remove files

test_gemm.cpp

-/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#include <iostream>
-#include <cstdlib>
-#include <ctime>
-#include "../test_helper.h"
-#include "common/log.h"
-#include "memory/t_malloc.h"
-#include "operators/math/gemm.h"
-
-#define a(i, j) a[(i)*lda + (j)]
-#define b(i, j) b[(i)*ldb + (j)]
-#define c(i, j) c[(i)*ldc + (j)]
-#define c1(i, j) c1[(i)*ldc + (j)]
-
-
-void print_matirx(int m, int n, int ldc, float *c) {
-    for (int i = 0; i < m; ++i) {
-        std::cout << c(i, 0);
-        for (int j = 1; j < n; ++j) {
-            std::cout << " | " << c(i, j);
-        }
-        std::cout << std::endl;
-    }
-    std::cout << std::endl;
-}
-
-int do_sgemm(int m, int n, int k, bool relu, int t1, int t2, int pr) {
-  int lda = k;
-  int ldb = n;
-  int ldc = n;
-
-  float *a = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * m * k));
-  float *b = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * k * n));
-  float *c = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * m * n));
-  float *c1 = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * m * n));
-  float* scale = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * m));
-  float* bias = static_cast<float *>(paddle_mobile::memory::Alloc(sizeof(float) * m));
-  
-  srand(unsigned(time(0)));
-  for (int i = 0; i < m * k; ++i) {
-    a[i] = t1 + rand() % t2; 
-  }
-  for (int i = 0; i < k * n; ++i) {
-    b[i] = t1 + rand() % t2; 
-  }
-  for (int i = 0; i < m; ++i) {
-    scale[i] = t1 + rand() % t2; 
-  }
-  for (int i = 0; i < m; ++i) {
-    bias[i] = t1 + rand() % t2; 
-  }
-  
-  for (int i = 0; i < m; ++i) {
-    for (int j = 0; j < n; ++j) {
-      float r = 0;
-      for (int p = 0; p < k; p++) {
-        r += a(i, p) * b(p, j);
-      }
-      r *= scale[i];
-      r += bias[i];
-      if (relu && (r < 0)) {
-        r = 0;
-      }
-      c1(i, j) = r;
-    }
-  }
-  
-  paddle_mobile::operators::math::SgemmWithBn(m, n, k, 0.9, a, lda,
-                 b, ldb, 0.3, c, ldc, relu, scale, bias);
-  int eq = 0;
-  int neq = 0;
-  for (int i = 0; i < m * n; ++i) {
-    if (static_cast<int>(c[i]) == static_cast<int>(c1[i])) {
-        ++eq;
-    } else {
-        ++neq;
-    }
-  }
-  
-  if (pr > 0) {
-    std::cout << "A:" << std::endl;
-    print_matirx(m, k, lda, a);
-    
-    std::cout << "B:" << std::endl;
-    print_matirx(k, n, ldb, b);
-    
-    std::cout << "C:" << std::endl;
-    print_matirx(m, n, ldc, c);
-
-    std::cout << "C1:" << std::endl;
-    print_matirx(m, n, ldc, c1);
-  }
-    
-  std::cout << "mnk=" << m << " " << n << " " << k << 
-    " relu=" << relu <<
-    "   eq=" << eq << " neq=" << neq << std::endl;
-
-  paddle_mobile::memory::Free(a);
-  paddle_mobile::memory::Free(b);
-  paddle_mobile::memory::Free(c);
-  paddle_mobile::memory::Free(c1);
-  paddle_mobile::memory::Free(scale);
-  paddle_mobile::memory::Free(bias);
-        
-  return 0;
-}
-
-int main() {
-    
-  do_sgemm(9, 9, 9, true, 10, 10, 10);
-  do_sgemm(10, 6, 12, false, 10, 10, 0);
-  do_sgemm(512, 256, 384, false, 10, 10, 0);
-  do_sgemm(1366, 768, 256, false, 10, 10, 0);
-  do_sgemm(1255, 755, 333, false, 10, 10, 0);
-  do_sgemm(555, 777, 999, false, 10, 10, 0);
-  
-  do_sgemm(10, 6, 12, true, -4, 10, 0);
-  do_sgemm(512, 256, 384, true, -4, 10, 0);
-  do_sgemm(1366, 768, 256, true, -4, 10, 0);
-  do_sgemm(1255, 755, 333, true, -4, 10, 0);
-  do_sgemm(555, 777, 999, true, -4, 10, 0);
-  return 0;
-}