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Diffstat (limited to 'src/caffe/test/test_deconvolution_layer.cpp')
-rw-r--r--src/caffe/test/test_deconvolution_layer.cpp159
1 files changed, 153 insertions, 6 deletions
diff --git a/src/caffe/test/test_deconvolution_layer.cpp b/src/caffe/test/test_deconvolution_layer.cpp
index fc63d5ef..770e7b27 100644
--- a/src/caffe/test/test_deconvolution_layer.cpp
+++ b/src/caffe/test/test_deconvolution_layer.cpp
@@ -58,8 +58,8 @@ TYPED_TEST(DeconvolutionLayerTest, TestSetup) {
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
- convolution_param->set_kernel_size(3);
- convolution_param->set_stride(2);
+ convolution_param->add_kernel_size(3);
+ convolution_param->add_stride(2);
convolution_param->set_num_output(4);
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
@@ -96,8 +96,8 @@ TYPED_TEST(DeconvolutionLayerTest, TestSimpleDeconvolution) {
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
- convolution_param->set_kernel_size(3);
- convolution_param->set_stride(2);
+ convolution_param->add_kernel_size(3);
+ convolution_param->add_stride(2);
convolution_param->set_num_output(4);
convolution_param->mutable_weight_filler()->set_type("constant");
convolution_param->mutable_weight_filler()->set_value(1);
@@ -144,8 +144,8 @@ TYPED_TEST(DeconvolutionLayerTest, TestGradient) {
layer_param.mutable_convolution_param();
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
- convolution_param->set_kernel_size(2);
- convolution_param->set_stride(1);
+ convolution_param->add_kernel_size(2);
+ convolution_param->add_stride(1);
convolution_param->set_num_output(1);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("gaussian");
@@ -155,4 +155,151 @@ TYPED_TEST(DeconvolutionLayerTest, TestGradient) {
this->blob_top_vec_);
}
+TYPED_TEST(DeconvolutionLayerTest, TestNDAgainst2D) {
+ typedef typename TypeParam::Dtype Dtype;
+ const int kernel_h = 11;
+ const int kernel_w = 13;
+ vector<int> bottom_shape(4);
+ bottom_shape[0] = 15;
+ bottom_shape[1] = 12;
+ bottom_shape[2] = kernel_h * 2;
+ bottom_shape[3] = kernel_w * 2;
+ FillerParameter filler_param;
+ GaussianFiller<Dtype> filler(filler_param);
+ for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {
+ this->blob_bottom_vec_[i]->Reshape(bottom_shape);
+ filler.Fill(this->blob_bottom_vec_[i]);
+ }
+ LayerParameter layer_param;
+ ConvolutionParameter* convolution_param =
+ layer_param.mutable_convolution_param();
+ convolution_param->set_num_output(18);
+ convolution_param->set_bias_term(false);
+ convolution_param->set_group(6);
+ convolution_param->set_kernel_h(kernel_h);
+ convolution_param->set_kernel_w(kernel_w);
+ convolution_param->mutable_weight_filler()->set_type("gaussian");
+ Blob<Dtype> weights;
+ Blob<Dtype> top_diff;
+ // Shape and fill weights and top_diff.
+ bool copy_diff;
+ bool reshape;
+ {
+ DeconvolutionLayer<Dtype> layer(layer_param);
+ layer.SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
+ top_diff.ReshapeLike(*this->blob_top_);
+ filler.Fill(&top_diff);
+ ASSERT_EQ(1, layer.blobs().size());
+ copy_diff = false; reshape = true;
+ weights.CopyFrom(*layer.blobs()[0], copy_diff, reshape);
+ }
+ vector<bool> propagate_down(1, true);
+ Blob<Dtype> result_2d;
+ Blob<Dtype> backward_result_2d;
+ Blob<Dtype> backward_weight_result_2d;
+ // Test with 2D im2col
+ {
+ caffe_set(this->blob_top_->count(), Dtype(0),
+ this->blob_top_->mutable_cpu_data());
+ caffe_set(this->blob_bottom_->count(), Dtype(0),
+ this->blob_bottom_->mutable_cpu_diff());
+ caffe_set(weights.count(), Dtype(0), weights.mutable_cpu_diff());
+ // Do SetUp and Forward; save Forward result in result_2d.
+ convolution_param->set_force_nd_im2col(false);
+ DeconvolutionLayer<Dtype> layer_2d(layer_param);
+ layer_2d.SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
+ ASSERT_EQ(1, layer_2d.blobs().size());
+ copy_diff = false; reshape = false;
+ layer_2d.blobs()[0]->CopyFrom(weights, copy_diff, reshape);
+ layer_2d.Forward(this->blob_bottom_vec_, this->blob_top_vec_);
+ copy_diff = false; reshape = true;
+ result_2d.CopyFrom(*this->blob_top_, copy_diff, reshape);
+ // Copy pre-generated top diff into actual top diff;
+ // do Backward and save result in backward_result_2d.
