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Support opset-11 DepthToSpace CPU kernel (#1759)

Browse source 
* Initial commit

* Uncomment tests

* Updates

* Updates

* Disable CRD mode DepthToSpace for NGraph builds

* Disable test

* Update tests

* PR feedback

* Add unit test for CRD mode

* Reflect class variable in naming

* Add a test to NGRAPH disabled list

* Update main.cc

* Update main.cc
This commit is contained in:
Hariharan Seshadri 2019-09-18 17:17:28 -07:00 committed by GitHub
parent 80bda77203
commit 55f5a52b23
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GPG key ID: 4AEE18F83AFDEB23
6 changed files with 165 additions and 17 deletions
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7
onnxruntime/core/providers/cpu/cpu_execution_provider.cc
View file

@ -195,7 +195,7 @@ class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOn
class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 9, int64_t, Slice);
class ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 9, string, Slice);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, SpaceToDepth);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 4, DepthToSpace);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 10, DepthToSpace);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 2, Split);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Squeeze);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Tile);
@ -315,6 +315,7 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Ha
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, LogSoftmax);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Softmax);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Loop);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, DepthToSpace);
void RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
static const BuildKernelCreateInfoFn function_table[] = {
@ -495,7 +496,7 @@ void RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 9, int64_t, Slice)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 9, string, Slice)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, SpaceToDepth)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 4, DepthToSpace)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, 10, DepthToSpace)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 2, Split)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 1, Squeeze)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 6, Tile)>,
@ -615,7 +616,7 @@ void RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, LogSoftmax)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Softmax)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, Loop)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, DepthToSpace)>,
};
for (auto& function_table_entry : function_table) {

37
onnxruntime/core/providers/cpu/tensor/space_depth_ops.cc
View file

@ -15,8 +15,13 @@ ONNX_CPU_OPERATOR_KERNEL(
ONNX_CPU_OPERATOR_VERSIONED_KERNEL(
DepthToSpace,
1,
4,
1, 10,
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
DepthToSpace<float>);
ONNX_CPU_OPERATOR_KERNEL(
DepthToSpace,
11,
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
DepthToSpace<float>);
@ -75,14 +80,28 @@ Status DepthToSpace<float>::Compute(OpKernelContext* context) const {
const int64_t output_width = input_width * blocksize_;
Tensor& output = *context->Output(0, {batch, output_depth, output_height, output_width});
// Process "DCR" mode
if (is_dcr_) {
std::array<int64_t, IntermediateTensorRank> permutation{{0, 3, 4, 1, 5, 2}};
EigenTensorMap(output.template MutableData<float>(), batch, input_depth / blocksize_ / blocksize_,
input_height, blocksize_, input_width, blocksize_) =
EigenTensorMap(const_cast<float*>(input.template Data<float>()), batch,
blocksize_, blocksize_, input_depth / blocksize_ / blocksize_,
input_height, input_width)
.shuffle(permutation);
}
std::array<int64_t, IntermediateTensorRank> permutation{{0, 3, 4, 1, 5, 2}};
EigenTensorMap(output.template MutableData<float>(), batch, input_depth / blocksize_ / blocksize_,
input_height, blocksize_, input_width, blocksize_) =
EigenTensorMap(const_cast<float*>(input.template Data<float>()), batch,
blocksize_, blocksize_, input_depth / blocksize_ / blocksize_,
input_height, input_width)
.shuffle(permutation);
// Process "CRD" mode
else {
std::array<int64_t, IntermediateTensorRank> permutation{{0, 1, 4, 2, 5, 3}};
EigenTensorMap(output.template MutableData<float>(), batch, input_depth / blocksize_ / blocksize_,
input_height, blocksize_, input_width, blocksize_) =
EigenTensorMap(const_cast<float*>(input.template Data<float>()), batch,
input_depth / blocksize_ / blocksize_, blocksize_, blocksize_,
input_height, input_width)
.shuffle(permutation);
}
return Status::OK();
}

13
onnxruntime/core/providers/cpu/tensor/space_depth_ops.h
View file

@ -31,9 +31,22 @@ template <typename T>
class DepthToSpace final : public SpaceDepthBase {
public:
DepthToSpace(const OpKernelInfo& info) : SpaceDepthBase(info) {
std::string mode;
// if mode doesn't exist, then it is the default "DCR" mode
// (or) it is an opset < 11 model for which the only mode is "DCR" mode
if (info.GetAttr("mode", &mode).IsOK()) {
if (mode == "CRD")
is_dcr_ = false;
else if (mode != "DCR")
ORT_THROW("DepthToSpace op: only 'DCR' and 'CRD' modes are supported");
}
}
Status Compute(OpKernelContext* context) const override;
private:
bool is_dcr_ = true;
};
} //namespace onnxruntime

