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fix: Add int support to constant_pad_nd #1283

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Merged
merged 3 commits into from
Aug 19, 2022
Merged

fix: Add int support to constant_pad_nd #1283

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cf54792
Checkpoint, initial test and implementation
mfeliz-cruise Jun 14, 2022
df24079
Fix error in layer conversion caused by zero/ones tensors of wrong type
mfeliz-cruise Jun 15, 2022
911ab5b
lint
mfeliz-cruise Aug 18, 2022
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19 changes: 6 additions & 13 deletions core/conversion/converters/impl/constant_pad.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,8 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
auto padding = args[1].unwrapToIntList().vec();
int64_t padSize = padding.size();
auto value = args[2].unwrapToScalar().to<float>();

at::Tensor value_tensor = torch::tensor(value, util::TRTDataTypeToScalarType(in->getType()));
auto valueTensor = tensor_to_const(ctx, value_tensor);
TORCHTRT_CHECK(padSize % 2 == 0, "Length of pad must be even but instead it equals " << padSize);

int64_t l_pad = padSize / 2;
Expand Down Expand Up @@ -55,10 +56,8 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
auto fill_layer = ctx->net->addFill(nvinfer1::Dims{1, {1}}, nvinfer1::FillOperation::kLINSPACE);
auto shape_gather_out = ctx->net->addShape(*left_gather_out)->getOutput(0);
fill_layer->setInput(0, *shape_gather_out);
at::Tensor value_tensor = torch::tensor(value, torch::kFloat32);
auto valueTensor = tensor_to_const(ctx, value_tensor);
fill_layer->setInput(1, *valueTensor);
at::Tensor delta_tensor = torch::zeros(inRank);
at::Tensor delta_tensor = torch::zeros(inRank, util::TRTDataTypeToScalarType(in->getType()));
auto deltaTensor = tensor_to_const(ctx, delta_tensor);
fill_layer->setInput(2, *deltaTensor);
auto padTensor = fill_layer->getOutput(0);
Expand All @@ -69,10 +68,8 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
} else {
inDims.d[axis] = padding[padding_index];
auto fill_layer = ctx->net->addFill(inDims, nvinfer1::FillOperation::kLINSPACE);
at::Tensor value_tensor = torch::tensor(value, torch::kFloat32);
auto valueTensor = tensor_to_const(ctx, value_tensor);
fill_layer->setInput(1, *valueTensor);
at::Tensor delta_tensor = torch::zeros(inRank);
at::Tensor delta_tensor = torch::zeros(inRank, util::TRTDataTypeToScalarType(in->getType()));
auto deltaTensor = tensor_to_const(ctx, delta_tensor);
fill_layer->setInput(2, *deltaTensor);
auto padTensor = fill_layer->getOutput(0);
Expand Down Expand Up @@ -112,10 +109,8 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
auto fill_layer = ctx->net->addFill(nvinfer1::Dims{1, {1}}, nvinfer1::FillOperation::kLINSPACE);
auto shape_gather_out = ctx->net->addShape(*right_gather_out)->getOutput(0);
fill_layer->setInput(0, *shape_gather_out);
at::Tensor value_tensor = torch::tensor(value, torch::kFloat32);
auto valueTensor = tensor_to_const(ctx, value_tensor);
fill_layer->setInput(1, *valueTensor);
at::Tensor delta_tensor = torch::zeros(inRank);
at::Tensor delta_tensor = torch::zeros(inRank, util::TRTDataTypeToScalarType(in->getType()));
auto deltaTensor = tensor_to_const(ctx, delta_tensor);
fill_layer->setInput(2, *deltaTensor);
auto padTensor = fill_layer->getOutput(0);
Expand All @@ -126,10 +121,8 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
} else {
inDims.d[axis] = padding[padding_index + 1];
auto fill_layer = ctx->net->addFill(inDims, nvinfer1::FillOperation::kLINSPACE);
at::Tensor value_tensor = torch::tensor(value, torch::kFloat32);
auto valueTensor = tensor_to_const(ctx, value_tensor);
fill_layer->setInput(1, *valueTensor);
at::Tensor delta_tensor = torch::zeros(inRank);
at::Tensor delta_tensor = torch::zeros(inRank, util::TRTDataTypeToScalarType(in->getType()));
auto deltaTensor = tensor_to_const(ctx, delta_tensor);
fill_layer->setInput(2, *deltaTensor);
auto padTensor = fill_layer->getOutput(0);
Expand Down
23 changes: 23 additions & 0 deletions tests/core/conversion/converters/test_constant_pad.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,29 @@ TEST(Converters, ATenConstantPad1dTensorConvertsCorrectly) {
torch_tensorrt::tests::util::almostEqual(jit_results[0], trt_results[0].reshape_as(jit_results[0]), 2e-6));
}

TEST(Converters, ATenConstantPad1dIntTensorConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor):
%1 : int[] = prim::Constant[value=[2, 3]]()
%2 : Scalar = prim::Constant[value=2]()
%3 : Tensor = aten::constant_pad_nd(%0, %1, %2)
return (%3))IR";

auto g = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(graph, g.get());

auto in1 = at::randint(1, 10, {1, 3, 4}, {at::kCUDA}).toType(at::kInt);

auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
auto jit_results = torch_tensorrt::tests::util::RunGraph(g, params, {in1});

params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {});
auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {in1});

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

TEST(Converters, ATenConstantPad1dRightZeroTensorConvertsCorrectly) {
const auto graph = R"IR(
graph(%0 : Tensor):
Expand Down