mirror of https://github.com/pjreddie/darknet.git
90 lines
5.2 KiB
C
90 lines
5.2 KiB
C
#ifndef BLAS_H
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#define BLAS_H
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#include "darknet.h"
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void flatten(float *x, int size, int layers, int batch, int forward);
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void pm(int M, int N, float *A);
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float *random_matrix(int rows, int cols);
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void time_random_matrix(int TA, int TB, int m, int k, int n);
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void reorg_cpu(float *x, int w, int h, int c, int batch, int stride, int forward, float *out);
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void test_blas();
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void const_cpu(int N, float ALPHA, float *X, int INCX);
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void constrain_ongpu(int N, float ALPHA, float * X, int INCX);
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void pow_cpu(int N, float ALPHA, float *X, int INCX, float *Y, int INCY);
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void mul_cpu(int N, float *X, int INCX, float *Y, int INCY);
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void fill_cpu(int N, float ALPHA, float * X, int INCX);
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float dot_cpu(int N, float *X, int INCX, float *Y, int INCY);
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int test_gpu_blas();
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void shortcut_cpu(int batch, int w1, int h1, int c1, float *add, int w2, int h2, int c2, float *out);
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void mean_cpu(float *x, int batch, int filters, int spatial, float *mean);
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void variance_cpu(float *x, float *mean, int batch, int filters, int spatial, float *variance);
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void scale_bias(float *output, float *scales, int batch, int n, int size);
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void backward_scale_cpu(float *x_norm, float *delta, int batch, int n, int size, float *scale_updates);
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void mean_delta_cpu(float *delta, float *variance, int batch, int filters, int spatial, float *mean_delta);
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void variance_delta_cpu(float *x, float *delta, float *mean, float *variance, int batch, int filters, int spatial, float *variance_delta);
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void normalize_delta_cpu(float *x, float *mean, float *variance, float *mean_delta, float *variance_delta, int batch, int filters, int spatial, float *delta);
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void smooth_l1_cpu(int n, float *pred, float *truth, float *delta, float *error);
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void l2_cpu(int n, float *pred, float *truth, float *delta, float *error);
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void l1_cpu(int n, float *pred, float *truth, float *delta, float *error);
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void weighted_sum_cpu(float *a, float *b, float *s, int num, float *c);
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void softmax(float *input, int n, float temp, int stride, float *output);
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void softmax_cpu(float *input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float *output);
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#ifdef GPU
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#include "cuda.h"
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#include "tree.h"
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void axpy_ongpu(int N, float ALPHA, float * X, int INCX, float * Y, int INCY);
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void axpy_ongpu_offset(int N, float ALPHA, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
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void copy_ongpu(int N, float * X, int INCX, float * Y, int INCY);
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void copy_ongpu_offset(int N, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
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void add_ongpu(int N, float ALPHA, float * X, int INCX);
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void supp_ongpu(int N, float ALPHA, float * X, int INCX);
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void mask_ongpu(int N, float * X, float mask_num, float * mask);
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void const_ongpu(int N, float ALPHA, float *X, int INCX);
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void pow_ongpu(int N, float ALPHA, float *X, int INCX, float *Y, int INCY);
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void mul_ongpu(int N, float *X, int INCX, float *Y, int INCY);
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void mean_gpu(float *x, int batch, int filters, int spatial, float *mean);
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void variance_gpu(float *x, float *mean, int batch, int filters, int spatial, float *variance);
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void normalize_gpu(float *x, float *mean, float *variance, int batch, int filters, int spatial);
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void normalize_delta_gpu(float *x, float *mean, float *variance, float *mean_delta, float *variance_delta, int batch, int filters, int spatial, float *delta);
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void fast_mean_delta_gpu(float *delta, float *variance, int batch, int filters, int spatial, float *mean_delta);
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void fast_variance_delta_gpu(float *x, float *delta, float *mean, float *variance, int batch, int filters, int spatial, float *variance_delta);
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void fast_variance_gpu(float *x, float *mean, int batch, int filters, int spatial, float *variance);
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void fast_mean_gpu(float *x, int batch, int filters, int spatial, float *mean);
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void shortcut_gpu(int batch, int w1, int h1, int c1, float *add, int w2, int h2, int c2, float *out);
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void scale_bias_gpu(float *output, float *biases, int batch, int n, int size);
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void backward_scale_gpu(float *x_norm, float *delta, int batch, int n, int size, float *scale_updates);
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void scale_bias_gpu(float *output, float *biases, int batch, int n, int size);
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void add_bias_gpu(float *output, float *biases, int batch, int n, int size);
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void backward_bias_gpu(float *bias_updates, float *delta, int batch, int n, int size);
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void smooth_l1_gpu(int n, float *pred, float *truth, float *delta, float *error);
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void l2_gpu(int n, float *pred, float *truth, float *delta, float *error);
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void l1_gpu(int n, float *pred, float *truth, float *delta, float *error);
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void weighted_delta_gpu(float *a, float *b, float *s, float *da, float *db, float *ds, int num, float *dc);
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void weighted_sum_gpu(float *a, float *b, float *s, int num, float *c);
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void mult_add_into_gpu(int num, float *a, float *b, float *c);
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void reorg_ongpu(float *x, int w, int h, int c, int batch, int stride, int forward, float *out);
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void softmax_gpu(float *input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float *output);
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void adam_gpu(int n, float *x, float *m, float *v, float B1, float B2, float rate, float eps, int t);
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void flatten_ongpu(float *x, int spatial, int layers, int batch, int forward, float *out);
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void softmax_tree(float *input, int spatial, int batch, int stride, float temp, float *output, tree hier);
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#endif
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#endif
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