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feat: Add converter for aten::isfinite #1841

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Merged
merged 1 commit into from
May 30, 2023
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feat: Add converter for aten::isfinite #1841

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20 changes: 20 additions & 0 deletions core/conversion/converters/impl/unary.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -49,6 +49,26 @@ auto logical_not_registration TORCHTRT_UNUSED = RegisterNodeConversionPatterns()
return true;
}});

auto isfinite_registration TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pattern(
{"aten::isfinite(Tensor self) -> Tensor", [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
auto in = args[0].ITensorOrFreeze(ctx);
// assuming x-x = 0 for all values other than nan/inf/-inf where x-x = nan
// x==x for all non-nan values
auto inf_test_layer = ctx->net->addElementWise(*in, *in, nvinfer1::ElementWiseOperation::kSUB);
TORCHTRT_CHECK(inf_test_layer, "Unable to create sub layer from node: " << *n);
inf_test_layer->setName((util::node_info(n) + "_inf_test").c_str());
auto inf_test_tensor = inf_test_layer->getOutput(0);

auto nan_test_layer =
ctx->net->addElementWise(*inf_test_tensor, *inf_test_tensor, nvinfer1::ElementWiseOperation::kEQUAL);
TORCHTRT_CHECK(nan_test_layer, "Unable to create eq layer from node: " << *n);
nan_test_layer->setName((util::node_info(n) + "_nan_test").c_str());

auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], nan_test_layer->getOutput(0));
LOG_DEBUG("Output tensor shape: " << out_tensor->getDimensions());
return true;
}});

#define convert(unary, trt_type) \
auto unary##_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pattern( \
{"aten::" #unary "(Tensor self) -> Tensor", \
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21 changes: 21 additions & 0 deletions tests/core/conversion/converters/test_unary.cpp
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Expand Up @@ -96,6 +96,27 @@ TEST(Converters, ATenLogicalNotBoolConvertsCorrectly) {
ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0], 2e-6));
}

TEST(Converters, ATenFiniteConvertsCorrectly) {
const auto graph = gen_test_graph("isfinite");
auto g = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(graph, g.get());
auto in = at::tensor(
{float(0),
std::nanf(""),
float(2),
std::numeric_limits<float>::infinity(),
float(4),
-std::numeric_limits<float>::infinity()},
{at::kCUDA});
auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
auto jit_results = torch_tensorrt::tests::util::RunGraph(g, params, {in});

params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {in});

ASSERT_TRUE(torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0], 2e-6));
}

#define test_unary(unary, name) \
TEST(Converters, ATen##name##ConvertsCorrectly) { \
const auto graph = gen_test_graph(#unary); \
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