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Fix torchToTosa lowering for avgpool2d to handle unsupported parameters (#3822) 

The existing TorchToTosa lowering logic for `torch.aten.avg_pool2d`
doesn't handle some unsupported properties well, leading to a silent
wrong answer(SWA) when we go through
`torch-backend-to-tosa-backend-pipeline.` For instance, with the
existing TOSA avgpool2d specification, we can not represent
`count_include_pad` and `divisor_override,` so during TorchToTosa
lowering, we silently ignore these properties which leads to SWA in some
cases—the fix captured in this change errors for unsupported scenarios.

For details on `count_include_pad` and `divisor_override,` please see
the below link.

https://pytorch.org/docs/stable/generated/torch.nn.AvgPool2d.html

---------

Co-authored-by: Hanumanth Hanumantharayappa <hhanuman@ah-hhanuman-l.dhcp.mathworks.com>
pull/3848/head
Hanumanth 2024-11-01 08:25:59 -04:00 committed by GitHub
parent 032a636c35
commit 7f9f99c6f8
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2 changed files with 72 additions and 16 deletions
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22
lib/Conversion/TorchToTosa/TorchToTosa.cpp
View File

@ -5466,6 +5466,28 @@ public:
DenseI64ArrayAttr &kernel, DenseI64ArrayAttr &kernel,
DenseI64ArrayAttr &stride, DenseI64ArrayAttr &pad, DenseI64ArrayAttr &stride, DenseI64ArrayAttr &pad,
Type &outputTy) const override { Type &outputTy) const override {
// Currently, we can not represent `count_include_pad` with the existing
// TOSA AvgPool2d specification. Without the below check, we produce silent
// wrong answers (SWA) when the `count_include_pad` value is `true.`
bool countIncludePad;
if (!matchPattern(op.getCountIncludePad(),
m_TorchConstantBool(&countIncludePad)) ||
countIncludePad) {
return rewriter.notifyMatchFailure(
op, "Unsupported `count_include_pad` value, for tosa AvgPool2dOp "
"`count_include_pad` value should be `False`.");
}
// Currently, we can not represent `divisor_override` with the existing TOSA
// AvgPool2d specification. Without the below check, we produce silent wrong
// answers (SWA) when the `divisor_override` value is other than `None.`
if (!isa<Torch::NoneType>(op.getDivisorOverride().getType())) {
return rewriter.notifyMatchFailure(
op, "Unsupported `divisor_override` value, for tosa AvgPool2dOp "
"`divisor_override` value should be `None`.");
}
SmallVector<int64_t, 2> dilationArray{1, 1}; SmallVector<int64_t, 2> dilationArray{1, 1};
if (failed(getOutputTypeAndPoolingParameters<AtenAvgPool2dOp, if (failed(getOutputTypeAndPoolingParameters<AtenAvgPool2dOp,
tosa::AvgPool2dOp>( tosa::AvgPool2dOp>(

