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[TensorRT] Fix BiasAdd with correct axis attribute #13953

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Merged
merged 3 commits into from Feb 11, 2023
Merged

[TensorRT] Fix BiasAdd with correct axis attribute #13953

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20e975b
[TensorRT] Fix BiasAdd with correct axis attribute
Feb 10, 2023
ce67e5c
lint
Feb 10, 2023
7206a18
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Feb 10, 2023
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18 changes: 14 additions & 4 deletions src/runtime/contrib/tensorrt/tensorrt_ops.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -956,7 +956,16 @@ class BiasAddOpConverter : public TensorRTOpConverter {
void Convert(TensorRTOpConverterParams* params) const {
auto input_tensor = params->inputs.at(0).tensor;
auto input_dims = TrtDimsToVector(input_tensor->getDimensions());
const size_t required_rank = TRT_HAS_IMPLICIT_BATCH(params) ? 3 : 4;
size_t required_rank = TRT_HAS_IMPLICIT_BATCH(params) ? 3 : 4;
const size_t input_nbDims = input_tensor->getDimensions().nbDims;
int axis = std::stoi(params->node.GetAttr<std::vector<std::string>>("axis")[0]);
if (axis == -1) {
// Make sure there are 2 dimensions after channel dimension,
if (input_nbDims + 2 > required_rank) required_rank = input_nbDims + 2;
axis = input_nbDims - 1;
} else if (TRT_HAS_IMPLICIT_BATCH(params)) {
axis -= 1;
}
ICHECK(input_dims.size() > 0 && input_dims.size() <= required_rank);
const bool need_reshape_on_input = input_dims.size() != required_rank;
if (need_reshape_on_input) {
Expand All @@ -968,10 +977,11 @@ class BiasAddOpConverter : public TensorRTOpConverter {

const nvinfer1::DataType weight_type = params->inputs.at(1).weight.type;

nvinfer1::Weights shift{weight_type, nullptr, 0};
nvinfer1::Weights scale{weight_type, nullptr, 0};
nvinfer1::Weights power{weight_type, nullptr, 0};
nvinfer1::IScaleLayer* scale_layer = params->network->addScale(
*input_tensor, nvinfer1::ScaleMode::kCHANNEL, params->inputs.at(1).weight, shift, power);
nvinfer1::IScaleLayer* scale_layer =
params->network->addScaleNd(*input_tensor, nvinfer1::ScaleMode::kCHANNEL,
params->inputs.at(1).weight, scale, power, axis);
ICHECK(scale_layer != nullptr);
auto output_tensor = scale_layer->getOutput(0);
if (need_reshape_on_input) {
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5 changes: 3 additions & 2 deletions tests/python/contrib/test_tensorrt.py
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Expand Up @@ -416,15 +416,16 @@ def get_graph(x_shape=(12, 128, 64), y_shape=(12, 128, 64), transa=False, transb


def test_bias_add(run_module):
def get_graph(x_shape=(1, 16), channels=16):
def get_graph(x_shape=(1, 16), channels=16, axis=1):
x = relay.var("x", shape=(x_shape), dtype="float32")
bias = relay.var("bias", shape=(channels,), dtype="float32")
out = relay.nn.bias_add(x, bias)
out = relay.nn.bias_add(x, bias, axis)
f = relay.Function([x, bias], out)
return f, {"x": x_shape, "bias": (channels,)}, ["bias"]

run_and_verify_func(get_graph(), run_module=run_module)
run_and_verify_func(get_graph((1, 6, 3, 4), 6), run_module=run_module)
run_and_verify_func(get_graph((1, 6, 3, 4), 4, -1), run_module=run_module)


def test_pool2d(run_module):
Expand Down