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author
NeiroYT
committed
Changes to tests
1 parent ce4f823 commit 7643258

5 files changed

Lines changed: 38 additions & 22 deletions

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‎src/graph/graph.cpp‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -42,7 +42,7 @@ void Graph::clone(Graph& result, Tensor& out,
4242
result.start_ = this->start_;
4343
result.V_ = this->V_;
4444
result.layers_ = std::vector<std::shared_ptr<Layer>>();
45-
for (int i = 0; i < this->layers_.size(); i++) {
45+
for (size_t i = 0; i < this->layers_.size(); i++) {
4646
result.layers_.push_back(
4747
layer_based_shared_copy(this->layers_[i], options));
4848
}

‎test/benchmarking/test_layers_time.cpp‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -72,8 +72,8 @@ TEST(conv_test, is_conv_stl_ok) {
7272
RuntimeOptions options_stl;
7373
options_stl.par_backend = ParBackend::kTbb;
7474

75-
ConvolutionalLayer p1(1, 1, 2, kernel, Tensor());
76-
ConvolutionalLayer p2(1, 1, 2, kernel, Tensor());
75+
ConvolutionalLayer p1(1, 1, 2, kernel);
76+
ConvolutionalLayer p2(1, 1, 2, kernel);
7777
double count1 = elapsed_time<double, std::milli>(test_func, p1, input, output,
7878
options_seq);
7979
double count2 = elapsed_time<double, std::milli>(test_func, p2, input, output,

‎test/single_layer/test_convlayer.cpp‎

Lines changed: 15 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -442,14 +442,15 @@ TEST(ConvolutionalLayerTest, DepthwiseIntegration) {
442442
std::vector<float> kernelvec(18, 1.0f);
443443
Shape kernel_shape({2, 1, 3, 3});
444444
Tensor kernel = make_tensor(kernelvec, kernel_shape);
445+
Tensor bias;
445446

446447
size_t out_height = (4 + 2 * 1 - 1 * (3 - 1) - 1) / 1 + 1;
447448
size_t out_width = (4 + 2 * 1 - 1 * (3 - 1) - 1) / 1 + 1;
448449
Shape output_shape({1, 2, out_height, out_width});
449450
std::vector<float> output_vec(32, 0.0f);
450451
Tensor output = make_tensor(output_vec, output_shape);
451452

452-
ConvolutionalLayer layer(1, 1, 1, kernel, Tensor(), 2);
453+
ConvolutionalLayer layer(1, 1, 1, kernel, bias, 2);
453454
std::vector<Tensor> in{input};
454455
std::vector<Tensor> out{output};
455456

@@ -570,12 +571,13 @@ TEST(ConvolutionalLayerTest, DepthwiseViaConvolutionalLayer) {
570571
std::vector<float> kernelvec(18, 1.0f);
571572
Shape kernel_shape({2, 1, 3, 3});
572573
Tensor kernel = make_tensor(kernelvec, kernel_shape);
574+
Tensor bias;
573575

574576
Shape output_shape({1, 2, 2, 2});
575577
std::vector<float> output_vec(8, 0.0f);
576578
Tensor output = make_tensor(output_vec, output_shape);
577579

578-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor(), 2);
580+
ConvolutionalLayer layer(1, 0, 1, kernel, bias, 2);
579581
std::vector<Tensor> in{input};
580582
std::vector<Tensor> out{output};
581583
layer.run(in, out);
@@ -603,7 +605,7 @@ TEST_F(ConvTestFixture, Conv4DSTLViaConvolutionalLayer) {
603605
std::vector<float> output_vec(8, 0.0f);
604606
Tensor output = make_tensor(output_vec, output_shape);
605607

606-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor());
608+
ConvolutionalLayer layer(1, 0, 1, kernel);
607609
std::vector<Tensor> in{input};
608610
std::vector<Tensor> out{output};
609611
layer.run(in, out, options);
@@ -685,14 +687,15 @@ TEST(ConvolutionalLayerTest, Conv4DLegacyViaConvolutionalLayer) {
685687
std::vector<float> kernelvec(54, 1.0f);
686688
Shape kernel_shape({3, 3, 3, 2});
687689
Tensor kernel = make_tensor(kernelvec, kernel_shape);
690+
Tensor bias;
688691

689692
size_t out_height = (4 + 2 * 0 - 1 * (3 - 1) - 1) / 1 + 1;
690693
size_t out_width = (4 + 2 * 0 - 1 * (3 - 1) - 1) / 1 + 1;
691694
Shape output_shape({1, 2, out_height, out_width});
692695
std::vector<float> output_vec(8, 0.0f);
693696
Tensor output = make_tensor(output_vec, output_shape);
694697

695-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor(), 1, true);
698+
ConvolutionalLayer layer(1, 0, 1, kernel, bias, 1, true);
696699
std::vector<Tensor> in{input};
697700
std::vector<Tensor> out{output};
698701

@@ -802,14 +805,15 @@ TEST(ConvolutionalLayerTest, DepthwiseConv4DNoBiasIntPathCoverage) {
802805
std::vector<int> kernelvec = {1, 1, 1, 1, 2, 2, 2, 2};
803806
Shape kernel_shape({2, 1, 2, 2});
804807
Tensor kernel = make_tensor(kernelvec, kernel_shape);
808+
Tensor bias;
805809

