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Align AvgPool ceil_mode on last value to torch #16752

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Merged
titaiwangms merged 8 commits into from
Jan 24, 2025
Merged

Align AvgPool ceil_mode on last value to torch #16752

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d2880f3
align ceil_mode on last value to torch
titaiwangms Jul 18, 2023
da2feec
Merge branch 'main' into titaiwang/fix_avgpool_ceil_mode_and_pads
titaiwangms Jul 18, 2023
f650a32
add f
titaiwangms Jul 19, 2023
369c635
add the change to 2d and 3d
titaiwangms Jul 19, 2023
d9664d9
Merge branch 'main' into titaiwang/fix_avgpool_ceil_mode_and_pads
titaiwangms Jan 17, 2025
1ec9cad
Merge branch 'main' into titaiwang/fix_avgpool_ceil_mode_and_pads
titaiwangms Jan 21, 2025
c84a858
update ceil_mode
titaiwangms Jan 23, 2025
488321a
move the broken test to general category
titaiwangms Jan 23, 2025
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3 changes: 3 additions & 0 deletions onnxruntime/core/providers/cpu/nn/pool_functors.h
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Original file line number Diff line number Diff line change
Expand Up @@ -406,6 +406,7 @@ struct AveragePool1DTask final {
for (int64_t ph = 0; ph < pooled_height; ++ph) {
int64_t hstart = ph * stride_h - pads[0];
int64_t hend = hstart + kernel_shape[0] * dilation_h;
hend = std::min(hend, height + pads[1]);
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y_d[ph] = 0;
int total_elements = 0;
for (int64_t h = hstart; h < hend; h += dilation_h) {
Expand Down Expand Up @@ -461,6 +462,7 @@ struct AveragePool2DTask final {
for (int64_t ph = 0; ph < pooled_height; ++ph) {
int64_t hstart = ph * stride_h - pads[0];
int64_t hend = hstart + kernel_shape[0] * dilation_h;
hend = std::min(hend, height + pads[1]);
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for (int64_t pw = 0; pw < pooled_width; ++pw) {
int64_t wstart = pw * stride_w - pads[1];
int64_t wend = wstart + kernel_shape[1] * dilation_w;
Expand Down Expand Up @@ -532,6 +534,7 @@ struct AveragePool3DTask {
for (int64_t ph = 0; ph < pooled_height; ++ph) {
int64_t hstart = ph * stride_h - pads[0];
int64_t hend = hstart + kernel_shape[0] * dilation_h;
hend = std::min(hend, height + pads[1]);
for (int64_t pw = 0; pw < pooled_width; ++pw) {
int64_t wstart = pw * stride_w - pads[1];
int64_t wend = wstart + kernel_shape[1] * dilation_w;
Expand Down
25 changes: 25 additions & 0 deletions onnxruntime/test/providers/cpu/nn/pool_op_test.cc
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Expand Up @@ -967,6 +967,31 @@ TEST(PoolTest, AveragePool_19_dilation_2d) {
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kAclExecutionProvider, kOpenVINOExecutionProvider});
}

TEST(PoolTest, AveragePool_19_ceil_count_include_pad_1d) {
// TODO: Unskip when fixed #41968513
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if (DefaultDmlExecutionProvider().get() != nullptr) {
GTEST_SKIP() << "Skipping because of the following error: MLOperatorAuthorImpl.cpp(2100): The parameter is incorrect.";
}

OpTester test("AveragePool", 19);

test.AddAttribute("auto_pad", "");
test.AddAttribute("strides", std::vector<int64_t>{3});
test.AddAttribute("pads", vector<int64_t>{3, 3});
test.AddAttribute("kernel_shape", vector<int64_t>{7});
test.AddAttribute("ceil_mode", (int64_t)1);
test.AddAttribute("count_include_pad", (int64_t)1);

std::vector<float> x_vals = {2.0903, 4.6493, 1.6320, -3.2051, 4.6975, 4.7296, 3.3653, -1.5815, -2.3832, 0.9628, -1.5899, -2.6820, 5.7529, 7.7346, -0.8910, -2.0151, 0.1313, -0.5374};
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std::vector<int64_t> x_dims = {1, 2, 9};
std::vector<int64_t> expected_dims = {1, 2, 4};
std::vector<float> expected_vals = {0.73807144, 2.5655572, 0.8032287, -0.09990001, 0.34911433, 1.0389, 1.4536142, -0.40353334};

test.AddInput<float>("X", x_dims, x_vals);
test.AddOutput<float>("Y", expected_dims, expected_vals);
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kTensorrtExecutionProvider, kAclExecutionProvider, kOpenVINOExecutionProvider});
}

TEST(PoolTest, GlobalAveragePool) {
OpTester test("GlobalAveragePool");

Expand Down