From: Salvatore Mesoraca <redacted>
Date: Tue, 27 Aug 2024 06:25:12 +0000 (+0200)
Subject: tests : fix memory leaks (#936)
X-Git-Tag: upstream/0.0.1642~439
X-Git-Url: https://git.djapps.eu/?a=commitdiff_plain;h=2438d62cb9290b5b5dc6228dec76fe81cf64238e;p=pkg%2Fggml%2Fsources%2Fggml

tests : fix memory leaks (#936)

It is annoying to run the tests using the sanitizers
because of all the uninteresting reports about the memory
leaked by the tests themselves.

Signed-off-by: Salvatore Mesoraca <redacted>
---

diff --git a/tests/test-conv-transpose-1d.cpp b/tests/test-conv-transpose-1d.cpp
index 83c60b42..c2e517dd 100644
--- a/tests/test-conv-transpose-1d.cpp
+++ b/tests/test-conv-transpose-1d.cpp
@@ -421,9 +421,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_0 = new float[ggml_nelements(conv1d_transpose_res_0)];
+    std::vector<float> conv1d_transpose_data_0(ggml_nelements(conv1d_transpose_res_0));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_0, conv1d_transpose_data_0, 0, ggml_nbytes(conv1d_transpose_res_0));
+    ggml_backend_tensor_get(conv1d_transpose_res_0, conv1d_transpose_data_0.data(), 0, ggml_nbytes(conv1d_transpose_res_0));
 
     const int n_conv_transpose_1d_test_0 = 4;
 
@@ -440,9 +440,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_1 = new float[ggml_nelements(conv1d_transpose_res_1)];
+    std::vector<float> conv1d_transpose_data_1(ggml_nelements(conv1d_transpose_res_1));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_1, conv1d_transpose_data_1, 0, ggml_nbytes(conv1d_transpose_res_1));
+    ggml_backend_tensor_get(conv1d_transpose_res_1, conv1d_transpose_data_1.data(), 0, ggml_nbytes(conv1d_transpose_res_1));
 
 
 
@@ -462,9 +462,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_2 = new float[ggml_nelements(conv1d_transpose_res_2)];
+    std::vector<float> conv1d_transpose_data_2(ggml_nelements(conv1d_transpose_res_2));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_2, conv1d_transpose_data_2, 0, ggml_nbytes(conv1d_transpose_res_2));
+    ggml_backend_tensor_get(conv1d_transpose_res_2, conv1d_transpose_data_2.data(), 0, ggml_nbytes(conv1d_transpose_res_2));
 
 
     const int n_conv_transpose_1d_test_2 = 10;
@@ -481,9 +481,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_3 = new float[ggml_nelements(conv1d_transpose_res_3)];
+    std::vector<float> conv1d_transpose_data_3(ggml_nelements(conv1d_transpose_res_3));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_3, conv1d_transpose_data_3, 0, ggml_nbytes(conv1d_transpose_res_3));
+    ggml_backend_tensor_get(conv1d_transpose_res_3, conv1d_transpose_data_3.data(), 0, ggml_nbytes(conv1d_transpose_res_3));
 
 
     const int n_conv_transpose_1d_test_3 = 14;
@@ -501,9 +501,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_4 = new float[ggml_nelements(conv1d_transpose_res_4)];
+    std::vector<float> conv1d_transpose_data_4(ggml_nelements(conv1d_transpose_res_4));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_4, conv1d_transpose_data_4, 0, ggml_nbytes(conv1d_transpose_res_4));
+    ggml_backend_tensor_get(conv1d_transpose_res_4, conv1d_transpose_data_4.data(), 0, ggml_nbytes(conv1d_transpose_res_4));
 
 
     const int n_conv_transpose_1d_test_4 = 12;
@@ -522,9 +522,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_5 = new float[ggml_nelements(conv1d_transpose_res_5)];
+    std::vector<float> conv1d_transpose_data_5(ggml_nelements(conv1d_transpose_res_5));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_5, conv1d_transpose_data_5, 0, ggml_nbytes(conv1d_transpose_res_5));
+    ggml_backend_tensor_get(conv1d_transpose_res_5, conv1d_transpose_data_5.data(), 0, ggml_nbytes(conv1d_transpose_res_5));
 