64
test/Conversion/TorchToTosa/basic.mlir
View File

@ -858,31 +858,29 @@ func.func @torch.aten.dropout$basic(%arg0: !torch.vtensor<[?,?],f32> ) -> !torch
// CHECK: %[[VAL_3:.*]] = torch.constant.int 1 // CHECK: %[[VAL_3:.*]] = torch.constant.int 1
// CHECK: %[[VAL_4:.*]] = torch.constant.int 0 // CHECK: %[[VAL_4:.*]] = torch.constant.int 0
// CHECK: %[[VAL_5:.*]] = torch.constant.bool false // CHECK: %[[VAL_5:.*]] = torch.constant.bool false
// CHECK: %[[VAL_6:.*]] = torch.constant.bool true // CHECK: %[[VAL_6:.*]] = torch.constant.none
// CHECK: %[[VAL_7:.*]] = torch.constant.none // CHECK: %[[VAL_7:.*]] = torch.prim.ListConstruct %[[VAL_2]], %[[VAL_2]] : (!torch.int, !torch.int) -> !torch.list<int>
// CHECK: %[[VAL_8:.*]] = torch.prim.ListConstruct %[[VAL_2]], %[[VAL_2]] : (!torch.int, !torch.int) -> !torch.list<int> // CHECK: %[[VAL_8:.*]] = torch.prim.ListConstruct %[[VAL_3]], %[[VAL_3]] : (!torch.int, !torch.int) -> !torch.list<int>
// CHECK: %[[VAL_9:.*]] = torch.prim.ListConstruct %[[VAL_3]], %[[VAL_3]] : (!torch.int, !torch.int) -> !torch.list<int> // CHECK: %[[VAL_9:.*]] = torch.prim.ListConstruct %[[VAL_4]], %[[VAL_4]] : (!torch.int, !torch.int) -> !torch.list<int>
// CHECK: %[[VAL_10:.*]] = torch.prim.ListConstruct %[[VAL_4]], %[[VAL_4]] : (!torch.int, !torch.int) -> !torch.list<int> // CHECK: %[[VAL_10:.*]] = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32>
// CHECK: %[[VAL_11:.*]] = "tosa.const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi32>}> : () -> tensor<4xi32> // CHECK: %[[VAL_11:.*]] = tosa.transpose %[[VAL_1]], %[[VAL_10]] : (tensor<1x512x7x7xf32>, tensor<4xi32>) -> tensor<1x7x7x512xf32>
// CHECK: %[[VAL_12:.*]] = tosa.transpose %[[VAL_1]], %[[VAL_11]] : (tensor<1x512x7x7xf32>, tensor<4xi32>) -> tensor<1x7x7x512xf32> // CHECK: %[[VAL_12:.*]] = tosa.avg_pool2d %[[VAL_11]] {acc_type = f32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x512xf32>) -> tensor<1x1x1x512xf32>
// CHECK: %[[VAL_13:.*]] = tosa.avg_pool2d %[[VAL_12]] {acc_type = f32, kernel = array<i64: 7, 7>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x7x7x512xf32>) -> tensor<1x1x1x512xf32> // CHECK: %[[VAL_13:.*]] = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32>
// CHECK: %[[VAL_14:.*]] = "tosa.const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> : () -> tensor<4xi32> // CHECK: %[[VAL_14:.*]] = tosa.transpose %[[VAL_12]], %[[VAL_13]] : (tensor<1x1x1x512xf32>, tensor<4xi32>) -> tensor<1x512x1x1xf32>
// CHECK: %[[VAL_15:.*]] = tosa.transpose %[[VAL_13]], %[[VAL_14]] : (tensor<1x1x1x512xf32>, tensor<4xi32>) -> tensor<1x512x1x1xf32> // CHECK: %[[VAL_15:.*]] = tensor.cast %[[VAL_14]] : tensor<1x512x1x1xf32> to tensor<1x512x1x1xf32>
// CHECK: %[[VAL_16:.*]] = tensor.cast %[[VAL_15]] : tensor<1x512x1x1xf32> to tensor<1x512x1x1xf32> // CHECK: %[[VAL_16:.*]] = torch_c.from_builtin_tensor %[[VAL_15]] : tensor<1x512x1x1xf32> -> !torch.vtensor<[1,512,1,1],f32>
// CHECK: %[[VAL_17:.*]] = torch_c.from_builtin_tensor %[[VAL_16]] : tensor<1x512x1x1xf32> -> !torch.vtensor<[1,512,1,1],f32> // CHECK: return %[[VAL_16]] : !torch.vtensor<[1,512,1,1],f32>
// CHECK: return %[[VAL_17]] : !torch.vtensor<[1,512,1,1],f32>
// CHECK: } // CHECK: }
func.func @torch.aten.avg_pool2d$basic(%arg0: !torch.vtensor<[1,512,7,7],f32> ) -> !torch.vtensor<[1,512,1,1],f32> { func.func @torch.aten.avg_pool2d$basic(%arg0: !torch.vtensor<[1,512,7,7],f32> ) -> !torch.vtensor<[1,512,1,1],f32> {
%int7 = torch.constant.int 7 %int7 = torch.constant.int 7
%int1 = torch.constant.int 1 %int1 = torch.constant.int 1
