115     int32_t paddingLeft = param.paddingLeft;                                    \
116     [[maybe_unused]] int32_t paddingRight = param.paddingRight;                 \
117     int32_t paddingTop = param.paddingTop;                                      \
118     [[maybe_unused]] int32_t paddingBottom = param.paddingBottom;               \
119     int32_t strideWidth = param.strideWidth, strideHeight = param.strideHeight; \
120     int32_t activation = param.activation;
124                        const TransposeConv2dParam& param, float* outputData,  in transposeConvNhwc()  argument
181                        const TransposeConv2dParam& param, T* outputData, const Shape& outputShape) {  in transposeConvNhwc()  argument
276                        const TransposeConv2dParam& param, _Float16* outputData,  in transposeConvNhwc()  argument
289                       biasData_float32.data(), biasShape, param, outputData_float32.data(),  in transposeConvNhwc()
299                    const TransposeConv2dParam& param, T_Input* outputData,  in transposeConv()  argument
301     InputWithLayout<T_Input> input(param.useNchw);  in transposeConv()
302     OutputWithLayout<T_Input> output(param.useNchw);  in transposeConv()
306                                    filterShape, biasData, biasShape, param, output.getNhwcBuffer(),  in transposeConv()
316                                        const Shape& biasShape, const TransposeConv2dParam& param,  in transposeConvQuant8PerChannelNhwc()  argument
419                                    const Shape& biasShape, const TransposeConv2dParam& param,  in transposeConvQuant8PerChannel()  argument
421     InputWithLayout<T> input(param.useNchw);  in transposeConvQuant8PerChannel()
422     OutputWithLayout<T> output(param.useNchw);  in transposeConvQuant8PerChannel()
427             biasData, biasShape, param, output.getNhwcBuffer(), output.getNhwcShape()));  in transposeConvQuant8PerChannel()
457     TransposeConv2dParam param;  in prepare()  local
458     NN_RET_CHECK(param.initialize(context));  in prepare()
461     uint32_t height = getSizeOfDimension(input, param.useNchw ? 2 : 1);  in prepare()
462     uint32_t width = getSizeOfDimension(input, param.useNchw ? 3 : 2);  in prepare()
463     uint32_t channels_in = getSizeOfDimension(input, param.useNchw ? 1 : 3);  in prepare()
477     uint32_t outWidth = computeOutSizeTransposeConv(width, filterWidth, param.strideWidth,  in prepare()
478                                                     param.paddingLeft, param.paddingRight);  in prepare()
479     uint32_t outHeight = computeOutSizeTransposeConv(height, filterHeight, param.strideHeight,  in prepare()
480                                                      param.paddingTop, param.paddingBottom);  in prepare()
486     if (param.useNchw) {  in prepare()
497     TransposeConv2dParam param;  in execute()  local
498     NN_RET_CHECK(param.initialize(context));  in execute()
506                                  context->getInputShape(kBiasTensor), param,  in execute()
515                                  context->getInputShape(kBiasTensor), param,  in execute()
530                         context->getInputShape(kBiasTensor), param,  in execute()
539                                      context->getInputShape(kBiasTensor), param,  in execute()
557                         context->getInputShape(kBiasTensor), param,  in execute()
567                                      context->getInputShape(kBiasTensor), param,  in execute()