 
     const int n_conv_transpose_1d_test_5 = 18;
@@ -543,9 +543,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_6 = new float[ggml_nelements(conv1d_transpose_res_6)];
+    std::vector<float> conv1d_transpose_data_6(ggml_nelements(conv1d_transpose_res_6));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_6, conv1d_transpose_data_6, 0, ggml_nbytes(conv1d_transpose_res_6));
+    ggml_backend_tensor_get(conv1d_transpose_res_6, conv1d_transpose_data_6.data(), 0, ggml_nbytes(conv1d_transpose_res_6));
 
 
     const int n_conv_transpose_1d_test_6 = 24;
@@ -565,9 +565,9 @@ int main(void)
         }
     }
 
-    float* conv1d_transpose_data_7 = new float[ggml_nelements(conv1d_transpose_res_7)];
+    std::vector<float> conv1d_transpose_data_7(ggml_nelements(conv1d_transpose_res_7));
 
-    ggml_backend_tensor_get(conv1d_transpose_res_7, conv1d_transpose_data_7, 0, ggml_nbytes(conv1d_transpose_res_7));
+    ggml_backend_tensor_get(conv1d_transpose_res_7, conv1d_transpose_data_7.data(), 0, ggml_nbytes(conv1d_transpose_res_7));
 
 
     const int n_conv_transpose_1d_test_7 = 32*1584;
diff --git a/tests/test-conv1d.cpp b/tests/test-conv1d.cpp
index 53481470..d38d2993 100644
--- a/tests/test-conv1d.cpp
+++ b/tests/test-conv1d.cpp
@@ -40,17 +40,17 @@ void load_model(test_model & model, bool use_gpu = false) {
     int IL = 8, N = 1;
 
     // Initialize adata
-    float * adata = new float[K * IC * OC];
+    std::vector<float> adata(K * IC * OC);
     for (int i = 0; i < K * IC * OC; i++) {
         adata[i] = 4.5f;
     }
 
     // Convert adata to fp16 format
     std::vector<ggml_fp16_t> hadata(K * IC * OC);
-    ggml_fp32_to_fp16_row(adata, hadata.data(), K * IC * OC);
+    ggml_fp32_to_fp16_row(adata.data(), hadata.data(), K * IC * OC);
 
     // Initialize bdata
-    float * bdata =  new float[IL * IC * N];
+    std::vector<float> bdata(IL * IC * N);
     for (int i = 0; i < IL * IC * N; i++) {
         bdata[i] = 2.5f;
     }
@@ -129,9 +129,9 @@ void load_model(test_model & model, bool use_gpu = false) {
                 || ggml_backend_is_metal(model.backend)
 #endif
     ) {
-        memcpy(model.b->data, bdata, ggml_nbytes(model.b));
+        memcpy(model.b->data, bdata.data(), ggml_nbytes(model.b));
     } else {
-        ggml_backend_tensor_set(model.b, bdata, 0, ggml_nbytes(model.b));
+        ggml_backend_tensor_set(model.b, bdata.data(), 0, ggml_nbytes(model.b));
     }
 }
 
@@ -226,11 +226,11 @@ int main(void)
         }
     }
 
-    uint16_t* im2col_data = new uint16_t[ggml_nelements(im2col_res)];
-    float* conv2d_data = new float[ggml_nelements(conv1d_res)];
+    std::vector<uint16_t> im2col_data(ggml_nelements(im2col_res));
+    std::vector<float> conv2d_data(ggml_nelements(conv1d_res));
 
-    ggml_backend_tensor_get(im2col_res, im2col_data, 0, ggml_nbytes(im2col_res));
-    ggml_backend_tensor_get(conv1d_res, conv2d_data, 0, ggml_nbytes(conv1d_res));
+    ggml_backend_tensor_get(im2col_res, im2col_data.data(), 0, ggml_nbytes(im2col_res));
+    ggml_backend_tensor_get(conv1d_res, conv2d_data.data(), 0, ggml_nbytes(conv1d_res));
 
     const int n_conv1d_test = 80;
     const int n_im2col_test = 240;
diff --git a/tests/test-conv2d.cpp b/tests/test-conv2d.cpp
index 227f94c3..37942c50 100644
--- a/tests/test-conv2d.cpp
+++ b/tests/test-conv2d.cpp
@@ -40,17 +40,17 @@ void load_model(test_model & model, bool use_gpu = false) {
     int IW = 8, IH = 6, N = 1;
 
