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#include "caffe2/core/init.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/utils/math.h"
#include "caffe2/utils/proto_utils.h"
#include "gtest/gtest.h"
#include <cmath>
#include <random>
namespace caffe2 {
namespace {
void AddNoiseInput(const vector<int64_t>& shape, const string& name, Workspace* ws) {
DeviceOption option;
CPUContext context(option);
Blob* blob = ws->CreateBlob(name);
auto* tensor = BlobGetMutableTensor(blob, CPU);
tensor->Resize(shape);
math::RandGaussian<float, CPUContext>(
tensor->size(), 0.0f, 3.0f, tensor->mutable_data<float>(), &context);
for (auto i = 0; i < tensor->size(); ++i) {
tensor->mutable_data<float>()[i] =
std::min(-5.0f, std::max(5.0f, tensor->mutable_data<float>()[i]));
}
}
void compareResizeNeareast(int N,
int C,
int H,
int W,
float wscale,
float hscale) {
Workspace ws;
OperatorDef def1;
def1.set_name("test");
def1.set_type("ResizeNearest");
def1.add_input("X");
def1.add_output("Y");
def1.add_arg()->CopyFrom(MakeArgument("width_scale", wscale));
def1.add_arg()->CopyFrom(MakeArgument("height_scale", hscale));
AddNoiseInput(vector<int64_t>{N, C, H, W}, "X", &ws);
unique_ptr<OperatorBase> op1(CreateOperator(def1, &ws));
EXPECT_NE(nullptr, op1.get());
EXPECT_TRUE(op1->Run());
const auto& X = ws.GetBlob("X")->Get<TensorCPU>();
const auto& Y = ws.GetBlob("Y")->Get<TensorCPU>();
const float* Xdata = X.data<float>();
const float* Ydata = Y.data<float>();
int outW = W * wscale;
int outH = H * hscale;
// Compare all output points
for (int n = 0; n < N; ++n) {
for (int c = 0; c < C; ++c) {
for (int ph = 0; ph < outH; ++ph) {
const int iny = std::min((int)(ph / hscale), (H - 1));
for (int pw = 0; pw < outW; ++pw) {
const int inx = std::min((int)(pw / wscale), (W - 1));
const float v = Xdata[iny * W + inx];
EXPECT_EQ(Ydata[outW * ph + pw], v);
}
}
Xdata += H * W;
Ydata += outW * outH;
}
}
}
int randInt(int a, int b) {
static std::random_device rd;
static std::mt19937 gen(rd());
return std::uniform_int_distribution<int>(a, b)(gen);
}
TEST(ResizeNearestOp, ResizeNearest2x) {
for (auto i = 0; i < 40; ++i) {
auto H = randInt(1, 100);
auto W = randInt(1, 100);
auto C = randInt(1, 10);
auto N = randInt(1, 2);
compareResizeNeareast(N, C, H, W, 2.0f, 2.0f);
}
}
} // unnamed namespace
} // namespace caffe2
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