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Rashuai/fix dilation (#415)

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* test with conv

* add dilation to shape inferencing

* add test cases

* add test cases
This commit is contained in:
Randy 2019-02-04 23:28:27 -08:00 committed by Pranav Sharma
parent 696ab8a194
commit 2062c49033
3 changed files with 147 additions and 6 deletions
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16
onnxruntime/core/providers/cpu/nn/conv_transpose.cc
View file

@ -31,6 +31,7 @@ inline void ComputeTransposePadAndOutputShape(
const int64_t in_size,
const int64_t stride,
const int64_t kernel,
const int64_t dilation,
const int64_t adj,
AutoPadType pad_type,
int64_t* pad_head,
@ -39,7 +40,7 @@ inline void ComputeTransposePadAndOutputShape(
if (*out_size != -1) {
ORT_ENFORCE(*out_size >= 0);
// total padding size
int64_t paddings = std::max<int64_t>(0, (in_size - 1) * stride + kernel + adj - *out_size);
int64_t paddings = std::max<int64_t>(0, (in_size - 1) * stride + kernel + dilation - 1 + adj - *out_size);
if (pad_type == AutoPadType::SAME_UPPER) { // pad more on head when paddings are odd.
*pad_head = paddings - paddings / 2;
*pad_tail = paddings / 2;
@ -61,14 +62,14 @@ inline void ComputeTransposePadAndOutputShape(
case AutoPadType::SAME_LOWER:
*pad_head = 0;
*pad_tail = 0;
*out_size = (in_size - 1) * stride + kernel + adj;
*out_size = (in_size - 1) * stride + kernel + dilation - 1 + adj;
break;
default:
throw NotImplementedException("pad type not supported");
}
} else {
*out_size =
(in_size - 1) * stride + kernel + adj - *pad_head - *pad_tail;
(in_size - 1) * stride + kernel + dilation - 1 + adj - *pad_head - *pad_tail;
}
}
}
@ -144,7 +145,7 @@ Status ConvTransposeBase::PrepareForCompute(OpKernelContext* context, bool has_b
std::vector<int64_t> Y_dims;
ComputePadsAndOutputShape(input_shape, num_output_channels, kernel_shape, strides, output_padding, &pads, &Y_dims);
ComputePadsAndOutputShape(input_shape, num_output_channels, kernel_shape, strides, dilations, output_padding, &pads, &Y_dims);
TensorShape Yshape(Y_dims);
Tensor* Y = context->Output(0, Yshape);
@ -169,6 +170,7 @@ void ConvTransposeBase::ComputePadsAndOutputShape(
const int64_t output_channel,
const std::vector<int64_t>& kernel_shape,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& dilations,
const std::vector<int64_t>& output_padding,
std::vector<int64_t>* pads,
std::vector<int64_t>* output_shape) const {
@ -189,6 +191,7 @@ void ConvTransposeBase::ComputePadsAndOutputShape(
H,
strides[0],
kernel_shape[0],
dilations[0],
output_padding[0],
auto_pad_,
&pads->at(0),
@ -199,6 +202,7 @@ void ConvTransposeBase::ComputePadsAndOutputShape(
W,
strides[1],
kernel_shape[1],
dilations[1],
output_padding[1],
auto_pad_,
&pads->at(1),
@ -256,8 +260,8 @@ Status ConvTranspose<T>::Compute(OpKernelContext* context) const {
p.Y->Shape()[3],
p.kernel_shape[0],
p.kernel_shape[1],
1,
1,
p.dilations[0],
p.dilations[1],
p.pads[0],
p.pads[1],
p.pads[2],

1
onnxruntime/core/providers/cpu/nn/conv_transpose.h
View file

@ -52,6 +52,7 @@ class ConvTransposeBase : public ConvBase {
const int64_t output_channel,
const std::vector<int64_t>& kernel_shape,
const std::vector<int64_t>& strides,
const std::vector<int64_t>& dilations,
const std::vector<int64_t>& output_padding,
std::vector<int64_t>* pads,
std::vector<int64_t>* output_shape) const;