806810
size_t out_height = (2 + 2 * 0 - 1 * (2 - 1) - 1) / 1 + 1;
807811
size_t out_width = (2 + 2 * 0 - 1 * (2 - 1) - 1) / 1 + 1;
808812
Shape output_shape({1, 2, out_height, out_width});
809813
std::vector<int> output_vec(2, 0);
810814
Tensor output = make_tensor(output_vec, output_shape);
811815

812-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor(), 2);
816+
ConvolutionalLayer layer(1, 0, 1, kernel, bias, 2);
813817
std::vector<Tensor> in{input};
814818
std::vector<Tensor> out{output};
815819

@@ -828,14 +832,15 @@ TEST(ConvolutionalLayerTest, DepthwiseConv4DNoBiasFloatPathCoverage) {
828832
0.5f, 0.5f, 0.5f, 0.5f};
829833
Shape kernel_shape({2, 1, 2, 2});
830834
Tensor kernel = make_tensor(kernelvec, kernel_shape);
835+
Tensor bias;
831836

832837
size_t out_height = (2 + 2 * 0 - 1 * (2 - 1) - 1) / 1 + 1;
833838
size_t out_width = (2 + 2 * 0 - 1 * (2 - 1) - 1) / 1 + 1;
834839
Shape output_shape({1, 2, out_height, out_width});
835840
std::vector<float> output_vec(2, 0.0f);
836841
Tensor output = make_tensor(output_vec, output_shape);
837842

838-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor(), 2);
843+
ConvolutionalLayer layer(1, 0, 1, kernel, bias, 2);
839844
std::vector<Tensor> in{input};
840845
std::vector<Tensor> out{output};
841846

@@ -1051,12 +1056,13 @@ TEST_F(ConvTestFixture, Conv4DWithParallelNoneBackend) {
10511056
std::vector<float> kernelvec(54, 1.0f);
10521057
Shape kernel_shape({2, 3, 3, 3});
10531058
Tensor kernel = make_tensor(kernelvec, kernel_shape);
1059+
Tensor bias;
10541060

10551061
Shape output_shape({1, 2, 2, 2});
10561062
std::vector<float> output_vec(8, 0.0f);
10571063
Tensor output = make_tensor(output_vec, output_shape);
10581064

1059-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor());
1065+
ConvolutionalLayer layer(1, 0, 1, kernel, bias);
10601066
std::vector<Tensor> in{input};
10611067
std::vector<Tensor> out{output};
10621068
layer.run(in, out, defaultOptions);
@@ -1085,7 +1091,7 @@ TEST(ConvolutionalLayerTest, Conv4DWithParallelDefaultFallback) {
10851091
std::vector<float> output_vec(8, 0.0f);
10861092
Tensor output = make_tensor(output_vec, output_shape);
10871093

1088-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor());
1094+
ConvolutionalLayer layer(1, 0, 1, kernel);
10891095
std::vector<Tensor> in{input};
10901096
std::vector<Tensor> out{output};
10911097
layer.run(in, out, options);
@@ -1113,7 +1119,7 @@ TEST_F(ConvTestFixture, Conv4DWithoutParallelFlag) {
11131119
std::vector<float> output_vec(8, 0.0f);
11141120
Tensor output = make_tensor(output_vec, output_shape);
11151121

1116-
ConvolutionalLayer layer(1, 0, 1, kernel, Tensor());
1122+
ConvolutionalLayer layer(1, 0, 1, kernel);
11171123
std::vector<Tensor> in{input};
11181124
std::vector<Tensor> out{output};
11191125
layer.run(in, out, options);

‎test/single_layer_onednn_version/test_convlayer_onednn.cpp‎

Lines changed: 18 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -111,8 +111,9 @@ TEST(convlayer_onednn, grouped_convolution) {
111111

112112
Tensor input = make_tensor(input_data, Shape({1, 4, 6, 6}));
113113
Tensor kernel = make_tensor(kernel_data, Shape({8, 2, 3, 3}));
114+
Tensor bias;
114115

115-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 2);
116+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 2);
116117

117118
Tensor output;
118119
std::vector<Tensor> in{input};
@@ -130,8 +131,9 @@ TEST(convlayer_onednn, depthwise_convolution) {
130131

131132
Tensor input = make_tensor(input_data, Shape({1, 3, 5, 5}));
132133
Tensor kernel = make_tensor(kernel_data, Shape({3, 1, 3, 3}));
134+
Tensor bias;
133135

134-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 3, false);
136+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 3, false);
135137

136138
Tensor output;
137139
std::vector<Tensor> in{input};
@@ -223,7 +225,8 @@ TEST(convlayer_onednn, special_conv_format) {
223225

224226
Tensor input = make_tensor(input_data, Shape({1, 1, 4, 4}));
225227
Tensor kernel = make_tensor(kernel_data, Shape({3, 3, 1, 2}));
226-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 1, true);
228+
Tensor bias;
229+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 1, true);
227230

