107     tflite::PoolParams toTfliteParam(const Shape& output) const {  in toTfliteParam()
118         if (output.type == OperandType::TENSOR_QUANT8_ASYMM) {  in toTfliteParam()
121             CalculateActivationRangeUint8(activation, output, &output_activation_min,  in toTfliteParam()
125         } else if (output.type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED) {  in toTfliteParam()
128             CalculateActivationRangeInt8(activation, output, &output_activation_min,  in toTfliteParam()
260     OutputWithLayout<T> output(param.useNchw);  in averagePool()  local
262     NN_RET_CHECK(output.initialize(outputData, outputShape));  in averagePool()
264                                  output.getNhwcBuffer(), output.getNhwcShape()));  in averagePool()
265     NN_RET_CHECK(output.commit());  in averagePool()
273     OutputWithLayout<T> output(param.useNchw);  in l2Pool()  local
275     NN_RET_CHECK(output.initialize(outputData, outputShape));  in l2Pool()
277                             output.getNhwcBuffer(), output.getNhwcShape()));  in l2Pool()
278     NN_RET_CHECK(output.commit());  in l2Pool()
286     OutputWithLayout<T> output(param.useNchw);  in maxPool()  local
288     NN_RET_CHECK(output.initialize(outputData, outputShape));  in maxPool()
290                              output.getNhwcBuffer(), output.getNhwcShape()));  in maxPool()
291     NN_RET_CHECK(output.commit());  in maxPool()
318     Shape output = input;  in prepare()  local
320         output.dimensions = {batches, channels, outHeight, outWidth};  in prepare()
322         output.dimensions = {batches, outHeight, outWidth, channels};  in prepare()
324     return context->setOutputShape(kOutputTensor, output);  in prepare()