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Fix the instance norm test input size bug in layout infer test (#661) 

Correct gamma and beta size in InstanceNorm.nhwc case

Type: Bug Fix
Issue: 37103

Signed-off-by: Feiyue Chen <Feiyue.Chen@verisilicon.com>
This commit is contained in:
Chen Feiyue 2023-11-22 09:20:27 +08:00 committed by GitHub
parent 74e2740daa
commit 517397949d
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 19 additions and 19 deletions
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38
src/tim/transform/layout_inference_test.cc
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@ -229,30 +229,30 @@ TEST(InstanceNorm, nhwc) {
auto src_graph = ctx->CreateGraph(); auto src_graph = ctx->CreateGraph();
tim::vx::ShapeType io_shape({2, 2, 2, 2}); //nhwc tim::vx::ShapeType io_shape({2, 2, 2, 2}); //nhwc
tim::vx::ShapeType param_shape({1}); tim::vx::ShapeType param_shape({2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::INPUT); io_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32, tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32,
param_shape, tim::vx::TensorAttribute::INPUT); param_shape, tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
io_shape, tim::vx::TensorAttribute::OUTPUT); io_shape, tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = src_graph->CreateTensor(input_spec); auto input_tensor = src_graph->CreateTensor(input_spec);
auto beta_tensor = src_graph->CreateTensor(param_spec); auto beta_tensor = src_graph->CreateTensor(param_spec);
auto gamma_tensor = src_graph->CreateTensor(param_spec); auto gamma_tensor = src_graph->CreateTensor(param_spec);
auto output_tensor = src_graph->CreateTensor(output_spec); auto output_tensor = src_graph->CreateTensor(output_spec);
std::vector<float> in_data = { std::vector<float> in_data = {
0.0f, 1.0f, 0.0f, 2.0f, 0.0f, 2.0f, 0.0f, 4.0f, 1.0f, -1.0f, -1.0f, 2.0f, -1.0f, -2.0f, 1.0f, 4.0f 0.0f, 1.0f, 0.0f, 2.0f, 0.0f, 2.0f, 0.0f, 4.0f, 1.0f, -1.0f, -1.0f, 2.0f, -1.0f, -2.0f, 1.0f, 4.0f
}; };
std::vector<float> beta = {0}; std::vector<float> beta = {0,0};
std::vector<float> gamma = {1.0f}; std::vector<float> gamma = {1.0f,1.0f};
std::vector<float> golden = { std::vector<float> golden = {
0.0f, -1.1470304f, 0.0f, -0.22940612f, 0.0f, -0.22940612f, 0.0f, 1.6058424f, 0.99995005f, 0.0f, -1.1470304f, 0.0f, -0.22940612f, 0.0f, -0.22940612f, 0.0f, 1.6058424f, 0.99995005f,
-0.7337929f, -0.99995005f, 0.52413774f, -0.99995005f, -1.1531031f, 0.99995005f, 1.3627582f, -0.7337929f, -0.99995005f, 0.52413774f, -0.99995005f, -1.1531031f, 0.99995005f, 1.3627582f,
}; };
auto op = src_graph->CreateOperation<tim::vx::ops::InstanceNormalization>(1e-4f, tim::vx::DataLayout::CWHN); auto op = src_graph->CreateOperation<tim::vx::ops::InstanceNormalization>(1e-4f, tim::vx::DataLayout::CWHN);
(*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor}); (*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor});
// Do layout inference // Do layout inference
auto transform = tim::transform::LayoutInference(src_graph, ctx); auto transform = tim::transform::LayoutInference(src_graph, ctx);
auto infer_graph = transform.first; auto infer_graph = transform.first;