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Fixed unreasonable type of parameter in broadcast #505

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Jan 4, 2024
Merged

Fixed unreasonable type of parameter in broadcast #505

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8 changes: 4 additions & 4 deletions include/tim/vx/ops/broadcast.h
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
#ifndef OVXLIBXX_OPERATIONS_BROADCAST_H_
#define OVXLIBXX_OPERATIONS_BROADCAST_H_
#include "tim/vx/builtin_op.h"

#define BROADCAST_OPVERSION 1
namespace tim {
namespace vx {
namespace ops {
Expand All @@ -45,12 +45,12 @@ namespace ops {

class Broadcast : public BuiltinOp {
public:
Broadcast(Graph* graph, const std::vector<int32_t>& shape, const std::vector<int32_t>& dimensions = {});
Broadcast(Graph* graph, const std::vector<uint32_t>& shape, const std::vector<int32_t>& dimensions = {});

std::shared_ptr<Operation> Clone(std::shared_ptr<Graph>& graph) const override;

protected:
const std::vector<int32_t> shape_;
protected:
std::vector<uint32_t> shape_;
std::vector<int32_t> dimensions_;
};

Expand Down
13 changes: 7 additions & 6 deletions src/tim/vx/ops/broadcast.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -30,23 +30,24 @@
namespace tim {
namespace vx {
namespace ops {
Broadcast::Broadcast(Graph* graph, const std::vector<int32_t>& shape,
Broadcast::Broadcast(Graph* graph, const std::vector <uint32_t>& shape,
const std::vector<int32_t>& dimensions)
: BuiltinOp(graph, VSI_NN_OP_EXPAND_BROADCAST),
shape_(shape),
dimensions_(dimensions) {
this->impl()->node()->nn_param.expand_broadcast.dim_num = shape_.size();
this->impl()->node()->nn_param.expand_broadcast.shape = (uint32_t*)shape_.data();
this->impl()->node()->nn_param.expand_broadcast.shape = shape_.data();
#ifdef VSI_EXPAND_BROADCAST_ENABLE_DIMENSIONS
this->impl()->node()->nn_param.expand_broadcast.dimensions_num = dimensions_.size();
if (dimensions.size() > 0)
{
int dim_num = shape.size();
for (uint32_t i = 0; i < dimensions.size(); ++i) {
dimensions_[i] += (dimensions[i] < 0 ? dim_num : 0U);
for (uint32_t i = 0; i < dimensions.size(); i++)
{
dimensions_[i] += (dimensions[i] < 0 ? shape_.size() : 0U );
}
this->impl()->node()->nn_param.expand_broadcast.dimensions = (uint32_t*)dimensions_.data();
} else {
} else
{
this->impl()->node()->nn_param.expand_broadcast.dimensions = nullptr;
}
#endif
Expand Down
56 changes: 47 additions & 9 deletions src/tim/vx/ops/broadcast_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ TEST(Broadcast, ScalarTo2D_2x3) {
std::vector<float> golden = {
2.25f, 2.25f, 2.25f, 2.25f, 2.25f, 2.25f,
};
std::vector<int32_t> shape = {3, 2};
std::vector<uint32_t> shape = {3, 2};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
in_data.size() * sizeof(float)));
Expand Down Expand Up @@ -93,7 +93,7 @@ TEST(Broadcast, 1DTo2D) {
std::vector<float> golden = {
1.f, 2.f, 3.f, 1.f, 2.f, 3.f,
};
std::vector<int32_t> shape = {3, 2};
std::vector<uint32_t> shape = {3, 2};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
in_data.size() * sizeof(float)));
Expand Down Expand Up @@ -125,7 +125,7 @@ TEST(Broadcast, 1DTo2D_WithDims0) {
1.f, 2.f,
1.f, 2.f,
};
std::vector<int32_t> shape = {2, 2};
std::vector<uint32_t> shape = {2, 2};
std::vector<int32_t> dimensions = {0};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down Expand Up @@ -158,7 +158,7 @@ TEST(Broadcast, 1DTo2D_WithDims1) {
1.f, 1.f,
2.f, 2.f,
};
std::vector<int32_t> shape = {2, 2};
std::vector<uint32_t> shape = {2, 2};
std::vector<int32_t> dimensions = {1};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand All @@ -170,6 +170,44 @@ TEST(Broadcast, 1DTo2D_WithDims1) {
CheckResult(graph, golden, output_tensor);
}

TEST(Broadcast, 1DTo2D_WithDimsMinus2) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();

tim::vx::ShapeType input_shape({3});
tim::vx::ShapeType output_shape({3, 2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape,
tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape,
tim::vx::TensorAttribute::OUTPUT);

auto input_tensor = graph->CreateTensor(input_spec);
auto output_tensor = graph->CreateTensor(output_spec);

std::vector<float> in_data = {
1.f, 2.f, 3.f
};
std::vector<float> golden = {
1.f, 2.f, 3.f,
1.f, 2.f, 3.f
};
std::vector<uint32_t> shape = {3, 2};
std::vector<int32_t> dimensions = {-2};
EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
in_data.size() * sizeof(float)));

auto op = graph->CreateOperation<tim::vx::ops::Broadcast>(shape, dimensions);
(*op).BindInputs({input_tensor}).BindOutputs({output_tensor});


EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());

std::vector<float> output(golden.size());
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}

TEST(Broadcast, 1DTo3D_WithDims0) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
Expand All @@ -190,7 +228,7 @@ TEST(Broadcast, 1DTo3D_WithDims0) {
std::vector<float> golden = {
1.f, 2.f, 1.f, 2.f, 1.f, 2.f, 1.f, 2.f,
};
std::vector<int32_t> shape = {2, 2, 2};
std::vector<uint32_t> shape = {2, 2, 2};
std::vector<int32_t> dimensions = {0};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down Expand Up @@ -222,7 +260,7 @@ TEST(Broadcast, 1DTo3D_WithDims1) {
std::vector<float> golden = {
1.f, 1.f, 2.f, 2.f, 1.f, 1.f, 2.f, 2.f,
};
std::vector<int32_t> shape = {2, 2, 2};
std::vector<uint32_t> shape = {2, 2, 2};
std::vector<int32_t> dimensions = {1};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down Expand Up @@ -254,7 +292,7 @@ TEST(Broadcast, 1DTo3D_WithDims2) {
std::vector<float> golden = {
1.f, 1.f, 1.f, 1.f, 2.f, 2.f, 2.f, 2.f,
};
std::vector<int32_t> shape = {2, 2, 2};
std::vector<uint32_t> shape = {2, 2, 2};
std::vector<int32_t> dimensions = {2};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down Expand Up @@ -286,7 +324,7 @@ TEST(Broadcast, 2DTo3D_WithDims02) {
std::vector<float> golden = {
1.f, 5.f, 1.f, 5.f, 2.f, 6.f, 2.f, 6.f,
};
std::vector<int32_t> shape = {2, 2, 2};
std::vector<uint32_t> shape = {2, 2, 2};
std::vector<int32_t> dimensions = {0, 2};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down Expand Up @@ -318,7 +356,7 @@ TEST(Broadcast, 2DTo3D_WithDims12) {
std::vector<float> golden = {
1.f, 1.f, 5.f, 5.f, 2.f, 2.f, 6.f, 6.f,
};
std::vector<int32_t> shape = {2, 2, 2};
std::vector<uint32_t> shape = {2, 2, 2};
std::vector<int32_t> dimensions = {1, 2};

EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(),
Expand Down
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