xavier
808a84131c
The new test works both with TensorRT and cuDNN. Preprocessing and Postprocessing are missing. Add ClippedReLU (for ReLU6), groups for Conv2d, additional bias for convolution. Other minors: -move the timer in the detector to measure all the processing time for a given frame (both centernet and yolo); -add int8 flag. Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com> Davide Sapienza <sapienza.dav@gmail.com>
62 lines
3.8 KiB
C
62 lines
3.8 KiB
C
#ifndef KERNELS_H
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#define KERNELS_H
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#include "utils.h"
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void activationELUForward(dnnType* srcData, dnnType* dstData, int size, cudaStream_t stream = cudaStream_t(0));
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void activationLEAKYForward(dnnType* srcData, dnnType* dstData, int size, cudaStream_t stream = cudaStream_t(0));
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void activationReLUCeilingForward(dnnType* srcData, dnnType* dstData, int size, const float ceiling, cudaStream_t stream= cudaStream_t(0));
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void activationLOGISTICForward(dnnType* srcData, dnnType* dstData, int size, cudaStream_t stream = cudaStream_t(0));
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void activationSIGMOIDForward(dnnType* srcData, dnnType* dstData, int size, cudaStream_t stream = cudaStream_t(0));
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void fill(dnnType* data, int size, dnnType val, cudaStream_t stream = cudaStream_t(0));
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void resizeForward( dnnType* srcData, dnnType* dstData, int n, int i_c, int i_h, int i_w,
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int o_c, int o_h, int o_w, cudaStream_t stream = cudaStream_t(0));
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void reorgForward( dnnType* srcData, dnnType* dstData,
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int n, int c, int h, int w, int stride, cudaStream_t stream = cudaStream_t(0));
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void softmaxForward(float *input, int n, int batch, int batch_offset,
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int groups, int group_offset, int stride, float temp, float *output, cudaStream_t stream = cudaStream_t(0));
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void shortcutForward(dnnType* srcData, dnnType* dstData, int n1, int c1, int h1, int w1, int s1,
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int n2, int c2, int h2, int w2, int s2,
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cudaStream_t stream = cudaStream_t(0));
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void upsampleForward(dnnType* srcData, dnnType* dstData,
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int n, int c, int h, int w, int s, int forward, float scale,
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cudaStream_t stream = cudaStream_t(0));
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void float2half(float* srcData, __half* dstData, int size, const cudaStream_t stream = cudaStream_t(0));
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// void modulated_deformable_im2col_cuda(cudaStream_t stream,
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// const float *data_im, const float *data_offset, const float *data_mask,
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// const int batch_size, const int channels, const int height_im, const int width_im,
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// const int height_col, const int width_col, const int kernel_h, const int kenerl_w,
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// const int pad_h, const int pad_w, const int stride_h, const int stride_w,
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// const int dilation_h, const int dilation_w,
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// const int deformable_group, float *data_col);
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void modulated_deformable_im2col_cuda(cudaStream_t stream,
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const float *data_im, const float *data_offset, const float *data_mask,
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const int batch_size, const int channels, const int height_im, const int width_im,
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const int height_col, const int width_col,
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const int deformable_group, float *data_col);
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void dcn_v2_cuda_forward(cublasStatus_t stat, cublasHandle_t handle,
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float *input, float *weight,
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float *bias, float *ones,
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float *offset, float *mask,
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float *output, float *columns,
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int kernel_h, int kernel_w,
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const int stride_h, const int stride_w,
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const int pad_h, const int pad_w,
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const int dilation_h, const int dilation_w,
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const int deformable_group,
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const int in_n, const int in_c, const int in_h, const int in_w,
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const int out_n, const int out_c, const int out_h, const int out_w,
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const int dst_dim, cudaStream_t stream = cudaStream_t(0));
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#endif //KERNELS_H
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