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TEST(ExternalCall, Conv1d_int) {
// A similar test, but now using kInt tensors
BufHandle Input("Input", {1, 100, 115}, kInt);
BufHandle Weight("Weight", {100, 1, 7}, kInt);
BufHandle Bias("Bias", {100}, kInt);
BufHandle ResultBuf("Result", {1, 100, 115}, kInt);
int64_t stride = 1;
int64_t pad = 3;
int64_t dilation = 1;
int64_t groups = 100;
Tensor Result = Tensor(
ResultBuf.node(),
ExternalCall::make(
ResultBuf,
"nnc_aten_conv1d",
{Input, Weight, Bias},
{stride, pad, dilation, groups}));
LoopNest l({Result});
l.prepareForCodegen();
l.simplify();
auto options = at::TensorOptions()
.dtype(at::kInt)
.layout(at::kStrided)
.device(at::kCPU)
.requires_grad(false);
at::Tensor input = at::ones({1, 100, 115}, options) * 5;
at::Tensor weight = at::ones({100, 1, 7}, options) * 6;
at::Tensor bias = at::ones({100}, options) * 11;
at::Tensor ref =
at::conv1d(input, weight, bias, {stride}, {pad}, {dilation}, groups);
at::Tensor nnc_result;
std::vector<int32_t> input_buf(1 * 100 * 115, 5);
std::vector<int32_t> weight_buf(100 * 1 * 7, 6);
std::vector<int32_t> bias_buf(100, 11);
std::vector<int32_t> result_buf(1 * 100 * 115, -1);
#ifdef TORCH_ENABLE_LLVM
LLVMCodeGen llvm_codegen(l.root_stmt(), {Input, Weight, Bias, Result});
llvm_codegen.call({input_buf, weight_buf, bias_buf, result_buf});
nnc_result = at::from_blob(result_buf.data(), {1, 100, 115}, options);
ASSERT_TRUE(at::allclose(nnc_result, ref));
#endif
SimpleIREvaluator ir_eval(l.root_stmt(), {Input, Weight, Bias, Result});
ir_eval.call({input_buf, weight_buf, bias_buf, result_buf});
nnc_result = at::from_blob(result_buf.data(), {1, 100, 115}, options);
ASSERT_TRUE(at::allclose(nnc_result, ref));
}
TEST(ExternalCall, Conv1d_nobias_noargs) {
BufHandle Input("Input", {1, 1, 115}, kFloat);
BufHandle Weight("Weight", {10, 1, 7}, kFloat);
BufHandle ResultBuf("Result", {1, 10, 109}, kFloat);
Tensor Result = Tensor(
ResultBuf.node(),
ExternalCall::make(ResultBuf, "nnc_aten_conv1d", {Input, Weight}, {}));
LoopNest l({Result});
l.prepareForCodegen();
l.simplify();
auto options = at::TensorOptions()
.dtype(at::kFloat)
.layout(at::kStrided)
.device(at::kCPU)
.requires_grad(false);
at::Tensor input = at::ones({1, 1, 115}, options) * 5.f;
at::Tensor weight = at::ones({10, 1, 7}, options) * 6.f;
at::Tensor ref = at::conv1d(input, weight);
at::Tensor nnc_result;
std::vector<float> input_buf(1 * 1 * 115, 5.f);
std::vector<float> weight_buf(10 * 1 * 7, 6.f);
std::vector<float> result_buf(1 * 10 * 109, -1.f);
#ifdef TORCH_ENABLE_LLVM
LLVMCodeGen llvm_codegen(l.root_stmt(), {Input, Weight, Result});
llvm_codegen.call({input_buf, weight_buf, result_buf});
nnc_result = at::from_blob(result_buf.data(), {1, 10, 109}, options);
ASSERT_TRUE(at::allclose(nnc_result, ref));
#endif
SimpleIREvaluator ir_eval(l.root_stmt(), {Input, Weight, Result});
ir_eval.call({input_buf, weight_buf, result_buf});
nnc_result = at::from_blob(result_buf.data(), {1, 10, 109}, options);
ASSERT_TRUE(at::allclose(nnc_result, ref));
}
TEST(ExternalCall, Conv2d_float) {
BufHandle Input("Input", {1, 3, 224, 224}, kFloat);
BufHandle Weight("Weight", {16, 3, 3, 3}, kFloat);
BufHandle Bias("Bias", {16}, kFloat);