120     int32_t paddingLeft = param.paddingLeft, paddingRight = param.paddingRight; \
121     int32_t paddingTop = param.paddingTop, paddingBottom = param.paddingBottom; \
122     int32_t strideWidth = param.strideWidth, strideHeight = param.strideHeight; \
123     int32_t activation = param.activation;
127                        const TransposeConv2dParam& param, float* outputData,  in transposeConvNhwc()  argument
184                        const TransposeConv2dParam& param, T* outputData, const Shape& outputShape) {  in transposeConvNhwc()  argument
279                        const TransposeConv2dParam& param, _Float16* outputData,  in transposeConvNhwc()  argument
292                       biasData_float32.data(), biasShape, param, outputData_float32.data(),  in transposeConvNhwc()
302                    const TransposeConv2dParam& param, T_Input* outputData,  in transposeConv()  argument
304     InputWithLayout<T_Input> input(param.useNchw);  in transposeConv()
305     OutputWithLayout<T_Input> output(param.useNchw);  in transposeConv()
309                                    filterShape, biasData, biasShape, param, output.getNhwcBuffer(),  in transposeConv()
319                                        const Shape& biasShape, const TransposeConv2dParam& param,  in transposeConvQuant8PerChannelNhwc()  argument
422                                    const Shape& biasShape, const TransposeConv2dParam& param,  in transposeConvQuant8PerChannel()  argument
424     InputWithLayout<T> input(param.useNchw);  in transposeConvQuant8PerChannel()
425     OutputWithLayout<T> output(param.useNchw);  in transposeConvQuant8PerChannel()
430             biasData, biasShape, param, output.getNhwcBuffer(), output.getNhwcShape()));  in transposeConvQuant8PerChannel()
504     TransposeConv2dParam param;  in prepare()  local
505     NN_RET_CHECK(param.initialize(context));  in prepare()
508     uint32_t height = getSizeOfDimension(input, param.useNchw ? 2 : 1);  in prepare()
509     uint32_t width = getSizeOfDimension(input, param.useNchw ? 3 : 2);  in prepare()
510     uint32_t channels_in = getSizeOfDimension(input, param.useNchw ? 1 : 3);  in prepare()
524     uint32_t outWidth = computeOutSizeTransposeConv(width, filterWidth, param.strideWidth,  in prepare()
525                                                     param.paddingLeft, param.paddingRight);  in prepare()
526     uint32_t outHeight = computeOutSizeTransposeConv(height, filterHeight, param.strideHeight,  in prepare()
527                                                      param.paddingTop, param.paddingBottom);  in prepare()
533     if (param.useNchw) {  in prepare()
544     TransposeConv2dParam param;  in execute()  local
545     NN_RET_CHECK(param.initialize(context));  in execute()
553                                  context->getInputShape(kBiasTensor), param,  in execute()
562                                  context->getInputShape(kBiasTensor), param,  in execute()
575                         context->getInputShape(kBiasTensor), param,  in execute()
584                                      context->getInputShape(kBiasTensor), param,  in execute()
600                         context->getInputShape(kBiasTensor), param,  in execute()
610                                      context->getInputShape(kBiasTensor), param,  in execute()