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#include <gtest/gtest.h>
#include <torch/csrc/jit/mobile/nnc/context.h>
#include <torch/csrc/jit/mobile/nnc/registry.h>
#include <ATen/Functions.h>
namespace torch {
namespace jit {
namespace mobile {
namespace nnc {
extern "C" {
// out = a * n (doing calculation in the `tmp` buffer)
int slow_mul_kernel(void** args) {
const int size = 128;
at::Tensor a = at::from_blob(args[0], {size}, at::kFloat);
at::Tensor out = at::from_blob(args[1], {size}, at::kFloat);
at::Tensor n = at::from_blob(args[2], {1}, at::kInt);
at::Tensor tmp = at::from_blob(args[3], {size}, at::kFloat);
tmp.zero_();
for (int i = n.item().toInt(); i > 0; i--) {
tmp.add_(a);
}
out.copy_(tmp);
return 0;
}
int dummy_kernel(void** /* args */) {
return 0;
}
} // extern "C"
REGISTER_NNC_KERNEL("slow_mul", slow_mul_kernel)
REGISTER_NNC_KERNEL("dummy", dummy_kernel)
InputSpec create_test_input_spec(const std::vector<int64_t>& sizes) {
InputSpec input_spec;
input_spec.sizes_ = sizes;
input_spec.dtype_ = at::kFloat;
return input_spec;
}
OutputSpec create_test_output_spec(const std::vector<int64_t>& sizes) {
OutputSpec output_spec;
output_spec.sizes_ = sizes;
output_spec.dtype_ = at::kFloat;
return output_spec;
}
MemoryPlan create_test_memory_plan(const std::vector<int64_t>& buffer_sizes) {
MemoryPlan memory_plan;
memory_plan.buffer_sizes_ = buffer_sizes;
return memory_plan;
}
TEST(Function, ExecuteSlowMul) {
const int a = 999;
const int n = 100;
const int size = 128;
Function f;
f.set_nnc_kernel_id("slow_mul");
f.set_input_specs({create_test_input_spec({size})});
f.set_output_specs({create_test_output_spec({size})});
f.set_parameters(c10::impl::toList(c10::List<at::Tensor>({
at::ones({1}, at::kInt).mul(n)
})));
f.set_memory_plan(create_test_memory_plan({sizeof(float) * size}));
c10::List<at::Tensor> input({
at::ones({size}, at::kFloat).mul(a)
});
auto outputs = f.run(c10::impl::toList(input));
auto output = ((const c10::IValue&) outputs[0]).toTensor();
auto expected_output = at::ones({size}, at::kFloat).mul(a * n);
EXPECT_TRUE(output.equal(expected_output));
}
TEST(Function, Serialization) {
Function f;
f.set_name("test_function");
f.set_nnc_kernel_id("test_kernel");
f.set_input_specs({create_test_input_spec({1, 3, 224, 224})});
f.set_output_specs({create_test_output_spec({1000})});
f.set_parameters(c10::impl::toList(c10::List<at::Tensor>({
at::ones({1, 16, 3, 3}, at::kFloat),
at::ones({16, 32, 1, 1}, at::kFloat),
at::ones({32, 1, 3, 3}, at::kFloat)
})));
f.set_memory_plan(create_test_memory_plan({
sizeof(float) * 1024,
sizeof(float) * 2048,
}));
auto serialized = f.serialize();
Function f2(serialized);
EXPECT_EQ(f2.name(), "test_function");
EXPECT_EQ(f2.nnc_kernel_id(), "test_kernel");
EXPECT_EQ(f2.input_specs().size(), 1);
EXPECT_EQ(f2.input_specs()[0].sizes_, std::vector<int64_t>({1, 3, 224, 224}));
EXPECT_EQ(f2.input_specs()[0].dtype_, at::kFloat);
EXPECT_EQ(f2.output_specs().size(), 1);
EXPECT_EQ(f2.output_specs()[0].sizes_, std::vector<int64_t>({1000}));
EXPECT_EQ(f2.output_specs()[0].dtype_, at::kFloat);
EXPECT_EQ(f2.parameters().size(), 3);
EXPECT_EQ(f2.parameters()[0].toTensor().sizes(), at::IntArrayRef({1, 16, 3, 3}));
EXPECT_EQ(f2.parameters()[1].toTensor().sizes(), at::IntArrayRef({16, 32, 1, 1}));
EXPECT_EQ(f2.parameters()[2].toTensor().sizes(), at::IntArrayRef({32, 1, 3, 3}));
EXPECT_EQ(f2.memory_plan().buffer_sizes_.size(), 2);
EXPECT_EQ(f2.memory_plan().buffer_sizes_[0], sizeof(float) * 1024);
EXPECT_EQ(f2.memory_plan().buffer_sizes_[1], sizeof(float) * 2048);
}
TEST(Function, ValidInput) {
const int size = 128;
Function f;
f.set_nnc_kernel_id("dummy");
f.set_input_specs({create_test_input_spec({size})});
c10::List<at::Tensor> input({
at::ones({size}, at::kFloat)
});
// NOLINTNEXTLINE(cppcoreguidelines-avoid-goto,hicpp-avoid-goto)
EXPECT_NO_THROW(
f.run(c10::impl::toList(input)));
}
TEST(Function, InvalidInput) {
const int size = 128;
Function f;
f.set_nnc_kernel_id("dummy");
f.set_input_specs({create_test_input_spec({size})});
c10::List<at::Tensor> input({
at::ones({size * 2}, at::kFloat)
});
// NOLINTNEXTLINE(cppcoreguidelines-avoid-goto,hicpp-avoid-goto)
EXPECT_THROW(
f.run(c10::impl::toList(input)),
c10::Error);
}
} // namespace nnc
} // namespace mobile
} // namespace jit
} // namespace torch
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