94 : NeonBaseWorkload<SpaceToBatchNdQueueDescriptor>(descriptor, info)
95{
96
98 descriptor.m_Parameters,
99 info,
100 this->GetGuid());
101
102 m_Data.ValidateInputsOutputs("NESpaceToBatchNdWorkload", 1, 1);
103
104 arm_compute::ITensor& input = PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Inputs[0])->GetTensor();
105 arm_compute::ITensor& output = PolymorphicPointerDowncast<IAclTensorHandle>(m_Data.m_Outputs[0])->GetTensor();
106
107 arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
108 input.info()->set_data_layout(aclDataLayout);
109 output.info()->set_data_layout(aclDataLayout);
110
111 arm_compute::TensorInfo aclReshapeInputInfo = BuildArmComputeTensorInfo(
info.m_InputTensorInfos[0],
112 m_Data.m_Parameters.m_DataLayout);
113 arm_compute::TensorInfo aclReshapeOutputInfo = BuildArmComputeTensorInfo(
info.m_OutputTensorInfos[0],
114 m_Data.m_Parameters.m_DataLayout);
115
116 const unsigned int rank =
info.m_InputTensorInfos[0].GetNumDimensions();
117 if (rank == 3)
118 {
119 const arm_compute::TensorShape inputShape = input.info()->tensor_shape();
120 const arm_compute::TensorShape outputShape = output.info()->tensor_shape();
121
122
124 {
125
126 aclReshapeInputInfo.set_tensor_shape({inputShape.x(), 1, inputShape.y(), inputShape.z()});
127 aclReshapeOutputInfo.set_tensor_shape({outputShape.x(), 1, outputShape.y(), outputShape.z()});
128 }
130 {
131
132 aclReshapeInputInfo.set_tensor_shape({1, inputShape.x(), inputShape.y(), inputShape.z()});
133 aclReshapeOutputInfo.set_tensor_shape({1, outputShape.x(), outputShape.y(), outputShape.z()});
134 }
135 else
136 {
137 throw InvalidArgumentException(
"Unsupported or unknown DataLayout",
CHECK_LOCATION());
138 }
139
140 m_ReshapeInputTensor.allocator()->init(aclReshapeInputInfo);
141 m_ReshapeOutputTensor.allocator()->init(aclReshapeOutputInfo);
142
143 InitialiseArmComputeTensorEmpty(m_ReshapeInputTensor);
144 InitialiseArmComputeTensorEmpty(m_ReshapeOutputTensor);
145
146 m_LayerReshapeInput.reset(new arm_compute::NEReshapeLayer());
147 m_LayerReshapeOutput.reset(new arm_compute::NEReshapeLayer());
148
149 m_LayerReshapeInput->configure(&input, &m_ReshapeInputTensor);
150 m_LayerReshapeOutput->configure(&m_ReshapeOutputTensor, &output);
151 }
152
153
155 int32_t blockWidth = (rank == 3) ? 1: armnn::
numeric_cast<int32_t>(descriptor.m_Parameters.m_BlockShape[1]);
156
157 unsigned int padLeft = (rank == 3) ? 0 : descriptor.m_Parameters.m_PadList[1].first;
158 unsigned int padRight = (rank == 3) ? 0 : descriptor.m_Parameters.m_PadList[1].second;
159 arm_compute::Size2D paddingLeftTop = BuildArmComputeSize2D(padLeft,
160 descriptor.m_Parameters.m_PadList[0].first);
161 arm_compute::Size2D paddingRightBottom = BuildArmComputeSize2D(padRight,
162 descriptor.m_Parameters.m_PadList[0].second);
163
164 m_Layer.reset(new arm_compute::NESpaceToBatchLayer());
165 m_Layer->configure((rank == 3) ? &m_ReshapeInputTensor : &input,
166 blockWidth,
167 blockHeight,
168 paddingLeftTop,
169 paddingRightBottom,
170 (rank == 3) ? &m_ReshapeOutputTensor : &output);
171 m_Layer->prepare();
172}
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)