filler_param.set_value(1.);
ConstantFiller<TypeParam> filler(filler_param);
filler.Fill(this->blob_bottom_);
+ TypeParam* bottom_data = this->blob_bottom_->mutable_cpu_data();
+ for (int n = 0; n < this->blob_bottom_->num(); ++n) {
+ for (int c = 0; c < this->blob_bottom_->channels(); ++c) {
+ for (int h = 0; h < this->blob_bottom_->height(); ++h) {
+ for (int w = 0; w < this->blob_bottom_->width(); ++w) {
+ bottom_data[this->blob_bottom_->offset(n, c, h, w)] = c;
+ }
+ }
+ }
+ }
LayerParameter layer_param;
layer_param.set_kernelsize(3);
layer_param.set_stride(2);
layer->Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
// After the convolution, the output should all have output values 9.1
const TypeParam* top_data = this->blob_top_->cpu_data();
- for (int i = 0; i < this->blob_top_->count(); ++i) {
- EXPECT_GE(top_data[i], 9.1 - 1e-4);
- EXPECT_LE(top_data[i], 9.1 + 1e-4);
+ for (int n = 0; n < this->blob_top_->num(); ++n) {
+ for (int c = 0; c < this->blob_top_->channels(); ++c) {
+ for (int h = 0; h < this->blob_top_->height(); ++h) {
+ for (int w = 0; w < this->blob_top_->width(); ++w) {
+ TypeParam data = top_data[this->blob_top_->offset(n, c, h, w)];
+ EXPECT_GE(data, c * 9 + 0.1 - 1e-4);
+ EXPECT_LE(data, c * 9 + 0.1 + 1e-4);
+ }
+ }
+ }
}
// Test GPU
Caffe::set_mode(Caffe::GPU);
layer->Forward(this->blob_bottom_vec_, &(this->blob_top_vec_));
// After the convolution, the output should all have output values 9.1
top_data = this->blob_top_->cpu_data();
- for (int i = 0; i < this->blob_top_->count(); ++i) {
- EXPECT_GE(top_data[i], 9.1 - 1e-4);
- EXPECT_LE(top_data[i], 9.1 + 1e-4);
+ for (int n = 0; n < this->blob_top_->num(); ++n) {
+ for (int c = 0; c < this->blob_top_->channels(); ++c) {
+ for (int h = 0; h < this->blob_top_->height(); ++h) {
+ for (int w = 0; w < this->blob_top_->width(); ++w) {
+ TypeParam data = top_data[this->blob_top_->offset(n, c, h, w)];
+ EXPECT_GE(data, c * 9 + 0.1 - 1e-4);
+ EXPECT_LE(data, c * 9 + 0.1 + 1e-4);
+ }
+ }
+ }
}
}