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boolean_unmask_ops_test.cc
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boolean_unmask_ops_test.cc
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#include <iostream>
#include <gtest/gtest.h>
#include "caffe2/core/context.h"
#include "caffe2/core/flags.h"
#include "caffe2/core/operator.h"
C10_DECLARE_string(caffe_test_root);
namespace caffe2 {
template <class DataT>
static void AddScalarInput(
const DataT& value,
const string& name,
Workspace* ws,
bool isEmpty = false) {
Blob* blob = ws->CreateBlob(name);
auto* tensor = BlobGetMutableTensor(blob, CPU);
if (!isEmpty) {
tensor->Resize(vector<int64_t>{1});
*(tensor->template mutable_data<DataT>()) = value;
} else {
tensor->Resize(vector<int64_t>{0});
tensor->template mutable_data<DataT>();
}
return;
}
// Test case for BooleanUnmask operator
// mask1: [ false ]
// values1: [ ]
// mask2: [ true ]
// values2: [ 1.0 ]
//
// Expected Output: [ 1.0 ]
TEST(BooleanUnmaskTest, Test) {
Workspace ws;
OperatorDef def;
def.set_name("test");
def.set_type("BooleanUnmask");
def.add_input("mask1");
def.add_input("values1");
def.add_input("mask2");
def.add_input("values2");
def.add_output("unmasked_data");
AddScalarInput(false, "mask1", &ws);
AddScalarInput(float(), "values1", &ws, true);
AddScalarInput(true, "mask2", &ws);
AddScalarInput(1.0f, "values2", &ws);
unique_ptr<OperatorBase> op(CreateOperator(def, &ws));
EXPECT_NE(nullptr, op.get());
EXPECT_TRUE(op->Run());
Blob* unmasked_data_blob = ws.GetBlob("unmasked_data");
EXPECT_NE(nullptr, unmasked_data_blob);
auto& unmasked_data = unmasked_data_blob->Get<TensorCPU>();
EXPECT_EQ(unmasked_data.numel(), 1);
TORCH_CHECK_EQ(unmasked_data.data<float>()[0], 1.0f);
}
} // namespace caffe2