136
onnxruntime/test/providers/cpu/nn/conv_transpose_op_test.cc
View file

@ -15,6 +15,7 @@ struct ConvTransposeOpAttributes {
vector<int64_t> output_shape;
vector<int64_t> pads;
vector<int64_t> strides;
vector<int64_t> dilations;
int64_t group;
};
@ -35,6 +36,7 @@ void TestConvTransposeOp(const ConvTransposeOpAttributes& attributes,
}
test.AddAttribute("pads", attributes.pads);
test.AddAttribute("strides", attributes.strides);
test.AddAttribute("dilations", attributes.dilations);
test.AddAttribute("group", attributes.group);
ORT_ENFORCE(inputs.size() <= 3, "Our name array is only setup to handle 3 inputs");
@ -54,6 +56,7 @@ TEST(ConvTransposeTest, ConvTranspose_1) {
{}, // output_shape
vector<int64_t>{1, 1, 1, 1}, // pads
vector<int64_t>{2, 2}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.16857791f, -0.15161794f, 0.08540368f,
@ -81,6 +84,7 @@ TEST(ConvTransposeTest, ConvTranspose_Bias_1) {
{}, // output_shape
vector<int64_t>{1, 1, 1, 1}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.22572887f, -0.07105902f, -0.40399021f, -0.14461157f, 0.05367219f,
@ -111,6 +115,7 @@ TEST(ConvTransposeTest, ConvTranspose_Bias_2) {
{}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.01270282f, 0.09657472f, -0.36909008f, -0.08085269f,
@ -158,6 +163,7 @@ TEST(ConvTransposeTest, ConvTranspose_Output_Shape) {
vector<int64_t>{1, 3, 4, 4}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
int image_size = 4 * 4;
@ -197,6 +203,7 @@ TEST(ConvTransposeTest, ConvTranspose_Output_Shape2) {
vector<int64_t>{1, 1, 1, 14}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f};
@ -217,6 +224,7 @@ TEST(ConvTransposeTest, ConvTranspose_Output_Shape_Batch) {
vector<int64_t>{2, 1, 1, 14}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
@ -239,6 +247,7 @@ TEST(ConvTransposeTest, ConvTranspose_Invalid_Kernel_Shape) {
vector<int64_t>{2, 1, 1, 14}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
@ -263,6 +272,7 @@ TEST(ConvTransposeTest, ConvTranspose_onnx) {
{}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0., 1., 2., 3., 4., 5., 6., 7., 8.};
@ -292,6 +302,7 @@ TEST(ConvTransposeTest, ConvTranspose_onnx2) {
{}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
1 // group
};
vector<float> X = {0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17.};
@ -323,6 +334,7 @@ TEST(ConvTransposeTest, ConvTranspose_onnx_group) {
{}, // output_shape
vector<int64_t>{0, 0, 0, 0}, // pads
vector<int64_t>{1, 1}, // strides
vector<int64_t>{1, 1}, // dilations
4 // group
};
vector<float> X = {0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 6.f, 7.f, 8.f, 9.f, 10.f, 11.f, 12.f, 13.f, 14.f, 15.f};
@ -334,5 +346,129 @@ TEST(ConvTransposeTest, ConvTranspose_onnx_group) {
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
TEST(ConvTransposeTest, ConvTranspose2D_group_dilation2) {
ConvTransposeOpAttributes attrs = {
vector<int64_t>{2, 2},
{}, {},
vector<int64_t>{0,0,0,0},
vector<int64_t>{1,1},
{2,2},
1
};
vector<float> X = {11.0f,12.0f,21.0f,22.0f};
vector<int64_t> X_shape = {1,1,2,2};
vector<float> W = {1.0f,1.0f,1.0f,1.0f};
vector<int64_t> W_shape = {1,1,2,2};
vector<int64_t> Y_shape = {1,1,4,4};
