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Bug fix for shape of optional output in Dropout op (#1507)

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* Bug fix for shape of optional output in Dropout op

* Exclude new test from NGraph EP

* Account for the fact that mask could be of different type in different opset variants of the op

* Make accompanying Cuda changes

* Fix build break

* Exclude Opset 7 test for tensorRT EP

* PR comments
This commit is contained in:
Hariharan Seshadri 2019-07-31 22:37:11 -07:00 committed by GitHub
parent 57e2482089
commit 465b30e3ca
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GPG key ID: 4AEE18F83AFDEB23
5 changed files with 69 additions and 6 deletions
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13
onnxruntime/core/providers/cpu/tensor/identity_op.h
View file

@ -43,7 +43,18 @@ class IdentityOp final : public OpKernel {
}
if (is_dropout) {
context->Output(1, std::vector<int64_t>());
Tensor* mask = context->Output(1, shape);
// a 'nullptr' returned would make it an unused optional output
if (mask != nullptr) {
// Opset 7 differs with Opset 10 in that the type of the 'mask'
// output is tied with the type of the input in Opset 7 whereas
// the type of 'mask' in Opset 10 is 'bool' always
// so we have a common solution
void* mask_data = mask->MutableDataRaw();
// In 'test'/'inference' mode, there are no input values dropped out
// so fill the buffer with 0/false
memset(mask_data, 0, mask->SizeInBytes());
}
}
return Status::OK();

6
onnxruntime/core/providers/cuda/cuda_execution_provider.cc
View file

@ -200,7 +200,7 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Un
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, 8, Flatten);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Squeeze);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Identity);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, Dropout);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 9, Dropout);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Gather);
class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 8, float, Gemm);
class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 8, double, Gemm);
@ -515,6 +515,7 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain,
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, float, Shrink);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, double, Shrink);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, MLFloat16, Shrink);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 10, Dropout);
static void RegisterCudaKernels(KernelRegistry& kernel_registry) {
static const BuildKernelCreateInfoFn function_table[] = {
@ -525,7 +526,7 @@ static void RegisterCudaKernels(KernelRegistry& kernel_registry) {
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, 8, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Squeeze)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Identity)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, Dropout)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 9, Dropout)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 1, Gather)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 8, float, Gemm)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 7, 8, double, Gemm)>,
@ -840,6 +841,7 @@ static void RegisterCudaKernels(KernelRegistry& kernel_registry) {
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, float, Shrink)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, double, Shrink)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 9, MLFloat16, Shrink)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCudaExecutionProvider, kOnnxDomain, 10, Dropout)>,
};
for (auto& function_table_entry : function_table) {

19
onnxruntime/core/providers/cuda/tensor/identity_op.cc
View file

@ -5,13 +5,28 @@
namespace onnxruntime {
namespace cuda {
ONNX_OPERATOR_VERSIONED_KERNEL_EX(
Dropout,
kOnnxDomain,
7, 9,
kCudaExecutionProvider,
KernelDefBuilder()
.TypeConstraint("T", {DataTypeImpl::GetTensorType<MLFloat16>(),
DataTypeImpl::GetTensorType<float>(),
DataTypeImpl::GetTensorType<double>()})
.Alias(0, 0),
IdentityOp<true>);
ONNX_OPERATOR_KERNEL_EX(
Dropout,
kOnnxDomain,
7,
10,
kCudaExecutionProvider,
KernelDefBuilder()
.TypeConstraint("T", {DataTypeImpl::GetTensorType<MLFloat16>(), DataTypeImpl::GetTensorType<float>(), DataTypeImpl::GetTensorType<double>()})
.TypeConstraint("T", {DataTypeImpl::GetTensorType<MLFloat16>(),
DataTypeImpl::GetTensorType<float>(),
DataTypeImpl::GetTensorType<double>()})
.TypeConstraint("T1", DataTypeImpl::GetTensorType<bool>())
.Alias(0, 0),
IdentityOp<true>);

13
onnxruntime/core/providers/cuda/tensor/identity_op.h
View file

@ -30,7 +30,18 @@ class IdentityOp final : public CudaKernel {
}
if (is_dropout) {
context->Output(1, std::vector<int64_t>());
Tensor* mask = context->Output(1, shape);
// a 'nullptr' returned would make it an unused optional output
if (mask != nullptr) {
// Opset 7 differs with Opset 10 in that the type of the 'mask'
// output is tied with the type of the input in Opset 7 whereas
// the type of 'mask' in Opset 10 is 'bool' always
// so we have a common solution
void* mask_data = mask->MutableDataRaw();
// In 'test'/'inference' mode, there are no input values dropped out
// so fill the buffer with 0/false
CUDA_RETURN_IF_ERROR(cudaMemsetAsync(mask_data, 0, mask->SizeInBytes()));
}
}
return Status::OK();

24
onnxruntime/test/providers/cpu/nn/dropout_op_test.cc
View file

@ -23,5 +23,29 @@ TEST(Dropout, Opset10) {
test.Run();
}
TEST(Dropout, WithOptionalOutputOpset10) {
OpTester test("Dropout", 10, kOnnxDomain);
std::vector<int64_t> dims{2, 2};
test.AddInput<float>("X", dims, {1.0f, 2.0f, 3.0f, 5.0f});
test.AddOutput<float>("Y", dims, {1.0f, 2.0f, 3.0f, 5.0f});
test.AddOutput<bool>("mask", dims, {false, false, false, false});
// The NGraph execution provider doesn't seem to support 'Dropout' with optional mask output
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kNGraphExecutionProvider});
}
TEST(Dropout, WithOptionalOutputOpset7) {
// Opset 7 differs with Opset 10 in that the type of the 'mask'
// output is tied with the type of the input in Opset 7 whereas
// the type of 'mask' in Opset 10 is 'bool' always
OpTester test("Dropout", 7, kOnnxDomain);
std::vector<int64_t> dims{2, 2};
test.AddInput<float>("X", dims, {1.0f, 2.0f, 3.0f, 5.0f});
test.AddOutput<float>("Y", dims, {1.0f, 2.0f, 3.0f, 5.0f});
test.AddOutput<float>("mask", dims, {0.0f, 0.0f, 0.0f, 0.0f});
// The NGraph execution provider doesn't seem to support 'Dropout' with optional mask output
// The TensorRT execution provider doesn't seem to support 'Dropout' with non-boolean mask output
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kNGraphExecutionProvider, kTensorrtExecutionProvider});
}
} // namespace test
} // namespace onnxruntime