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	#ifndef BLAS_H
	#define BLAS_H
	#include "darknet.h"

	void flatten(float *x, int size, int layers, int batch, int forward);
	void pm(int M, int N, float *A);
	float *random_matrix(int rows, int cols);
	void time_random_matrix(int TA, int TB, int m, int k, int n);
	void reorg_cpu(float x, int w, int h, int c, int batch, int stride, int forward, float out);

	void test_blas();

	void inter_cpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void deinter_cpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void mult_add_into_cpu(int N, float X, float Y, float *Z);

	void const_cpu(int N, float ALPHA, float *X, int INCX);
	void constrain_gpu(int N, float ALPHA, float * X, int INCX);
	void pow_cpu(int N, float ALPHA, float X, int INCX, float Y, int INCY);
	void mul_cpu(int N, float X, int INCX, float Y, int INCY);

	int test_gpu_blas();
	void shortcut_cpu(int batch, int w1, int h1, int c1, float add, int w2, int h2, int c2, float s1, float s2, float out);

	void mean_cpu(float x, int batch, int filters, int spatial, float mean);
	void variance_cpu(float x, float mean, int batch, int filters, int spatial, float *variance);

	void scale_bias(float output, float scales, int batch, int n, int size);
	void backward_scale_cpu(float x_norm, float delta, int batch, int n, int size, float *scale_updates);
	void mean_delta_cpu(float delta, float variance, int batch, int filters, int spatial, float *mean_delta);
	void variance_delta_cpu(float x, float delta, float mean, float variance, int batch, int filters, int spatial, float *variance_delta);
	void normalize_delta_cpu(float x, float mean, float variance, float mean_delta, float variance_delta, int batch, int filters, int spatial, float delta);
	void l2normalize_cpu(float x, float dx, int batch, int filters, int spatial);

	void smooth_l1_cpu(int n, float pred, float truth, float delta, float error);
	void l2_cpu(int n, float pred, float truth, float delta, float error);
	void l1_cpu(int n, float pred, float truth, float delta, float error);
	void logistic_x_ent_cpu(int n, float pred, float truth, float delta, float error);
	void softmax_x_ent_cpu(int n, float pred, float truth, float delta, float error);
	void weighted_sum_cpu(float a, float b, float s, int num, float c);
	void weighted_delta_cpu(float a, float b, float s, float da, float db, float ds, int n, float *dc);

	void softmax(float input, int n, float temp, int stride, float output);
	void softmax_cpu(float input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float output);
	void upsample_cpu(float in, int w, int h, int c, int batch, int stride, int forward, float scale, float out);

	#ifdef GPU
	#include "cuda.h"
	#include "tree.h"

	void axpy_gpu(int N, float ALPHA, float * X, int INCX, float * Y, int INCY);
	void axpy_gpu_offset(int N, float ALPHA, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
	void copy_gpu(int N, float * X, int INCX, float * Y, int INCY);
	void copy_gpu_offset(int N, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
	void add_gpu(int N, float ALPHA, float * X, int INCX);
	void supp_gpu(int N, float ALPHA, float * X, int INCX);
	void mask_gpu(int N, float * X, float mask_num, float * mask, float val);
	void scale_mask_gpu(int N, float * X, float mask_num, float * mask, float scale);
	void const_gpu(int N, float ALPHA, float *X, int INCX);
	void pow_gpu(int N, float ALPHA, float X, int INCX, float Y, int INCY);
	void mul_gpu(int N, float X, int INCX, float Y, int INCY);

	void mean_gpu(float x, int batch, int filters, int spatial, float mean);
	void variance_gpu(float x, float mean, int batch, int filters, int spatial, float *variance);
	void normalize_gpu(float x, float mean, float *variance, int batch, int filters, int spatial);
	void l2normalize_gpu(float x, float dx, int batch, int filters, int spatial);

	void normalize_delta_gpu(float x, float mean, float variance, float mean_delta, float variance_delta, int batch, int filters, int spatial, float delta);

	void fast_mean_delta_gpu(float delta, float variance, int batch, int filters, int spatial, float *mean_delta);
	void fast_variance_delta_gpu(float x, float delta, float mean, float variance, int batch, int filters, int spatial, float *variance_delta);

