Compute Library
 22.08
Integration_OperatorFuseMovenetSubGraph1.cpp File Reference

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Namespaces

 arm_compute
 Copyright (c) 2017-2022 Arm Limited.
 
 arm_compute::test
 
 arm_compute::test::validation
 

Functions

 TEST_CASE (Operator_Fuse_Movenet_SubGraph_1_F32, framework::DatasetMode::ALL)
 
 TEST_CASE (DataType_QASYMM8, framework::DatasetMode::ALL)
 
 TEST_CASE (DataLayout_NCHW, framework::DatasetMode::ALL)
 
 TEST_SUITE_END () FIXTURE_DATA_TEST_CASE(RunSmall = ActivationValidationQuantizedFixture<CLTensor, CLAccessor, CLActivationLayer, T>
 [CLActivationLayer Test snippet] More...
 
 add_op_conv2d (op_graph, conv2d_desc, op_t_l0_input, op_t_l0_weight, op_t_l0_dst)
 
 add_op_conv2d (op_graph, conv2d_desc, op_t_l0_dst, op_t_l1_weight, op_t_dst)
 
 ARM_COMPUTE_EXPECT (!bool(success), framework::LogLevel::ERRORS)
 
 ARM_COMPUTE_EXPECT (!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS)
 
 TEST_CASE (Enlarging_Execution_Space, framework::DatasetMode::ALL)
 
 TEST_CASE (Root_Simple_And_Complex, framework::DatasetMode::ALL)
 
 TEST_CASE (Loop, framework::DatasetMode::ALL)
 

Variables

const auto t_l0_input_shape = TensorShape(1024, 56, 56)
 
const auto t_l0_weight_shape = TensorShape(512, 1024, 1, 1)
 
const auto t_l1_weight_shape = TensorShape(512, 256, 1, 1)
 
auto t_l0_input_info = TensorInfo(t_l0_input_shape, 1, data_type, data_layout)
 
auto t_l0_weight_info = TensorInfo(t_l0_weight_shape, 1, data_type, data_layout)
 
auto t_l1_weight_info = TensorInfo(t_l1_weight_shape, 1, data_type, data_layout)
 
auto t_l0_dst_info = TensorInfo()
 
auto t_dst_info = TensorInfo()
 
OperatorGraph op_graph
 
const auto conv2d_desc = Conv2dDescriptor{}
 
const auto op_t_l0_input = add_tensor(op_graph, t_l0_input_info)
 
const auto op_t_l0_weight = add_tensor(op_graph, t_l0_weight_info)
 
const auto op_t_l1_weight = add_tensor(op_graph, t_l1_weight_info)
 
const auto op_t_l0_dst = add_tensor(op_graph, t_l0_dst_info)
 
const auto op_t_dst = add_tensor(op_graph, t_dst_info)
 
const ClWorkloadContext workload_ctx { GpuInfo{ CLScheduler::get().target() } }
 
ClWorkload workload
 
const auto success = build(workload, op_graph, workload_ctx)