4
onnxruntime/test/onnx/main.cc
View file

@ -404,8 +404,6 @@ int real_main(int argc, char* argv[], Ort::Env& env) {
{"round", "not implemented yet"},
{"gather_elements_1", "not implemented yet"},
{"gather_elements_0", "not implemented yet"},
{"depthtospace_crd_mode_example", "not implemented yet"},
{"depthtospace_crd_mode", "not implemented yet"},
{"cumsum_2d_axis_1", "not implemented yet"},
{"cumsum_2d_axis_0", "not implemented yet"},
{"cumsum_1d_reverse_exclusive", "not implemented yet"},
@ -457,6 +455,8 @@ int real_main(int argc, char* argv[], Ort::Env& env) {
broken_tests.insert({"clip_default_min", "not implemented yet for opset 11"});
broken_tests.insert({"clip_default_max", "not implemented yet for opset 11"});
broken_tests.insert({"clip", "not implemented yet for opset 11"});
broken_tests.insert({"depthtospace_crd_mode_example", "NGraph does not support CRD mode"});
broken_tests.insert({"depthtospace_crd_mode", "NGraph does not support CRD mode"});
#endif
#ifdef USE_MKLDNN

119
onnxruntime/test/providers/cpu/tensor/space_depth_ops_test.cc
View file

@ -73,7 +73,7 @@ TEST(TensorOpTest, SpaceToDepthTest_2) {
}
TEST(TensorOpTest, DepthToSpaceTest_1) {
OpTester test("DepthToSpace");
OpTester test("DepthToSpace", 7); // create an opset 7 model
const int64_t blocksize = 2;
test.AddAttribute("blocksize", blocksize);
@ -104,7 +104,7 @@ TEST(TensorOpTest, DepthToSpaceTest_1) {
}
TEST(TensorOpTest, DepthToSpaceTest_2) {
OpTester test("DepthToSpace");
OpTester test("DepthToSpace", 7); // create an opset 7 model
const int64_t blocksize = 2;
test.AddAttribute("blocksize", blocksize);
@ -145,5 +145,120 @@ TEST(TensorOpTest, DepthToSpaceTest_2) {
test.AddOutput<float>("output", {2, 3, 6, 4}, result);
test.Run();
}
TEST(TensorOpTest, DepthToSpaceTest_3) {
OpTester test("DepthToSpace", 11); // create an opset 11 model with missing default attribute
const int64_t blocksize = 2;
test.AddAttribute("blocksize", blocksize);
const int64_t N = 2, C = 12, H = 3, W = 2;
const std::vector<float> X = {
0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.,
11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21.,
22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32.,
33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43.,
44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54.,
55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65.,
66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,
77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87.,
88., 89., 90., 91., 92., 93., 94., 95., 96., 97., 98.,
99., 100., 101., 102., 103., 104., 105., 106., 107., 108., 109.,
110., 111., 112., 113., 114., 115., 116., 117., 118., 119., 120.,
121., 122., 123., 124., 125., 126., 127., 128., 129., 130., 131.,
132., 133., 134., 135., 136., 137., 138., 139., 140., 141., 142.,
143.};
test.AddInput<float>("input", {N, C, H, W}, X);
const std::vector<float> result = {
0., 18., 1., 19., 36., 54., 37., 55., 2., 20., 3.,
21., 38., 56., 39., 57., 4., 22., 5., 23., 40., 58.,
41., 59., 6., 24., 7., 25., 42., 60., 43., 61., 8.,
26., 9., 27., 44., 62., 45., 63., 10., 28., 11., 29.,
46., 64., 47., 65., 12., 30., 13., 31., 48., 66., 49.,
67., 14., 32., 15., 33., 50., 68., 51., 69., 16., 34.,
17., 35., 52., 70., 53., 71., 72., 90., 73., 91., 108.,
126., 109., 127., 74., 92., 75., 93., 110., 128., 111., 129.,
76., 94., 77., 95., 112., 130., 113., 131., 78., 96., 79.,
97., 114., 132., 115., 133., 80., 98., 81., 99., 116., 134.,
117., 135., 82., 100., 83., 101., 118., 136., 119., 137., 84.,
102., 85., 103., 120., 138., 121., 139., 86., 104., 87., 105.,
122., 140., 123., 141., 88., 106., 89., 107., 124., 142., 125.,