+ ASSERT_EQ(this->blob_top_->shape(), top_diff.shape());
+ caffe_copy(top_diff.count(), top_diff.cpu_data(),
+ this->blob_top_->mutable_cpu_diff());
+ layer_2d.Backward(this->blob_top_vec_, propagate_down,
+ this->blob_bottom_vec_);
+ copy_diff = true; reshape = true;
+ backward_result_2d.CopyFrom(*this->blob_bottom_, copy_diff, reshape);
+ backward_weight_result_2d.CopyFrom(weights, copy_diff, reshape);
+ }
+ Blob<Dtype> result_nd;
+ Blob<Dtype> backward_result_nd;
+ Blob<Dtype> backward_weight_result_nd;
+ // Test with ND im2col
+ {
+ caffe_set(this->blob_top_->count(), Dtype(0),
+ this->blob_top_->mutable_cpu_data());
+ caffe_set(this->blob_bottom_->count(), Dtype(0),
+ this->blob_bottom_->mutable_cpu_diff());
+ caffe_set(weights.count(), Dtype(0), weights.mutable_cpu_diff());
+ // Do SetUp and Forward; save Forward result in result_nd.
+ convolution_param->set_force_nd_im2col(true);
+ DeconvolutionLayer<Dtype> layer_nd(layer_param);
+ layer_nd.SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
+ ASSERT_EQ(1, layer_nd.blobs().size());
+ copy_diff = false; reshape = false;
+ layer_nd.blobs()[0]->CopyFrom(weights, copy_diff, reshape);
+ layer_nd.Forward(this->blob_bottom_vec_, this->blob_top_vec_);
+ copy_diff = false; reshape = true;
+ result_nd.CopyFrom(*this->blob_top_, copy_diff, reshape);
+ // Copy pre-generated top diff into actual top diff;
+ // do Backward and save result in backward_result_nd.
+ ASSERT_EQ(this->blob_top_->shape(), top_diff.shape());
+ caffe_copy(top_diff.count(), top_diff.cpu_data(),
+ this->blob_top_->mutable_cpu_diff());
+ layer_nd.Backward(this->blob_top_vec_, propagate_down,
+ this->blob_bottom_vec_);
+ copy_diff = true; reshape = true;
+ backward_result_nd.CopyFrom(*this->blob_bottom_, copy_diff, reshape);
+ backward_weight_result_nd.CopyFrom(weights, copy_diff, reshape);
+ }
+ ASSERT_EQ(result_nd.count(), result_2d.count());
+ for (int i = 0; i < result_2d.count(); ++i) {
+ EXPECT_EQ(result_2d.cpu_data()[i], result_nd.cpu_data()[i]);
+ }
+ ASSERT_EQ(backward_result_nd.count(), backward_result_2d.count());
+ for (int i = 0; i < backward_result_2d.count(); ++i) {
+ EXPECT_EQ(backward_result_2d.cpu_diff()[i],
+ backward_result_nd.cpu_diff()[i]);
+ }
+ ASSERT_EQ(backward_weight_result_nd.count(),
+ backward_weight_result_2d.count());
+ for (int i = 0; i < backward_weight_result_2d.count(); ++i) {
+ EXPECT_EQ(backward_weight_result_2d.cpu_diff()[i],
+ backward_weight_result_nd.cpu_diff()[i]);
+ }
+}
+
+TYPED_TEST(DeconvolutionLayerTest, TestGradient3D) {
+ typedef typename TypeParam::Dtype Dtype;
+ vector<int> bottom_shape(5);
+ bottom_shape[0] = this->blob_bottom_vec_[0]->shape(0);
+ bottom_shape[1] = this->blob_bottom_vec_[0]->shape(1);
+ bottom_shape[2] = 2;
+ bottom_shape[3] = 3;
+ bottom_shape[4] = 2;
+ FillerParameter filler_param;
+ GaussianFiller<Dtype> filler(filler_param);
+ for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {
+ this->blob_bottom_vec_[i]->Reshape(bottom_shape);
+ filler.Fill(this->blob_bottom_vec_[i]);
+ }
+ LayerParameter layer_param;
+ ConvolutionParameter* convolution_param =
+ layer_param.mutable_convolution_param();
+ convolution_param->add_kernel_size(2);
+ convolution_param->add_stride(2);
+ convolution_param->add_pad(1);
+ convolution_param->set_num_output(2);
+ convolution_param->mutable_weight_filler()->set_type("gaussian");
+ convolution_param->mutable_bias_filler()->set_type("gaussian");
+ DeconvolutionLayer<Dtype> layer(layer_param);
+ GradientChecker<Dtype> checker(1e-2, 1e-3);
+ checker.CheckGradientExhaustive(&layer, this->blob_bottom_vec_,
+ this->blob_top_vec_);
+}
+
} // namespace caffe
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-14 09:20:23 +0000