     // Initialize adata
-    float * adata = new float[KW * KH * IC * OC];
+    std::vector<float> adata(KW * KH * IC * OC);
     for (int i = 0; i < KW * KH * IC * OC; i++) {
         adata[i] = 2.5f;
     }
 
     // Convert adata to fp16 format
     std::vector<ggml_fp16_t> hadata(KW * KH * IC * OC);
-    ggml_fp32_to_fp16_row(adata, hadata.data(), KW * KH * IC * OC);
+    ggml_fp32_to_fp16_row(adata.data(), hadata.data(), KW * KH * IC * OC);
 
     // Initialize bdata
-    float * bdata =  new float[IW * IH * IC * N];
+    std::vector<float> bdata(IW * IH * IC * N);
     for (int i = 0; i < IW * IH * IC * N; i++) {
         bdata[i] = 1.5f;
     }
@@ -129,9 +129,9 @@ void load_model(test_model & model, bool use_gpu = false) {
                 || ggml_backend_is_metal(model.backend)
 #endif
     ) {
-        memcpy(model.b->data, bdata, ggml_nbytes(model.b));
+        memcpy(model.b->data, bdata.data(), ggml_nbytes(model.b));
     } else {
-        ggml_backend_tensor_set(model.b, bdata, 0, ggml_nbytes(model.b));
+        ggml_backend_tensor_set(model.b, bdata.data(), 0, ggml_nbytes(model.b));
     }
 }
 
@@ -229,11 +229,11 @@ int main(void)
         }
     }
 
-    uint16_t* im2col_data = new uint16_t[ggml_nelements(im2col_res)];
-    float* conv2d_data = new float[ggml_nelements(conv2d_res)];
+    std::vector<uint16_t> im2col_data(ggml_nelements(im2col_res));
+    std::vector<float> conv2d_data(ggml_nelements(conv2d_res));
 
-    ggml_backend_tensor_get(im2col_res, im2col_data, 0, ggml_nbytes(im2col_res));
-    ggml_backend_tensor_get(conv2d_res, conv2d_data, 0, ggml_nbytes(conv2d_res));
+    ggml_backend_tensor_get(im2col_res, im2col_data.data(), 0, ggml_nbytes(im2col_res));
+    ggml_backend_tensor_get(conv2d_res, conv2d_data.data(), 0, ggml_nbytes(conv2d_res));
 
     const int n_conv2d_test = 480;
     const int n_im2col_test = 4320;
diff --git a/tests/test-mul-mat.cpp b/tests/test-mul-mat.cpp
index cd218a2c..f91e172a 100644
--- a/tests/test-mul-mat.cpp
+++ b/tests/test-mul-mat.cpp
@@ -232,8 +232,8 @@ static void gemm_f16_out_f32(int m, int n, int k,
 void perform_gemm_test(float* a, float* b, float* expected, int M, int N, int K) {
     printf("\nPerforming gemm_f16_out_f32 test:\n");
 
-    float* gemm_out = new float[M * N];
-    gemm_f16_out_f32(M, N, K, a, b, gemm_out, 0, 1);
+    std::vector<float> gemm_out(M * N);
+    gemm_f16_out_f32(M, N, K, a, b, gemm_out.data(), 0, 1);
 
     for (int i = 0; i < M; i++) {
         for (int j = 0; j < N; j++) {
@@ -318,9 +318,9 @@ int main(void)
 
     struct ggml_tensor * result = compute(model, allocr);
 
-    float* out_data = new float[ggml_nelements(result)];
+    std::vector<float> out_data(ggml_nelements(result));
 
-    ggml_backend_tensor_get(result, out_data, 0, ggml_nbytes(result));
+    ggml_backend_tensor_get(result, out_data.data(), 0, ggml_nbytes(result));
 
     printf("\nPerforming ggml_mul_mat test:\n");