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Merged
merged 1 commit into from
Jan 29, 2021
Merged

Add support for ne layer #300

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64 changes: 64 additions & 0 deletions core/conversion/converters/impl/element_wise.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -260,6 +260,70 @@ auto element_wise_registrations TRTORCH_UNUSED =
LOG_DEBUG("Output tensor shape: " << out->getDimensions());
return true;
}})
.pattern({"aten::ne.Tensor(Tensor self, Tensor other) -> (Tensor)",
[](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
// TODO: Remove with functionalization
auto self = args[0].ITensorOrFreeze(ctx);
auto other = args[1].ITensorOrFreeze(ctx);
auto equal = add_elementwise(
ctx,
nvinfer1::ElementWiseOperation::kEQUAL,
self,
other,
util::node_info(n) + std::string("is_equal"));
TRTORCH_CHECK(equal, "Unable to create elementwise equal layer from node: " << *n);
// XOR with ones negates and produces not_equal result
auto options = torch::TensorOptions().dtype(torch::kFloat32);
auto ones = at::full({1}, 1, {options});
auto ones_tensor = tensor_to_const(ctx, ones);
nvinfer1::IIdentityLayer* cast_layer = ctx->net->addIdentity(*ones_tensor);
cast_layer->setOutputType(0, nvinfer1::DataType::kBOOL);

auto sub = add_elementwise(
ctx,
nvinfer1::ElementWiseOperation::kXOR,
cast_layer->getOutput(0),
equal->getOutput(0),
util::node_info(n));
TRTORCH_CHECK(sub, "Unable to create ne (not equal) layer from node: " << *n);

sub->setName(util::node_info(n).c_str());
auto out = ctx->AssociateValueAndTensor(n->outputs()[0], sub->getOutput(0));
LOG_DEBUG("Not equal layer output tensor shape: " << out->getDimensions());
return true;
}})
.pattern({"aten::ne.Scalar(Tensor self, Scalar other) -> (Tensor)",
[](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
auto self = args[0].ITensorOrFreeze(ctx);
auto scalar = args[1].unwrapToScalar().to<float>();
auto scalar_tensor = tensor_to_const(ctx, torch::tensor({scalar}));
auto equal = add_elementwise(
ctx,
nvinfer1::ElementWiseOperation::kEQUAL,
self,
scalar_tensor,
util::node_info(n) + std::string("is_equal"));
TRTORCH_CHECK(equal, "Unable to create elementwise equal layer from node: " << *n);
// XOR with ones negates and produces not_equal result
auto options = torch::TensorOptions().dtype(torch::kFloat32);
auto ones = at::full({1}, 1, {options});
auto ones_tensor = tensor_to_const(ctx, ones);
nvinfer1::IIdentityLayer* cast_layer = ctx->net->addIdentity(*ones_tensor);
cast_layer->setOutputType(0, nvinfer1::DataType::kBOOL);

auto sub = add_elementwise(
ctx,
nvinfer1::ElementWiseOperation::kXOR,
cast_layer->getOutput(0),
equal->getOutput(0),
util::node_info(n));
TRTORCH_CHECK(sub, "Unable to create ne (not equal) layer from node: " << *n);

sub->setName(util::node_info(n).c_str());
auto out = ctx->AssociateValueAndTensor(n->outputs()[0], sub->getOutput(0));
LOG_DEBUG("Not equal layer output tensor shape: " << out->getDimensions());
return true;
}})
.pattern({"aten::pow.Tensor_Tensor(Tensor self, Tensor exponent) -> (Tensor)",
[](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
// TODO: Remove with functionalization
Expand Down
32 changes: 26 additions & 6 deletions tests/core/conversion/converters/test_element_wise.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,16 @@ TEST(Converters, ATenAddImplicitWithAlphaConvertsCorrectly) {
pointwise_test_helper(graph, false, true, {3, 4, 3}, {4, 3});
}

TEST(Converters, ATenAddWithScalarConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor):
%2 : int = prim::Constant[value=1]()
%scalar : float = prim::Constant[value=2.4]()
%3 : Tensor = aten::add(%0, %scalar, %2)
return (%3))IR";
pointwise_test_helper(graph, true);
}

TEST(Converters, ATenSubConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor, %1 : Tensor):
Expand Down Expand Up @@ -134,12 +144,22 @@ TEST(Converters, ATenPowScalarConvertsCorrectly) {
pointwise_test_helper(graph, true);
}

TEST(Converters, ATenAddWithScalarConvertsCorrectly) {
TEST(Converters, ATenNeTensorConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor):
%2 : int = prim::Constant[value=1]()
%scalar : float = prim::Constant[value=2.4]()
%3 : Tensor = aten::add(%0, %scalar, %2)
graph(%x.1 : Tensor,
%y.1 : Tensor):
%3 : Tensor = aten::ne(%x.1, %y.1)
return (%3))IR";
pointwise_test_helper(graph, true);
pointwise_test_helper(graph, false, false, {3, 4}, {3, 4});
pointwise_test_helper(graph, false, true, {3, 4}, {3, 4});
}

TEST(Converters, ATenNeScalarConvertsCorrectly) {
const auto graph = R"IR(
graph(%x.1 : Tensor):
%2 : int = prim::Constant[value=2]()
%3 : Tensor = aten::ne(%x.1, %2)
return (%3))IR";
pointwise_test_helper(graph, true, false, {3, 4, 2});
;
}