	void fast_variance_gpu(float x, float mean, int batch, int filters, int spatial, float *variance);
	void fast_mean_gpu(float x, int batch, int filters, int spatial, float mean);
	void shortcut_gpu(int batch, int w1, int h1, int c1, float add, int w2, int h2, int c2, float s1, float s2, float out);
	void scale_bias_gpu(float output, float biases, int batch, int n, int size);
	void backward_scale_gpu(float x_norm, float delta, int batch, int n, int size, float *scale_updates);
	void scale_bias_gpu(float output, float biases, int batch, int n, int size);
	void add_bias_gpu(float output, float biases, int batch, int n, int size);
	void backward_bias_gpu(float bias_updates, float delta, int batch, int n, int size);

	void logistic_x_ent_gpu(int n, float pred, float truth, float delta, float error);
	void softmax_x_ent_gpu(int n, float pred, float truth, float delta, float error);
	void smooth_l1_gpu(int n, float pred, float truth, float delta, float error);
	void l2_gpu(int n, float pred, float truth, float delta, float error);
	void l1_gpu(int n, float pred, float truth, float delta, float error);
	void wgan_gpu(int n, float pred, float truth, float delta, float error);
	void weighted_delta_gpu(float a, float b, float s, float da, float db, float ds, int num, float *dc);
	void weighted_sum_gpu(float a, float b, float s, int num, float c);
	void mult_add_into_gpu(int num, float a, float b, float *c);
	void inter_gpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void deinter_gpu(int NX, float X, int NY, float Y, int B, float *OUT);

	void reorg_gpu(float x, int w, int h, int c, int batch, int stride, int forward, float out);

	void softmax_gpu(float input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float output);
	void adam_update_gpu(float w, float d, float m, float v, float B1, float B2, float eps, float decay, float rate, int n, int batch, int t);
	void adam_gpu(int n, float x, float m, float *v, float B1, float B2, float rate, float eps, int t);

	void flatten_gpu(float x, int spatial, int layers, int batch, int forward, float out);
	void softmax_tree(float input, int spatial, int batch, int stride, float temp, float output, tree hier);
	void upsample_gpu(float in, int w, int h, int c, int batch, int stride, int forward, float scale, float out);

	#endif
	#endif

	#ifndef BLAS_H
	#define BLAS_H
	#include "darknet.h"

	void flatten(float *x, int size, int layers, int batch, int forward);
	void pm(int M, int N, float *A);
	float *random_matrix(int rows, int cols);
	void time_random_matrix(int TA, int TB, int m, int k, int n);
	void reorg_cpu(float x, int w, int h, int c, int batch, int stride, int forward, float out);

	void test_blas();

	void inter_cpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void deinter_cpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void mult_add_into_cpu(int N, float X, float Y, float *Z);

	void const_cpu(int N, float ALPHA, float *X, int INCX);
	void constrain_gpu(int N, float ALPHA, float * X, int INCX);
	void pow_cpu(int N, float ALPHA, float X, int INCX, float Y, int INCY);
	void mul_cpu(int N, float X, int INCX, float Y, int INCY);

	int test_gpu_blas();
	void shortcut_cpu(int batch, int w1, int h1, int c1, float add, int w2, int h2, int c2, float s1, float s2, float out);

	void mean_cpu(float x, int batch, int filters, int spatial, float mean);
	void variance_cpu(float x, float mean, int batch, int filters, int spatial, float *variance);

	void scale_bias(float output, float scales, int batch, int n, int size);
	void backward_scale_cpu(float x_norm, float delta, int batch, int n, int size, float *scale_updates);
	void mean_delta_cpu(float delta, float variance, int batch, int filters, int spatial, float *mean_delta);
	void variance_delta_cpu(float x, float delta, float mean, float variance, int batch, int filters, int spatial, float *variance_delta);
	void normalize_delta_cpu(float x, float mean, float variance, float mean_delta, float variance_delta, int batch, int filters, int spatial, float delta);
	void l2normalize_cpu(float x, float dx, int batch, int filters, int spatial);

	void smooth_l1_cpu(int n, float pred, float truth, float delta, float error);
	void l2_cpu(int n, float pred, float truth, float delta, float error);
	void l1_cpu(int n, float pred, float truth, float delta, float error);
	void logistic_x_ent_cpu(int n, float pred, float truth, float delta, float error);
	void softmax_x_ent_cpu(int n, float pred, float truth, float delta, float error);
	void weighted_sum_cpu(float a, float b, float s, int num, float c);
	void weighted_delta_cpu(float a, float b, float s, float da, float db, float ds, int n, float *dc);

	void softmax(float input, int n, float temp, int stride, float output);
	void softmax_cpu(float input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float output);
	void upsample_cpu(float in, int w, int h, int c, int batch, int stride, int forward, float scale, float out);

