107             Shape inputShape = context->getInputShape(kInputTensor);  in initialize()
108             Shape filterShape = context->getInputShape(kFilterTensor);  in initialize()
178 bool needim2colData(const Shape& filterShape, int32_t stride_width, int32_t stride_height,  in needim2colData()
194 bool convNhwc(const float* inputData, const Shape& inputShape, const float* filterData,  in convNhwc()
195               const Shape& filterShape, const float* biasData, const Shape& biasShape,  in convNhwc()
199               float* outputData, const Shape& outputShape) {  in convNhwc()
223 bool convNhwc(const uint8_t* inputData, const Shape& inputShape, const uint8_t* filterData,  in convNhwc()
224               const Shape& filterShape, const int32_t* biasData, const Shape& biasShape,  in convNhwc()
228               uint8_t* outputData, const Shape& outputShape) {  in convNhwc()
277 bool convNhwc(const int8_t* inputData, Shape inputShape, const int8_t* filterData,  in convNhwc()
278               Shape filterShape, const int32_t* biasData, const Shape& biasShape,  in convNhwc()
282               int8_t* outputData, Shape outputShape) {  in convNhwc()
306 bool convNhwc(const _Float16* inputData, const Shape& inputShape, const _Float16* filterData,  in convNhwc()
307               const Shape& filterShape, const _Float16* biasData, const Shape& biasShape,  in convNhwc()
311               _Float16* outputData, const Shape& outputShape) {  in convNhwc()
333 bool conv(const T_Input* inputData, const Shape& inputShape, const T_Filter* filterData,  in conv()
334           const Shape& filterShape, const T_Bias* biasData, const Shape& biasShape,  in conv()
338           const Shape& outputShape) {  in conv()
352 bool convQuant8PerChannelNhwc(const uint8_t* inputData, const Shape& inputShape,  in convQuant8PerChannelNhwc()
353                               const int8_t* filterData, const Shape& filterShape,  in convQuant8PerChannelNhwc()
355                               const Shape& biasShape, int32_t paddingLeft, int32_t paddingRight,  in convQuant8PerChannelNhwc()
359                               const Shape& outputShape) {  in convQuant8PerChannelNhwc()
381         Shape filterChannelShape = filterShape;  in convQuant8PerChannelNhwc()
383         Shape biasChannelShape = biasShape;  in convQuant8PerChannelNhwc()
445 bool convQuant8PerChannelNhwc(const int8_t* inputData, const Shape& inputShape,  in convQuant8PerChannelNhwc()
446                               const int8_t* filterData, const Shape& filterShape,  in convQuant8PerChannelNhwc()
448                               const Shape& biasShape, int32_t paddingLeft, int32_t paddingRight,  in convQuant8PerChannelNhwc()
452                               const Shape& outputShape) {  in convQuant8PerChannelNhwc()
474         Shape filterChannelShape = filterShape;  in convQuant8PerChannelNhwc()
476         Shape biasChannelShape = biasShape;  in convQuant8PerChannelNhwc()
509 bool convQuant8PerChannel(const T* inputData, const Shape& inputShape, const int8_t* filterData,  in convQuant8PerChannel()
510                           const Shape& filterShape, const float* filterScales,  in convQuant8PerChannel()
511                           const int32_t* biasData, const Shape& biasShape, int32_t paddingLeft,  in convQuant8PerChannel()
515                           T* outputData, const Shape& outputShape) {  in convQuant8PerChannel()
637     Shape input = context->getInputShape(kInputTensor);  in prepare()
638     Shape filter = context->getInputShape(kFilterTensor);  in prepare()
639     Shape bias = context->getInputShape(kBiasTensor);  in prepare()
689     Shape output = context->getOutputShape(kOutputTensor);  in prepare()