TYPED_TEST(CuDNNConvolutionLayerTest, TestSimpleConvolutionCuDNN) {
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
convolution_param->add_kernel_size(3);
convolution_param->add_stride(2);
convolution_param->set_num_output(4);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("constant");
convolution_param->mutable_bias_filler()->set_value(0.1);
shared_ptr<Layer<TypeParam> > layer(
new CuDNNConvolutionLayer<TypeParam>(layer_param));
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);
// Check against reference convolution.
const TypeParam* top_data;
const TypeParam* ref_top_data;
caffe_conv(this->blob_bottom_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_));
top_data = this->blob_top_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
caffe_conv(this->blob_bottom_2_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_2_));
top_data = this->blob_top_2_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
}
TYPED_TEST(MKLDNNConvolutionLayerTest, TestSimple3DConvolution) {
typedef typename TypeParam::Dtype Dtype;
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
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] = 5;
bottom_shape[3] = this->blob_bottom_vec_[0]->shape(2);
bottom_shape[4] = this->blob_bottom_vec_[0]->shape(3);
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(3);
convolution_param->add_stride(2);
convolution_param->set_num_output(4);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("gaussian");
shared_ptr<Layer<Dtype> > layer(
new MKLDNNConvolutionLayer<Dtype>(layer_param));
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);
// Check against reference convolution.
const Dtype* top_data;
const Dtype* ref_top_data;
caffe_conv(this->blob_bottom_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_));
top_data = this->blob_top_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
#if 0 // TODO: improve conv so that it runs on all buffers in bottom vector
caffe_conv(this->blob_bottom_2_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_2_));
top_data = this->blob_top_2_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
#endif
}
TYPED_TEST(MKLDNNConvolutionLayerTest, TestSimpleConvolutionReLUGroup) {
typedef typename TypeParam::Dtype Dtype;
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
convolution_param->add_kernel_size(3);
convolution_param->add_stride(2);
convolution_param->set_num_output(OC);
convolution_param->set_relu(true);
convolution_param->set_group(GR);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("constant");
convolution_param->mutable_bias_filler()->set_value(0.1);
shared_ptr<Layer<Dtype> > layer(
new MKLDNNConvolutionLayer<Dtype>(layer_param));
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);
// Check against reference convolution.
const Dtype* top_data;
const Dtype* ref_top_data;
caffe_conv(this->blob_bottom_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_));
top_data = this->blob_top_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
}
TYPED_TEST(ConvolutionLayerTest, TestDilatedConvolution) {
typedef typename TypeParam::Dtype Dtype;
vector<int> bottom_shape;
bottom_shape.push_back(2);
bottom_shape.push_back(3);
bottom_shape.push_back(8);
bottom_shape.push_back(7);
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
for (int i = 0; i < this->blob_bottom_vec_.size(); ++i) {
this->blob_bottom_vec_[i]->Reshape(bottom_shape);
}
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
convolution_param->add_kernel_size(3);
convolution_param->add_dilation(2);
convolution_param->set_num_output(4);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("constant");
convolution_param->mutable_bias_filler()->set_value(0.1);
shared_ptr<Layer<Dtype> > layer(
new ConvolutionLayer<Dtype>(layer_param));
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);
// Check against reference convolution.
const Dtype* top_data;
const Dtype* ref_top_data;
caffe_conv(this->blob_bottom_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_));
top_data = this->blob_top_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
caffe_conv(this->blob_bottom_2_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_2_));
top_data = this->blob_top_2_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
}
TYPED_TEST(MKLDNNConvolutionLayerTest, TestSimpleConvolutionMKLDNN) {
typedef typename TypeParam::Dtype Dtype;
this->blob_bottom_vec_.push_back(this->blob_bottom_2_);
this->blob_top_vec_.push_back(this->blob_top_2_);
LayerParameter layer_param;
ConvolutionParameter* convolution_param =
layer_param.mutable_convolution_param();
convolution_param->add_kernel_size(KH);
convolution_param->add_stride(CS);
convolution_param->set_num_output(OC);
convolution_param->add_pad(PD);
convolution_param->mutable_weight_filler()->set_type("gaussian");
convolution_param->mutable_bias_filler()->set_type("constant");
convolution_param->mutable_bias_filler()->set_value(0.1);
shared_ptr<Layer<Dtype> > layer(
new MKLDNNConvolutionLayer<Dtype>(layer_param));
layer->SetUp(this->blob_bottom_vec_, this->blob_top_vec_);
layer->Forward(this->blob_bottom_vec_, this->blob_top_vec_);
// Check against reference convolution.
const Dtype* top_data;
const Dtype* ref_top_data;
caffe_conv(this->blob_bottom_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_));
top_data = this->blob_top_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
#if 0 // TODO: improve conv so that it runs on all buffers in bottom vector
caffe_conv(this->blob_bottom_2_, convolution_param, layer->blobs(),
this->MakeReferenceTop(this->blob_top_2_));
top_data = this->blob_top_2_->cpu_data();
ref_top_data = this->ref_blob_top_->cpu_data();
for (int i = 0; i < this->blob_top_->count(); ++i) {
EXPECT_NEAR(top_data[i], ref_top_data[i], 1e-4);
}
#endif
}
