94             Shape inputShape = context->getInputShape(kInputTensor);  in initialize()  local
96             int32_t input_width = getSizeOfDimension(inputShape, useNchw ? 3 : 2);  in initialize()
97             int32_t input_height = getSizeOfDimension(inputShape, useNchw ? 2 : 1);  in initialize()
120     uint32_t height       = getSizeOfDimension(inputShape, 1);                  \
121     uint32_t width        = getSizeOfDimension(inputShape, 2);                  \
126     uint32_t inDepth      = getSizeOfDimension(inputShape, 3);                  \
164 bool convNhwc(const float* inputData, const Shape& inputShape, const float* filterData,  in convNhwc()  argument
180     tflite::optimized_ops::Conv(inputData, convertShapeToDims(inputShape), filterData,  in convNhwc()
189 bool convNhwc(const uint8_t* inputData, const Shape& inputShape, const uint8_t* filterData,  in convNhwc()  argument
199     int32_t inputOffset = -inputShape.offset;  in convNhwc()
209     NN_RET_CHECK(GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape, outputShape,  in convNhwc()
227             inputData, convertShapeToDims(inputShape), inputOffset, filterData,  in convNhwc()
236 bool convNhwc(const _Float16* inputData, const Shape& inputShape, const _Float16* filterData,  in convNhwc()  argument
244     std::vector<float> inputData_float32(getNumberOfElements(inputShape));  in convNhwc()
253     convNhwc(inputData_float32.data(), inputShape, filterData_float32.data(), filterShape,  in convNhwc()
263 bool conv(const T_Input* inputData, const Shape& inputShape, const T_Filter* filterData,  in conv()  argument
271     NN_RET_CHECK(input.initialize(inputData, inputShape));  in conv()
282 bool convQuant8PerChannelNhwc(const uint8_t* inputData, const Shape& inputShape,  in convQuant8PerChannelNhwc()  argument
292     uint32_t numBatches = getSizeOfDimension(inputShape, 0);  in convQuant8PerChannelNhwc()
293     uint32_t inputHeight = getSizeOfDimension(inputShape, 1);  in convQuant8PerChannelNhwc()
294     uint32_t inputWidth = getSizeOfDimension(inputShape, 2);  in convQuant8PerChannelNhwc()
295     uint32_t inputDepth = getSizeOfDimension(inputShape, 3);  in convQuant8PerChannelNhwc()
303     int32_t inputOffset = -inputShape.offset;  in convQuant8PerChannelNhwc()
314         biasChannelShape.scale = filterScales[i] * inputShape.scale;  in convQuant8PerChannelNhwc()
316                 inputShape, filterChannelShape, biasChannelShape, outputShape, &realMultiplier[i]));  in convQuant8PerChannelNhwc()
375 bool convQuant8PerChannel(const uint8_t* inputData, const Shape& inputShape,  in convQuant8PerChannel()  argument
385     NN_RET_CHECK(input.initialize(inputData, inputShape));  in convQuant8PerChannel()