Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2020 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Finn Williams | 6f9f990 | 2020-11-13 13:23:15 +0000 | [diff] [blame] | 8 | #include <armnn/utility/IgnoreUnused.hpp> |
| 9 | |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 10 | #include <tensorflow/lite/builtin_ops.h> |
| 11 | #include <tensorflow/lite/c/builtin_op_data.h> |
| 12 | #include <tensorflow/lite/c/common.h> |
| 13 | #include <tensorflow/lite/minimal_logging.h> |
| 14 | |
| 15 | namespace armnnDelegate |
| 16 | { |
| 17 | |
| 18 | TfLiteStatus VisitSliceOperator(DelegateData& delegateData, |
| 19 | TfLiteContext* tfLiteContext, |
| 20 | TfLiteNode* tfLiteNode, |
| 21 | int nodeIndex, |
| 22 | int32_t sliceOperatorCode) |
| 23 | { |
Jan Eilers | 2ffddda | 2021-02-03 09:14:30 +0000 | [diff] [blame] | 24 | TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex)); |
| 25 | TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex)); |
Finn Williams | 6f9f990 | 2020-11-13 13:23:15 +0000 | [diff] [blame] | 26 | |
Jan Eilers | 2ffddda | 2021-02-03 09:14:30 +0000 | [diff] [blame] | 27 | // Read inputs [input, begin, end, strides] |
| 28 | int numInputs = tfLiteNode->inputs->size; |
| 29 | std::vector<const TfLiteTensor*> tfLiteInputs; |
| 30 | tfLiteInputs.reserve(numInputs); |
| 31 | const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors; |
| 32 | for (int i = 0; i < numInputs; i++) |
| 33 | { |
| 34 | const TfLiteTensor* inputTensor = &tfLiteTensors[tfLiteNode->inputs->data[i]]; |
| 35 | tfLiteInputs.push_back(inputTensor); |
| 36 | if (!IsValid(tfLiteContext, *inputTensor, sliceOperatorCode, nodeIndex)) |
| 37 | { |
| 38 | return kTfLiteError; |
| 39 | } |
| 40 | } |
| 41 | |
| 42 | // We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs |
| 43 | int inputRank = tfLiteInputs[0]->dims->size; |
| 44 | auto ReadInt32Input = [&](int inputIndex, std::vector<int32_t>& outputData) -> TfLiteStatus |
| 45 | { |
| 46 | if (tfLiteInputs[inputIndex]->type != kTfLiteInt32) |
| 47 | { |
| 48 | TF_LITE_MAYBE_KERNEL_LOG( |
| 49 | tfLiteContext, |
| 50 | "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " |
| 51 | "be of type int32. Operator: #%d node #%d: ", |
| 52 | sliceOperatorCode, nodeIndex); |
| 53 | return kTfLiteError; |
| 54 | } |
| 55 | int rank = tfLiteInputs[inputIndex]->dims->size; |
| 56 | if (rank != 1) |
| 57 | { |
| 58 | TF_LITE_MAYBE_KERNEL_LOG( |
| 59 | tfLiteContext, |
| 60 | "TfLiteArmnnDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need to " |
| 61 | "be a 1D-Tensor. Operator: #%d node #%d: ", |
| 62 | sliceOperatorCode, nodeIndex); |
| 63 | return kTfLiteError; |
| 64 | } |
| 65 | int numValues = tfLiteInputs[inputIndex]->dims->data[0]; |
| 66 | if (numValues != inputRank) |
| 67 | { |
| 68 | TF_LITE_MAYBE_KERNEL_LOG( |
| 69 | tfLiteContext, |
| 70 | "TfLiteArmnnDelegate: The number of values in the Begin-, End- and Stride-Tensors of the " |
| 71 | "StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ", |
| 72 | sliceOperatorCode, nodeIndex); |
| 73 | return kTfLiteError; |
| 74 | } |
| 75 | // return tensor data |
| 76 | auto* tensorDataPtr = tflite::GetTensorData<int32_t>(tfLiteInputs[inputIndex]); |
| 77 | outputData.assign(tensorDataPtr, tensorDataPtr+numValues); |
| 78 | return kTfLiteOk; |
| 79 | }; |
| 80 | |
| 81 | std::vector<int32_t> beginData; |
| 82 | if (ReadInt32Input(1, beginData) != kTfLiteOk) |
| 83 | return kTfLiteError; |
| 84 | std::vector<int32_t> endData; |
| 85 | if (ReadInt32Input(2, endData) != kTfLiteOk) |
| 86 | return kTfLiteError; |
| 87 | std::vector<int32_t> strideData; |
| 88 | if (ReadInt32Input(3, strideData) != kTfLiteOk) |
| 89 | return kTfLiteError; |
| 90 | |
| 91 | // parse built in options |
| 92 | auto* stridedSliceParams = reinterpret_cast<TfLiteStridedSliceParams*>(tfLiteNode->builtin_data); |
| 93 | |
| 94 | // Write all data to the descriptor |
| 95 | armnn::StridedSliceDescriptor descriptor; |
| 96 | descriptor.m_Begin = std::move(beginData); |
| 97 | descriptor.m_End = std::move(endData); |
| 98 | descriptor.m_Stride = std::move(strideData); |
| 99 | descriptor.m_BeginMask = stridedSliceParams->begin_mask; |
| 100 | descriptor.m_EllipsisMask = stridedSliceParams->ellipsis_mask; |
| 101 | descriptor.m_EndMask = stridedSliceParams->end_mask; |
| 102 | descriptor.m_NewAxisMask = stridedSliceParams->new_axis_mask; |
| 103 | descriptor.m_ShrinkAxisMask = stridedSliceParams->shrink_axis_mask; |
| 104 | descriptor.m_DataLayout = armnn::DataLayout::NHWC; |
| 105 | |
| 106 | // Validate output |
| 107 | const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]]; |
| 108 | if (!IsValid(tfLiteContext, tfLiteOutputTensor, sliceOperatorCode, nodeIndex)) |
| 109 | { |
| 110 | return kTfLiteError; |
| 111 | } |
| 112 | |
| 113 | const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(*tfLiteInputs[0]); |
| 114 | const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor); |
| 115 | |
| 116 | bool isSupported = false; |
| 117 | auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported) |
| 118 | { |
| 119 | FORWARD_LAYER_SUPPORT_FUNC(__func__, |
| 120 | tfLiteContext, |
| 121 | IsStridedSliceSupported, |
| 122 | delegateData.m_Backends, |
| 123 | isSupported, |
| 124 | inputTensorInfo, |
| 125 | outInfo, |
| 126 | descriptor); |
| 127 | }; |
| 128 | |
| 129 | if (!delegateData.m_Network) |
| 130 | { |
| 131 | validateFunc(outputTensorInfo, isSupported); |
| 132 | return isSupported ? kTfLiteOk : kTfLiteError; |
| 133 | } |
| 134 | |
| 135 | // Add a StridedSlice layer |
| 136 | armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor); |
| 137 | ARMNN_ASSERT(layer != nullptr); |
| 138 | |
| 139 | armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0); |
| 140 | outputSlot.SetTensorInfo(outputTensorInfo); |
| 141 | |
| 142 | // Connect |
| 143 | return Connect(layer, tfLiteNode, delegateData); |
Sadik Armagan | 62483be | 2020-10-23 17:14:43 +0100 | [diff] [blame] | 144 | } |
| 145 | |
| 146 | } // namespace armnnDelegate |