228231
Tensor output;
229232
std::vector<Tensor> in{input};
@@ -366,7 +369,8 @@ TEST(convlayer_onednn, group_validation_errors) {
366369
{
367370
std::vector<float> kernel_data(4 * 3 * 3 * 3, 1.0f);
368371
Tensor kernel = make_tensor(kernel_data, Shape({4, 3, 3, 3}));
369-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 2);
372+
Tensor bias;
373+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 2);
370374

371375
std::vector<float> input_data(1 * 5 * 6 * 6, 1.0f);
372376
Tensor input = make_tensor(input_data, Shape({1, 5, 6, 6}));
@@ -379,7 +383,8 @@ TEST(convlayer_onednn, group_validation_errors) {
379383
{
380384
std::vector<float> kernel_data(6 * 3 * 3 * 3, 1.0f);
381385
Tensor kernel = make_tensor(kernel_data, Shape({6, 3, 3, 3}));
382-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 2);
386+
Tensor bias;
387+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 2);
383388

384389
std::vector<float> input_data(1 * 4 * 6 * 6, 1.0f);
385390
Tensor input = make_tensor(input_data, Shape({1, 4, 6, 6}));
@@ -394,8 +399,9 @@ TEST(convlayer_onednn, group_validation_errors) {
394399
TEST(convlayer_onednn, depthwise_kernel_shape_validation) {
395400
std::vector<float> kernel_data(3 * 2 * 3 * 3, 1.0f);
396401
Tensor kernel = make_tensor(kernel_data, Shape({3, 2, 3, 3}));
402+
Tensor bias;
397403

398-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 3, false);
404+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 3, false);
399405

400406
std::vector<float> input_data(1 * 3 * 5 * 5, 1.0f);
401407
Tensor input = make_tensor(input_data, Shape({1, 3, 5, 5}));
@@ -484,8 +490,9 @@ TEST(convlayer_onednn, int_kernel_processing) {
484490
0, 1, 0, 0, 1, 0, 0, 1, 0};
485491

486492
Tensor kernel = make_tensor(kernel_data, Shape({3, 3, 1, 2}));
493+
Tensor bias;
487494

488-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 1, true);
495+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 1, true);
489496

490497
std::vector<int> input_data(1 * 1 * 4 * 4, 1);
491498
Tensor input = make_tensor(input_data, Shape({1, 1, 4, 4}));
@@ -504,8 +511,9 @@ TEST(convlayer_onednn, int_kernel_processing) {
504511
TEST(convlayer_onednn, special_conv_diagnostics) {
505512
std::vector<float> kernel_data(3 * 3 * 64 * 128, 1.0f);
506513
Tensor kernel = make_tensor(kernel_data, Shape({3, 3, 64, 128}));
514+
Tensor bias;
507515

508-
ConvLayerOneDnn layer(2, 1, 2, kernel, Tensor(), 1, true);
516+
ConvLayerOneDnn layer(2, 1, 2, kernel, bias, 1, true);
509517

510518
std::vector<float> input_data(1 * 64 * 8 * 8, 1.0f);
511519
Tensor input = make_tensor(input_data, Shape({1, 64, 8, 8}));
@@ -525,8 +533,9 @@ TEST(convlayer_onednn, special_conv_diagnostics) {
525533
TEST(convlayer_onednn, int_input_processing_special_conv) {
526534
std::vector<int> kernel_data(3 * 3 * 1 * 2, 1);
527535
Tensor kernel = make_tensor(kernel_data, Shape({3, 3, 1, 2}));
536+
Tensor bias;
528537

529-
ConvLayerOneDnn layer(1, 0, 1, kernel, Tensor(), 1, true);
538+
ConvLayerOneDnn layer(1, 0, 1, kernel, bias, 1, true);
530539

531540
std::vector<int> input_data(1 * 1 * 4 * 4, 2);
532541
Tensor input = make_tensor(input_data, Shape({1, 1, 4, 4}));

‎test/single_layer_parall_version/test_convlayer_parall.cpp‎

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -111,14 +111,15 @@ TEST(convlayer_parall, parallel_depthwise_conv) {
111111
std::vector<float> kernelvec(32 * 1 * 3 * 3, 1.0f);
112112
Shape kernel_shape({32, 1, 3, 3});
113113
Tensor kernel = make_tensor(kernelvec, kernel_shape);
114+
Tensor bias;
114115

115116
size_t out_height = (56 + 2 * 1 - 1 * (3 - 1) - 1) / 1 + 1;
116117
size_t out_width = (56 + 2 * 1 - 1 * (3 - 1) - 1) / 1 + 1;
117118
Shape output_shape({batch_size, 32, out_height, out_width});
118119
std::vector<float> output_vec(batch_size * 32 * out_height * out_width, 0.0f);
119120
Tensor output = make_tensor(output_vec, output_shape);
120121

121-
ConvolutionalLayer layer(1, 1, 1, kernel, Tensor(), 32);
122+
ConvolutionalLayer layer(1, 1, 1, kernel, bias, 32);
122123
std::vector<Tensor> in{input};
123124
std::vector<Tensor> out{output};
124125

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