1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5
6 #include "NeonStridedSliceWorkload.hpp"
7
8 #include "NeonWorkloadUtils.hpp"
9 #include <neon/NeonTensorHandle.hpp>
10 #include <aclCommon/ArmComputeUtils.hpp>
11 #include <aclCommon/ArmComputeTensorUtils.hpp>
12 #include <armnn/utility/NumericCast.hpp>
13 #include <armnn/utility/PolymorphicDowncast.hpp>
14 #include <backendsCommon/WorkloadUtils.hpp>
15
16 namespace armnn
17 {
18
NeonStridedSliceWorkloadValidate(const TensorInfo & input,const TensorInfo & output,const StridedSliceDescriptor & descriptor)19 arm_compute::Status NeonStridedSliceWorkloadValidate(const TensorInfo& input,
20 const TensorInfo& output,
21 const StridedSliceDescriptor& descriptor)
22 {
23 const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);
24 const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
25
26 arm_compute::Coordinates starts;
27 arm_compute::Coordinates ends;
28 arm_compute::Coordinates strides;
29
30 std::tie(starts, ends, strides) = SetNeonStridedSliceData(descriptor.m_Begin,
31 descriptor.m_End,
32 descriptor.m_Stride);
33
34 auto numDimensions = armnn::numeric_cast<int>(input.GetNumDimensions());
35 int32_t begin_mask = ConvertMaskToACLFormat(descriptor.m_BeginMask, numDimensions);
36 int32_t end_mask = ConvertMaskToACLFormat(descriptor.m_EndMask, numDimensions);
37 int32_t shrink_axis_mask = ConvertMaskToACLFormat(descriptor.m_ShrinkAxisMask, numDimensions);
38
39 return arm_compute::NEStridedSlice::validate(&aclInput,
40 &aclOutput,
41 starts,
42 ends,
43 strides,
44 begin_mask,
45 end_mask,
46 shrink_axis_mask);
47 }
48
NeonStridedSliceWorkload(const StridedSliceQueueDescriptor & descriptor,const WorkloadInfo & info)49 NeonStridedSliceWorkload::NeonStridedSliceWorkload(const StridedSliceQueueDescriptor& descriptor,
50 const WorkloadInfo& info)
51 : BaseWorkload<StridedSliceQueueDescriptor>(descriptor, info)
52 {
53 m_Data.ValidateInputsOutputs("NeonStridedSliceWorkload", 1, 1);
54
55 arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
56 arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
57
58 arm_compute::Coordinates starts;
59 arm_compute::Coordinates ends;
60 arm_compute::Coordinates strides;
61
62 std::tie(starts, ends, strides) = SetNeonStridedSliceData(m_Data.m_Parameters.m_Begin,
63 m_Data.m_Parameters.m_End,
64 m_Data.m_Parameters.m_Stride);
65
66 auto numDimensions = armnn::numeric_cast<int>(info.m_InputTensorInfos[0].GetNumDimensions());
67 int32_t begin_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_BeginMask, numDimensions);
68 int32_t end_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_EndMask, numDimensions);
69 int32_t shrink_axis_mask = ConvertMaskToACLFormat(m_Data.m_Parameters.m_ShrinkAxisMask, numDimensions);
70
71 arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
72 input.info()->set_data_layout(aclDataLayout);
73 output.info()->set_data_layout(aclDataLayout);
74
75 auto layer = std::make_unique<arm_compute::NEStridedSlice>();
76
77 layer->configure(&input,
78 &output,
79 starts,
80 ends,
81 strides,
82 begin_mask,
83 end_mask,
84 shrink_axis_mask);
85 m_Layer.reset(layer.release());
86 }
87
Execute() const88 void NeonStridedSliceWorkload::Execute() const
89 {
90 ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonStridedSliceWorkload_Execute");
91 m_Layer->run();
92 }
93
94 } //namespace armnn