	#ifdef GPU
	#include "cuda.h"
	#include "tree.h"

	void axpy_gpu(int N, float ALPHA, float * X, int INCX, float * Y, int INCY);
	void axpy_gpu_offset(int N, float ALPHA, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
	void copy_gpu(int N, float * X, int INCX, float * Y, int INCY);
	void copy_gpu_offset(int N, float * X, int OFFX, int INCX, float * Y, int OFFY, int INCY);
	void add_gpu(int N, float ALPHA, float * X, int INCX);
	void supp_gpu(int N, float ALPHA, float * X, int INCX);
	void mask_gpu(int N, float * X, float mask_num, float * mask, float val);
	void scale_mask_gpu(int N, float * X, float mask_num, float * mask, float scale);
	void const_gpu(int N, float ALPHA, float *X, int INCX);
	void pow_gpu(int N, float ALPHA, float X, int INCX, float Y, int INCY);
	void mul_gpu(int N, float X, int INCX, float Y, int INCY);

	void mean_gpu(float x, int batch, int filters, int spatial, float mean);
	void variance_gpu(float x, float mean, int batch, int filters, int spatial, float *variance);
	void normalize_gpu(float x, float mean, float *variance, int batch, int filters, int spatial);
	void l2normalize_gpu(float x, float dx, int batch, int filters, int spatial);

	void normalize_delta_gpu(float x, float mean, float variance, float mean_delta, float variance_delta, int batch, int filters, int spatial, float delta);

	void fast_mean_delta_gpu(float delta, float variance, int batch, int filters, int spatial, float *mean_delta);
	void fast_variance_delta_gpu(float x, float delta, float mean, float variance, int batch, int filters, int spatial, float *variance_delta);

	void fast_variance_gpu(float x, float mean, int batch, int filters, int spatial, float *variance);
	void fast_mean_gpu(float x, int batch, int filters, int spatial, float mean);
	void shortcut_gpu(int batch, int w1, int h1, int c1, float add, int w2, int h2, int c2, float s1, float s2, float out);
	void scale_bias_gpu(float output, float biases, int batch, int n, int size);
	void backward_scale_gpu(float x_norm, float delta, int batch, int n, int size, float *scale_updates);
	void scale_bias_gpu(float output, float biases, int batch, int n, int size);
	void add_bias_gpu(float output, float biases, int batch, int n, int size);
	void backward_bias_gpu(float bias_updates, float delta, int batch, int n, int size);

	void logistic_x_ent_gpu(int n, float pred, float truth, float delta, float error);
	void softmax_x_ent_gpu(int n, float pred, float truth, float delta, float error);
	void smooth_l1_gpu(int n, float pred, float truth, float delta, float error);
	void l2_gpu(int n, float pred, float truth, float delta, float error);
	void l1_gpu(int n, float pred, float truth, float delta, float error);
	void wgan_gpu(int n, float pred, float truth, float delta, float error);
	void weighted_delta_gpu(float a, float b, float s, float da, float db, float ds, int num, float *dc);
	void weighted_sum_gpu(float a, float b, float s, int num, float c);
	void mult_add_into_gpu(int num, float a, float b, float *c);
	void inter_gpu(int NX, float X, int NY, float Y, int B, float *OUT);
	void deinter_gpu(int NX, float X, int NY, float Y, int B, float *OUT);

	void reorg_gpu(float x, int w, int h, int c, int batch, int stride, int forward, float out);

	void softmax_gpu(float input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float output);
	void adam_update_gpu(float w, float d, float m, float v, float B1, float B2, float eps, float decay, float rate, int n, int batch, int t);
	void adam_gpu(int n, float x, float m, float *v, float B1, float B2, float rate, float eps, int t);

	void flatten_gpu(float x, int spatial, int layers, int batch, int forward, float out);
	void softmax_tree(float input, int spatial, int batch, int stride, float temp, float output, tree hier);
	void upsample_gpu(float in, int w, int h, int c, int batch, int stride, int forward, float scale, float out);

	#endif
	#endif