch.float -> !torch.vtensor<[?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.where.ScalarSelf(
|
|
// CHECK-SAME: %[[COND:.*]]: !torch.vtensor<[?,?,?],i1>, %[[OTHER:.*]]: !torch.vtensor<[?,?],f64>) -> !torch.vtensor<[?,?,?],f64> {
|
|
// CHECK: %[[CST:.*]] = torch.constant.float 4.000000e+00
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[ALLOC:.*]] = torch.aten.empty.memory_format %[[LIST]], %none, %none, %none, %none, %none : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[FILL:.*]] = torch.valsem.aten.fill.Scalar %[[ALLOC]], %[[CST]] : !torch.vtensor<[],f64>, !torch.float -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[OUT:.*]] = torch.aten.where.self %[[COND]], %[[FILL]], %[[OTHER]] : !torch.vtensor<[?,?,?],i1>, !torch.vtensor<[],f64>, !torch.vtensor<[?,?],f64> -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?,?],f64>
|
|
func @torch.aten.where.ScalarSelf(%arg0: !torch.vtensor<[?,?,?],i1>, %arg1: !torch.vtensor<[?,?],f64>) -> !torch.vtensor<[?,?,?],f64> {
|
|
%cst = torch.constant.float 4.000000e+00
|
|
%0 = torch.aten.where.ScalarSelf %arg0, %cst, %arg1 : !torch.vtensor<[?,?,?],i1>, !torch.float, !torch.vtensor<[?,?],f64> -> !torch.vtensor<[?,?,?],f64>
|
|
return %0 : !torch.vtensor<[?,?,?],f64>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.where.ScalarOther(
|
|
// CHECK-SAME: %[[COND:.*]]: !torch.vtensor<[?,?,?],i1>, %[[SELF:.*]]: !torch.vtensor<[?,?],f64>) -> !torch.vtensor<[?,?,?],f64> {
|
|
// CHECK: %[[CST:.*]] = torch.constant.float 4.000000e+00
|
|
// CHECK: %[[LIST:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[ALLOC:.*]] = torch.aten.empty.memory_format %[[LIST]], %none, %none, %none, %none, %none : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.none, !torch.none -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[FILL:.*]] = torch.valsem.aten.fill.Scalar %[[ALLOC]], %[[CST]] : !torch.vtensor<[],f64>, !torch.float -> !torch.vtensor<[],f64>
|
|
// CHECK: %[[OUT:.*]] = torch.aten.where.self %[[COND]], %[[SELF]], %[[FILL]] : !torch.vtensor<[?,?,?],i1>, !torch.vtensor<[?,?],f64>, !torch.vtensor<[],f64> -> !torch.vtensor<[?,?,?],f64>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?,?],f64>
|
|
func @torch.aten.where.ScalarOther(%arg0: !torch.vtensor<[?,?,?],i1>, %arg1: !torch.vtensor<[?,?],f64>) -> !torch.vtensor<[?,?,?],f64> {
|
|
%cst = torch.constant.float 4.000000e+00
|
|
%0 = torch.aten.where.ScalarOther %arg0, %arg1, %cst : !torch.vtensor<[?,?,?],i1>, !torch.vtensor<[?,?],f64>, !torch.float -> !torch.vtensor<[?,?,?],f64>
|
|
return %0 : !torch.vtensor<[?,?,?],f64>
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}
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// -----
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// CHECK-LABEL: func @torch.aten.pad
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// CHECK-SAME: (%[[SELF:.*]]: !torch.vtensor<[?,?,?],f64>, %[[VALUE:.*]]: !torch.float) -> !torch.vtensor<[?,?,?],f64> {
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// CHECK-NOT: torch.aten.pad
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// CHECK: %[[STRING:.*]] = torch.constant.str "constant"
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// CHECK-NEXT: %[[LIST:.*]] = torch.prim.ListConstruct
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|
// CHECK-NEXT: %[[PAD_ND:.*]] = torch.aten.constant_pad_nd %[[SELF]], %[[LIST]], %[[VALUE]]
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// CHECK-NEXT: return %[[PAD_ND]]
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|
func @torch.aten.pad(%arg0: !torch.vtensor<[?,?,?],f64>, %arg1: !torch.float) -> !torch.vtensor<[?,?,?],f64> {
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|
%int0 = torch.constant.int 0
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|
%int1 = torch.constant.int 1
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|
%int2 = torch.constant.int 2
|
|
%int3 = torch.constant.int 3
|
|
%str = torch.constant.str "constant"
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|
%0 = torch.prim.ListConstruct %int0, %int1, %int2, %int3 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.pad %arg0, %0, %str, %arg1 : !torch.vtensor<[?,?,?],f64>, !torch.list<int>, !torch.str, !torch.float -> !torch.vtensor<[?,?,?],f64>
|
|
return %1 : !torch.vtensor<[?,?,?],f64>
|
|
}
|
|
|
|
// -----
|
|
// CHECK-LABEL: func @torch.aten.to.dtype_layout(
|
|
// CHECK-SAME: %[[SELF:.*]]: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f64> {
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[FALSE:.*]] = torch.constant.bool false
|
|
// CHECK: %[[CST0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[CST7:.*]] = torch.constant.int 7
|
|
// CHECK: %[[OUT:.*]] = torch.aten.to.dtype %[[SELF]], %[[CST7]], %[[FALSE]], %[[FALSE]], %[[NONE]] : !torch.vtensor<[?,?],f32>, !torch.int, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?],f64>
|
|
// CHECK: return %[[OUT]] : !torch.vtensor<[?,?],f64>
|
|
func @torch.aten.to.dtype_layout(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor<[?,?],f64> {
|
|
%none = torch.constant.none
|
|
%false = torch.constant.bool false
|
|
%int0 = torch.constant.int 0
|
|
%int7 = torch.constant.int 7
|
|
%0 = torch.aten.to.dtype_layout %arg0, %int7, %int0, %none, %none, %false, %false, %none : !torch.vtensor<[?,?],f32>, !torch.int, !torch.int, !torch.none, !torch.none, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[?,?],f64>
|
|
return %0 : !torch.vtensor<[?,?],f64>
|
|
}
|