%int0 = torch.constant.int 0 %int0 = torch.constant.int 0
%false = torch.constant.bool false %false = torch.constant.bool false
%true = torch.constant.bool true
%none = torch.constant.none %none = torch.constant.none
%kernel = torch.prim.ListConstruct %int7, %int7 : (!torch.int, !torch.int) -> !torch.list<int> %kernel = torch.prim.ListConstruct %int7, %int7 : (!torch.int, !torch.int) -> !torch.list<int>
%stride = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int> %stride = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
%padding = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int> %padding = torch.prim.ListConstruct %int0, %int0 : (!torch.int, !torch.int) -> !torch.list<int>
%0 = torch.aten.avg_pool2d %arg0, %kernel, %stride, %padding, %false, %true, %none : !torch.vtensor<[1,512,7,7],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,512,1,1],f32> %0 = torch.aten.avg_pool2d %arg0, %kernel, %stride, %padding, %false, %false, %none : !torch.vtensor<[1,512,7,7],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,512,1,1],f32>
return %0 : !torch.vtensor<[1,512,1,1],f32> return %0 : !torch.vtensor<[1,512,1,1],f32>
} }
@ -2001,6 +1999,42 @@ func.func @torch.aten.round(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vtenso
// ----- // -----
func.func @torch.aten.avg_pool2d.count_include_pad_unsupported_value(%arg0: !torch.vtensor<[1,192,35,35],f32>) -> !torch.vtensor<[1,192,35,35],f32> {
%int0 = torch.constant.int 0
%int1 = torch.constant.int 1
%int3 = torch.constant.int 3
%false= torch.constant.bool false
%count_include_pad = torch.constant.bool true
%divisor_override = torch.constant.none
%0 = torch.prim.ListConstruct %int3, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
%1 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
%2 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
// expected-error @+1 {{failed to legalize operation 'torch.aten.avg_pool2d' that was explicitly marked illegal}}
%3 = torch.aten.avg_pool2d %arg0, %0, %1, %2, %false, %count_include_pad, %divisor_override : !torch.vtensor<[1,192,35,35],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.bool, !torch.none -> !torch.vtensor<[1,192,35,35],f32>
return %3 : !torch.vtensor<[1,192,35,35],f32>
}
// -----
func.func @torch.aten.avg_pool2d.divisor_override_unsupported_value(%arg0: !torch.vtensor<[1,192,35,35],f32>) -> !torch.vtensor<[1,192,35,35],f32> {
%int0 = torch.constant.int 0
%int1 = torch.constant.int 1
%int3 = torch.constant.int 3
%false= torch.constant.bool false
%count_include_pad = torch.constant.bool false
%divisor_override = torch.constant.int 9
%0 = torch.prim.ListConstruct %int3, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
%1 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
%2 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
// expected-error @+1 {{failed to legalize operation 'torch.aten.avg_pool2d' that was explicitly marked illegal}}
%3 = torch.aten.avg_pool2d %arg0, %0, %1, %2, %false, %count_include_pad, %divisor_override : !torch.vtensor<[1,192,35,35],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.bool, !torch.int -> !torch.vtensor<[1,192,35,35],f32>
return %3 : !torch.vtensor<[1,192,35,35],f32>
}
// -----
// CHECK-LABEL: func.func @torch.aten.empty.memory_format$basic() -> !torch.vtensor<[3,4],si64> { // CHECK-LABEL: func.func @torch.aten.empty.memory_format$basic() -> !torch.vtensor<[3,4],si64> {
// CHECK: %[[VAL_0:.*]] = torch.constant.int 0 // CHECK: %[[VAL_0:.*]] = torch.constant.int 0
// CHECK: %[[VAL_1:.*]] = torch.constant.bool false // CHECK: %[[VAL_1:.*]] = torch.constant.bool false