#include <stdexcept>
#include "internal/Padding.h"
-#include "internal/kernels/cpufallback/CPUConvolutionLayer.h"
+#include "internal/kernels/cpufallback/ConvolutionLayer.h"
#include "internal/kernels/cpufallback/AvgPoolLayer.h"
#include "logging.h"
auto ker_alloc = tensors->at(::internal::tflite::operand::Index{param.ker_index});
auto bias_alloc = tensors->at(::internal::tflite::operand::Index{param.bias_index});
- std::unique_ptr<::internal::kernels::cpu::CPUConvolutionLayer> fn{
- new ::internal::kernels::cpu::CPUConvolutionLayer};
+ std::unique_ptr<::internal::kernels::cpu::ConvolutionLayer> fn{
+ new ::internal::kernels::cpu::ConvolutionLayer};
fn->configure(ifm_alloc->buffer(), param.ifm_shape, ker_alloc->buffer(), param.ker_shape,
bias_alloc->buffer(), param.bias_shape, param.padding.left, param.padding.right,
-#include "CPUConvolutionLayer.h"
+#include "ConvolutionLayer.h"
#include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h"
#include "internal/kernels/cpufallback/OperationUtils.h"
im2colGuard.reset(im2colData); \
}
-bool CPUConvolutionLayer::convFloat32()
+bool ConvolutionLayer::convFloat32()
{
ANDROID_NN_CONV_PARAMETERS(float)
return true;
}
-bool CPUConvolutionLayer::convQuant8()
+bool ConvolutionLayer::convQuant8()
{
/*
ANDROID_NN_CONV_PARAMETERS(uint8_t)
return true;
}
-void CPUConvolutionLayer::configure(
+void ConvolutionLayer::configure(
uint8_t *inputData, const internal::tflite::operand::Shape inputShape, uint8_t *kernelData,
const internal::tflite::operand::Shape kernelShape, uint8_t *biasData,
const internal::tflite::operand::Shape biasShape, const uint32_t paddingLeft,
_outputShape = convertShape(outputShape);
}
-void CPUConvolutionLayer::run()
+void ConvolutionLayer::run()
{
convFloat32();
/*
-#ifndef __INTERNAL_KERNELS_CPU_CPUCONVOLUTIONLAYER_H__
-#define __INTERNAL_KERNELS_CPU_CPUCONVOLUTIONLAYER_H__
+#ifndef __INTERNAL_KERNELS_CPU_CONVOLUTIONLAYER_H__
+#define __INTERNAL_KERNELS_CPU_CONVOLUTIONLAYER_H__
#include <NeuralNetworks.h>
namespace cpu
{
-class CPUConvolutionLayer : public ::arm_compute::IFunction
+class ConvolutionLayer : public ::arm_compute::IFunction
{
public:
- CPUConvolutionLayer() {}
+ ConvolutionLayer() {}
public:
bool convFloat32();
} // namespace kernels
} // namespace internal
-#endif // __INTERNAL_KERNELS_CPU_CPUCONVOLUTIONLAYER_H__
+#endif // __INTERNAL_KERNELS_CPU_CONVOLUTIONLAYER_H__