auto expected_vals = {11.0f,12.0f,11.0f,12.0f,
21.0f,22.0f,21.0f,22.0f,
11.0f,12.0f,11.0f,12.0f,
21.0f,22.0f,21.0f,22.0f};
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
TEST(ConvTransposeTest, ConvTranspose2D_group_dilation3) {
ConvTransposeOpAttributes attrs = {
vector<int64_t>{2, 2},
{}, {},
vector<int64_t>{0,0,0,0},
vector<int64_t>{1,1},
{3,3},
1
};
vector<float> X = {11.0f,12.0f,21.0f,22.0f};
vector<int64_t> X_shape = {1,1,2,2};
vector<float> W = {1.0f,1.0f,1.0f,1.0f};
vector<int64_t> W_shape = {1,1,2,2};
vector<int64_t> Y_shape = {1,1,5,5};
auto expected_vals = {11.0f,12.0f,0.0f,11.0f,12.0f,
21.0f,22.0f,0.0f,21.0f,22.0f,
0.0f, 0.0f, 0.0f,0.0f, 0.0f,
11.0f,12.0f,0.0f,11.0f,12.0f,
21.0f,22.0f,0.0f,21.0f,22.0f};
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
TEST(ConvTransposeTest, ConvTranspose3D_group_dilation2) {
ConvTransposeOpAttributes attrs = {
vector<int64_t>{2, 2},
{}, {},
vector<int64_t>{0,0,0,0,0,0,0,0,0},
vector<int64_t>{1,1,1},
{2,2},
1
};
vector<float> X = {3.0f,8.0f,1.0f,9.0f,5.0f,7.0f,3.0f,2.0f,6.0f};
vector<int64_t> X_shape = {1,1,3,3};
vector<float> W = {7.0f,2.0f,1.0f,9.0f};
vector<int64_t> W_shape = {1,1,2,2};
vector<int64_t> Y_shape = {1,1,5,5};
auto expected_vals = {21.0f, 56.0f, 13.0f, 16.0f, 2.0f,
63.0f, 35.0f, 67.0f, 10.0f, 14.0f,
24.0f, 22.0f, 76.0f, 76.0f, 21.0f,
9.0f, 5.0f, 88.0f, 45.0f, 63.0f,
3.0f, 2.0f, 33.0f, 18.0f, 54.0f};
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
TEST(ConvTransposeTest, ConvTranspose3D_group_dilation3) {
ConvTransposeOpAttributes attrs = {
vector<int64_t>{2, 2},
{}, {},
vector<int64_t>{0,0,0,0,0,0,0,0,0},
vector<int64_t>{1,1,1},
{3,3},
1
};
vector<float> X = {3.0f,8.0f,1.0f,9.0f,5.0f,7.0f,3.0f,2.0f,6.0f};
vector<int64_t> X_shape = {1,1,3,3};
vector<float> W = {7.0f,2.0f,1.0f,9.0f};
vector<int64_t> W_shape = {1,1,2,2};
vector<int64_t> Y_shape = {1,1,6,6};
auto expected_vals = {21.0f, 56.0f, 7.0f, 6.0f, 16.0f, 2.0f,
63.0f, 35.0f, 49.0f, 18.0f, 10.0f, 14.0f,
21.0f, 14.0f, 42.0f, 6.0f, 4.0f, 12.0f,
3.0f, 8.0f, 1.0f, 27.0f, 72.0f, 9.0f,
9.0f, 5.0f, 7.0f, 81.0f, 45.0f, 63.0f,
3.0f, 2.0f, 6.0f, 27.0f, 18.0f, 54.0f};
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
TEST(ConvTransposeTest, ConvTranspose3D_group2_dilation2) {
ConvTransposeOpAttributes attrs = {
vector<int64_t>{2, 2},
{}, {},
vector<int64_t>{0,0,0,0,0,0,0,0,0},
vector<int64_t>{1,1,1},
{2,2},
2
};
vector<float> X = {3.0f,8.0f,1.0f,9.0f,5.0f,7.0f,3.0f,2.0f,3.0f,7.0f,9.0f,1.0f,5.0f,2.0f,3.0f,9.0f,0.0f,2.0f};
vector<int64_t> X_shape = {1,2,3,3};
vector<float> W = {9.0f,3.0f,1.0f,2.0f,3.0f,7.0f,0.0f,8.0f};
vector<int64_t> W_shape = {2,1,2,2};
vector<int64_t> Y_shape = {1,2,5,5};
auto expected_vals = {27.0f, 72.0f, 18.0f, 24.0f, 3.0f,
81.0f, 45.0f, 90.0f, 15.0f, 21.0f,
30.0f, 26.0f, 43.0f, 22.0f, 11.0f,
9.0f, 5.0f, 25.0f, 10.0f, 14.0f,
3.0f, 2.0f, 9.0f, 4.0f, 6.0f,
21.0f, 27.0f, 52.0f, 63.0f, 7.0f,
15.0f, 6.0f, 44.0f, 14.0f, 21.0f,
27.0f, 0.0f, 125.0f, 72.0f, 22.0f,
0.0f, 0.0f, 40.0f, 16.0f, 24.0f,
0.0f, 0.0f, 72.0f, 0.0f, 16.0f};
TestConvTransposeOp(attrs, {X, W}, {X_shape, W_shape}, expected_vals, Y_shape);
}
} // namespace test
} // namespace onnxruntime