| 37 | } |
| 38 | |
| 39 | bool setup(const arm_compute::utils::CommonGraphParams &common_params, |
| 40 | const arm_compute::utils::SimpleOption<std::string> &expected_output_filename) |
| 41 | { |
| 42 | using namespace arm_compute; |
| 43 | using namespace arm_compute::graph; |
| 44 | using namespace arm_compute::utils; |
| 45 | using namespace arm_compute::graph_utils; |
| 46 | |
| 47 | const auto &data_path = common_params.data_path; |
| 48 | const auto &target = common_params.target; |
| 49 | |
| 50 | NodeID id_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.add_node<ConstNode>(TensorDescriptor{ |
| 51 | TensorShape{12, 2, 2, 3}, DataType::QASYMM8, QuantizationInfo(0.00393533194437623, 1), DataLayout::NHWC}); |
| 52 | INode *node_upscale_net_FakeQuantWithMinMaxVars_transposed = |
| 53 | _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_transposed); |
| 54 | node_upscale_net_FakeQuantWithMinMaxVars_transposed->set_common_node_parameters( |
| 55 | NodeParams{"upscale_net_FakeQuantWithMinMaxVars_transposed", target}); |
| 56 | node_upscale_net_FakeQuantWithMinMaxVars_transposed->output(0)->set_accessor(get_weights_accessor( |
| 57 | data_path, "/cnn_data/edsr_model/upscale_net_FakeQuantWithMinMaxVars_transposed.npy", DataLayout::NHWC)); |
| 58 | |
| 59 | NodeID id_pre_upscale_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ |
| 60 | TensorShape{12}, DataType::S32, QuantizationInfo(2.9644968435604824e-06), DataLayout::NHWC}); |
| 61 | INode *node_pre_upscale_Conv2D_bias = _graph.node(id_pre_upscale_Conv2D_bias); |
| 62 | node_pre_upscale_Conv2D_bias->set_common_node_parameters(NodeParams{"pre_upscale_Conv2D_bias", target}); |
| 63 | node_pre_upscale_Conv2D_bias->output(0)->set_accessor( |
| 64 | get_weights_accessor(data_path, "/cnn_data/edsr_model/pre_upscale_Conv2D_bias.npy", DataLayout::NHWC)); |
| 65 | |
| 66 | NodeID id_pre_upscale_FakeQuantWithMinMaxVars = |
| 67 | _graph.add_node<ConstNode>(TensorDescriptor{TensorShape{256, 3, 3, 12}, DataType::QASYMM8, |
| 68 | QuantizationInfo(0.000455576169770211, 128), DataLayout::NHWC}); |
| 69 | INode *node_pre_upscale_FakeQuantWithMinMaxVars = _graph.node(id_pre_upscale_FakeQuantWithMinMaxVars); |
| 70 | node_pre_upscale_FakeQuantWithMinMaxVars->set_common_node_parameters( |
| 71 | NodeParams{"pre_upscale_FakeQuantWithMinMaxVars", target}); |
| 72 | node_pre_upscale_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( |
| 73 | data_path, "/cnn_data/edsr_model/pre_upscale_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); |
| 74 | |
| 75 | NodeID id_post_residual_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ |
| 76 | TensorShape{256}, DataType::S32, QuantizationInfo(1.2760000345224398e-06), DataLayout::NHWC}); |
| 77 | INode *node_post_residual_Conv2D_bias = _graph.node(id_post_residual_Conv2D_bias); |
| 78 | node_post_residual_Conv2D_bias->set_common_node_parameters(NodeParams{"post_residual_Conv2D_bias", target}); |
| 79 | node_post_residual_Conv2D_bias->output(0)->set_accessor( |
| 80 | get_weights_accessor(data_path, "/cnn_data/edsr_model/post_residual_Conv2D_bias.npy", DataLayout::NHWC)); |
| 81 | |
| 82 | NodeID id_post_residual_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( |
| 83 | TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, |
| 84 | QuantizationInfo(0.00036424631252884865, 129), DataLayout::NHWC}); |
| 85 | INode *node_post_residual_FakeQuantWithMinMaxVars = _graph.node(id_post_residual_FakeQuantWithMinMaxVars); |
| 86 | node_post_residual_FakeQuantWithMinMaxVars->set_common_node_parameters( |
| 87 | NodeParams{"post_residual_FakeQuantWithMinMaxVars", target}); |
| 88 | node_post_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( |
| 89 | data_path, "/cnn_data/edsr_model/post_residual_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); |
| 90 | |
| 91 | NodeID id_mul_15_y = _graph.add_node<ConstNode>(TensorDescriptor{ |
| 92 | TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); |
| 93 | INode *node_mul_15_y = _graph.node(id_mul_15_y); |
| 94 | node_mul_15_y->set_common_node_parameters(NodeParams{"mul_15_y", target}); |
| 95 | node_mul_15_y->output(0)->set_accessor( |
| 96 | get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_15_y.npy", DataLayout::NHWC)); |
no test coverage detected