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enable exclude outside for resize op (#2203)

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* enable exclude outside for resize mode

* fix centos error

* updates per review + plus more data types for resize

* fix typo in error message

* reset wrong fix
This commit is contained in:
Ashwini Khade 2019-10-21 11:18:33 -07:00 committed by GitHub
parent 3cda9f717b
commit dc5efbf5ce
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GPG key ID: 4AEE18F83AFDEB23
5 changed files with 66 additions and 11 deletions
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9
onnxruntime/core/providers/cpu/cpu_execution_provider.cc
View file

@ -422,6 +422,8 @@ class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain,
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, int32_t_float_float, OneHot);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, int64_t_float_float, OneHot);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, float, Resize);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, int32_t, Resize);
class ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, uint8_t, Resize);
Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
static const BuildKernelCreateInfoFn function_table[] = {
@ -1080,7 +1082,12 @@ Status RegisterOnnxOperatorKernels(KernelRegistry& kernel_registry) {
int32_t_float_float, OneHot)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11,
int64_t_float_float, OneHot)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11, float, Resize)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11,
float, Resize)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11,
int32_t, Resize)>,
BuildKernelCreateInfo<ONNX_OPERATOR_TYPED_KERNEL_CLASS_NAME(kCpuExecutionProvider, kOnnxDomain, 11,
uint8_t, Resize)>,
};
for (auto& function_table_entry : function_table) {

14
onnxruntime/core/providers/cpu/tensor/resize.cc
View file

@ -36,4 +36,18 @@ ONNX_CPU_OPERATOR_TYPED_KERNEL(
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
Resize<float>);
ONNX_CPU_OPERATOR_TYPED_KERNEL(
Resize,
11,
int32_t,
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<int32_t>()),
Resize<int32_t>);
ONNX_CPU_OPERATOR_TYPED_KERNEL(
Resize,
11,
uint8_t,
KernelDefBuilder().TypeConstraint("T", DataTypeImpl::GetTensorType<uint8_t>()),
Resize<uint8_t>);
} // namespace onnxruntime