143.};
test.AddOutput<float>("output", {2, 3, 6, 4}, result);
test.Run();
}
TEST(TensorOpTest, DepthToSpaceTest_4) {
OpTester test("DepthToSpace", 11); // create an opset 11 model with attribute present = "DCR" mode
const int64_t blocksize = 2;
test.AddAttribute("blocksize", blocksize);
test.AddAttribute("mode", "DCR");
const int64_t N = 2, C = 12, H = 3, W = 2;
const std::vector<float> X = {
0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.,
11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21.,
22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32.,
33., 34., 35., 36., 37., 38., 39., 40., 41., 42., 43.,
44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54.,
55., 56., 57., 58., 59., 60., 61., 62., 63., 64., 65.,
66., 67., 68., 69., 70., 71., 72., 73., 74., 75., 76.,
77., 78., 79., 80., 81., 82., 83., 84., 85., 86., 87.,
88., 89., 90., 91., 92., 93., 94., 95., 96., 97., 98.,
99., 100., 101., 102., 103., 104., 105., 106., 107., 108., 109.,
110., 111., 112., 113., 114., 115., 116., 117., 118., 119., 120.,
121., 122., 123., 124., 125., 126., 127., 128., 129., 130., 131.,
132., 133., 134., 135., 136., 137., 138., 139., 140., 141., 142.,
143.};
test.AddInput<float>("input", {N, C, H, W}, X);
const std::vector<float> result = {
0., 18., 1., 19., 36., 54., 37., 55., 2., 20., 3.,
21., 38., 56., 39., 57., 4., 22., 5., 23., 40., 58.,
41., 59., 6., 24., 7., 25., 42., 60., 43., 61., 8.,
26., 9., 27., 44., 62., 45., 63., 10., 28., 11., 29.,
46., 64., 47., 65., 12., 30., 13., 31., 48., 66., 49.,
67., 14., 32., 15., 33., 50., 68., 51., 69., 16., 34.,
17., 35., 52., 70., 53., 71., 72., 90., 73., 91., 108.,
126., 109., 127., 74., 92., 75., 93., 110., 128., 111., 129.,
76., 94., 77., 95., 112., 130., 113., 131., 78., 96., 79.,
97., 114., 132., 115., 133., 80., 98., 81., 99., 116., 134.,
117., 135., 82., 100., 83., 101., 118., 136., 119., 137., 84.,
102., 85., 103., 120., 138., 121., 139., 86., 104., 87., 105.,
122., 140., 123., 141., 88., 106., 89., 107., 124., 142., 125.,
143.};
test.AddOutput<float>("output", {2, 3, 6, 4}, result);
test.Run();
}
TEST(TensorOpTest, DepthToSpaceTest_5) {
OpTester test("DepthToSpace", 11); // create an opset 11 model with attribute present = "CRD" mode
const int64_t blocksize = 2;
test.AddAttribute("blocksize", blocksize);
test.AddAttribute("mode", "CRD");
const int64_t N = 1, C = 4, H = 2, W = 3;
const std::vector<float> X = {0., 1., 2.,
3., 4., 5.,
9., 10., 11.,
12., 13., 14.,
18., 19., 20.,
21., 22., 23.,
27., 28., 29.,
30., 31., 32.};
test.AddInput<float>("input", {N, C, H, W}, X);
const std::vector<float> result = {0., 9., 1., 10., 2., 11.,
18., 27., 19., 28., 20., 29.,
3., 12., 4., 13., 5., 14.,
21., 30., 22., 31., 23., 32.};
test.AddOutput<float>("output", {1, 1, 4, 6}, result);
test.Run();
}
} // namespace test
} // namespace onnxruntime

2
onnxruntime/test/python/onnx_backend_test_series.py
View file

@ -113,7 +113,6 @@ def create_backend_test(testname=None):
'^test_dynamicquantizelinear_expanded*',
'^test_dynamicquantizelinear_max_adjusted_expanded*',
'^test_dynamicquantizelinear_min_adjusted_expanded*',
'^test_depthtospace*',
'^test_gather_elements*',
'^test_scatter_elements*',
'^test_top_k*',
@ -159,6 +158,7 @@ def create_backend_test(testname=None):
# current_failing_tests = current_failing_tests + ('|^test_operator_repeat_dim_overflow_cpu.*',)
if c2.supports_device('NGRAPH'):
current_failing_tests = current_failing_tests + ('|^test_clip*',)
current_failing_tests = current_failing_tests + ('|^test_depthtospace_crd*',)
filters = current_failing_tests + \
tests_with_pre_opset7_dependencies_filters() + \