44
onnxruntime/core/providers/cpu/tensor/upsample.cc
View file

@ -420,6 +420,7 @@ float CubicInterpolation1D(const T* Xdata,
int64_t input_height,
int64_t input_width,
std::array<float, CubicModeGridLength>& coeff_array,
float coeff_sum,
std::unordered_map<int64_t, float>& cache) {
// When calculating cubic interpolation we move the 4*4 grid across the original data and therefore there is
// opportunity to cache the results for previously seen combinations.
@ -434,7 +435,7 @@ float CubicInterpolation1D(const T* Xdata,
float result = 0;
for (int i = 0, j = -1; i < static_cast<int>(CubicModeGridLength); i++, j++) {
auto orig_data = GetDataForCoordinate(Xdata, x + j, y, input_height, input_width);
result += static_cast<float>(coeff_array[i] * orig_data);
result += coeff_array[i]/coeff_sum * orig_data;
}
cache[grid_start_pos] = result;
@ -452,6 +453,7 @@ void ResizeBiCubic(
float cubic_coeff_a,
bool use_extrapolation,
float extrapolation_value,
bool exclude_outside,
const std::vector<float>& roi,
const T* Xdata,
T* Ydata,
@ -494,6 +496,12 @@ void ResizeBiCubic(
}
}
// setup up temp arrays to hold coefficients when exclude_outside is set to true
std::array<float, CubicModeGridLength> y_coeff_holder;
std::array<float, CubicModeGridLength> x_coeff_holder;
float y_coeff_sum = 1;
float x_coeff_sum = 1;
for (int64_t n = 0; n < batch_size; n++) {
for (int64_t c = 0; c < num_channels; c++) {
for (int64_t y = 0; y < output_height; ++y) {
@ -509,7 +517,19 @@ void ResizeBiCubic(
}
auto y_int = static_cast<int64_t>(std::floor(in_y));
auto& coeff_y = cubic_coeffs[in_y - y_int];
auto& coeff_y = exclude_outside ? y_coeff_holder : cubic_coeffs[in_y - y_int];
y_coeff_sum = 1;
if (exclude_outside) {
// When true, the weight of sampling locations outside the grid will be set to 0
// and the weight will be renormalized so that their sum is 1.0
y_coeff_sum = 0;
auto& orig_y_coeffs = cubic_coeffs[in_y - y_int];
for (int64_t i = 0, y_val = y_int - 1; y_val <= y_int + 2; y_val++, i++) {
y_coeff_holder[i] = (y_val < 0 || y_val >= static_cast<float>(input_height)) ? 0.0f : orig_y_coeffs[i];
y_coeff_sum += y_coeff_holder[i];
}
}
for (int64_t x = 0; x < output_width; ++x) {
auto in_x = x_original[x];
@ -523,7 +543,19 @@ void ResizeBiCubic(
auto x_int = static_cast<int64_t>(std::floor(in_x));
auto s_x = static_cast<float>(in_x - x_int);
auto& coeff_x = cubic_coeffs[s_x];
auto& coeff_x = exclude_outside ? x_coeff_holder : cubic_coeffs[s_x];
x_coeff_sum = 1;
if (exclude_outside) {
// When true, the weight of sampling locations outside the grid will be set to 0
// and the weight will be renormalized so that their sum is 1.0
x_coeff_sum = 0;
auto& orig_x_coeff = cubic_coeffs[s_x];
for (int64_t i = 0, x_val = x_int - 1; x_val <= x_int + 2; x_val++, i++) {
x_coeff_holder[i] = (x_val < 0 || x_val >= static_cast<float>(input_width)) ? 0.0f : orig_x_coeff[i];
x_coeff_sum += x_coeff_holder[i];
}
}
// Compute cubic interpolation in x dimension using the x coefficients.
// From the result of cubic interpolation in x dim, compute cubic interpolation in y dimension
@ -531,9 +563,9 @@ void ResizeBiCubic(
float result = 0;
for (int64_t y_val = y_int - 1, i = 0; y_val <= y_int + 2; y_val++, i++) {
auto x_interpolation_result = CubicInterpolation1D(Xdata, x_int, y_val,
input_height, input_width, coeff_x,
input_height, input_width, coeff_x, x_coeff_sum,
interpolation_result_cache);
result += x_interpolation_result * coeff_y[i];
result += x_interpolation_result * coeff_y[i]/y_coeff_sum;
}
Ydata[y * output_width + x] = static_cast<T>(result);
@ -615,7 +647,7 @@ Status Upsample<T>::BaseCompute(OpKernelContext* context, const std::vector<floa
ResizeBiCubic(batch_size, num_channels, input_height, input_width,
is_2D ? scales[0] : scales[2], is_2D ? scales[1] : scales[3], cubic_coeff_a_, use_extrapolation_,
extrapolation_value_, roi, X->template Data<float>(), Y->template MutableData<float>(),
extrapolation_value_, exclude_outside_, roi, X->template Data<float>(), Y->template MutableData<float>(),
get_original_coordinate_);
return Status::OK();
}

4
onnxruntime/core/providers/cpu/tensor/upsample.h
View file

@ -59,6 +59,10 @@ class UpsampleBase {
cubic_coeff_a_ = info.GetAttrOrDefault<float>("cubic_coeff_a", -0.75f);
exclude_outside_ = info.GetAttrOrDefault<int64_t>("exclude_outside", 0) == 0 ? false : true;
if (exclude_outside_ == 1 && mode_ != CUBIC) {
ORT_THROW("exclude_outside can be set to 1 only when mode is CUBIC. Current mode is set to " + mode );
}
// after version 11 update, this optimization is no longer applicable for all the available modes...
// TODO : needs more testing to enable this for version 11
use_nearest2x_optimization = start > 10 ? false : true;

6
onnxruntime/test/onnx/main.cc
View file

@ -429,10 +429,8 @@ int real_main(int argc, char* argv[], Ort::Env& env) {
{"cumsum_1d_reverse_exclusive", "only failing linux GPU CI. Likely build error."},
{"det_2d", "not implemented yet"},
{"det_nd", "not implemented yet"},
{"resize_downsample_scales_cubic_A_n0p5_exclude_outside", "not implemented yet"},
{"resize_downsample_scales_cubic_align_corners", "not implemented yet"},
{"resize_downsample_scales_linear_align_corners", "not implemented yet"},
{"resize_upsample_scales_cubic_A_n0p5_exclude_outside", "not implemented yet"},
{"resize_downsample_scales_cubic_align_corners", "results mismatch with onnx tests"},
{"resize_downsample_scales_linear_align_corners", "results mismatch with onnx tests"},
{"resize_tf_crop_and_resize", "Bad onnx test output. Needs test fix."},
{"resize_upsample_sizes_nearest_ceil_half_pixel", "Bad onnx test output. Needs test fix."},
{"resize_upsample_sizes_nearest_floor_align_corners", "Bad onnx test output. Needs test fix."},