fix whitespace (abetlen#944)

Author: CRD716

Makefile

@@ -171,15 +171,15 @@ embedding: examples/embedding/embedding.cpp ggml.o llama.o common.o
 
 libllama.so: llama.o ggml.o
 	$(CXX) $(CXXFLAGS) -shared -fPIC -o libllama.so llama.o ggml.o $(LDFLAGS)
-  
+
 #
 # Tests
 #
 
 benchmark: ggml.o
-	$(CXX) $(CXXFLAGS) examples/benchmark/benchmark-q4_0-matmult.c ggml.o -o benchmark-q4_0-matmult $(LDFLAGS)	
+	$(CXX) $(CXXFLAGS) examples/benchmark/benchmark-q4_0-matmult.c ggml.o -o benchmark-q4_0-matmult $(LDFLAGS)
 	./benchmark-q4_0-matmult
-	
+
 .PHONY: tests
 tests:
 	bash ./tests/run-tests.sh

examples/benchmark/benchmark-q4_0-matmult.c

@@ -24,12 +24,12 @@
 
 float tensor_sum_elements(struct ggml_tensor * tensor) {
     float sum = 0;
-    if (tensor->type==6) { 
-        for (int j = 0; j < tensor->ne[1]; j++) { 
-            for (int k = 0; k < tensor->ne[0]; k++) { 
-                sum +=  ((float *) tensor->data)[j*tensor->ne[0]+k]; 
-            } 
-        } 
+    if (tensor->type==6) {
+        for (int j = 0; j < tensor->ne[1]; j++) {
+            for (int k = 0; k < tensor->ne[0]; k++) {
+                sum +=  ((float *) tensor->data)[j*tensor->ne[0]+k];
+            }
+        }
     }
     return sum;
 }
@@ -39,7 +39,7 @@ float tensor_sum_elements(struct ggml_tensor * tensor) {
     These are mapping to unknown
     GGML_TYPE_I8,
     GGML_TYPE_I16,
-    GGML_TYPE_I32,    
+    GGML_TYPE_I32,
     GGML_TYPE_COUNT,
 */
 
@@ -50,7 +50,7 @@ float tensor_sum_elements(struct ggml_tensor * tensor) {
         TENSOR->ne[0], TENSOR->ne[1], TENSOR->ne[2], TENSOR->nb[0], TENSOR->nb[1], TENSOR->nb[2]); \
     { float sum = tensor_sum_elements(TENSOR); printf("Sum of tensor %s is %6.2f\n",#TENSOR, sum); }
 
-struct benchmark_params_struct {    
+struct benchmark_params_struct {
     int32_t n_threads     = 1;
     int32_t n_iterations  = 10;
 };
@@ -67,7 +67,7 @@ void print_usage(int /*argc*/, char ** argv, struct benchmark_params_struct para
 
 int main(int argc, char ** argv)  {
 
-    
+
     struct benchmark_params_struct benchmark_params;
 
     bool invalid_param = false;
@@ -90,7 +90,7 @@ int main(int argc, char ** argv)  {
         }  else if (arg == "-h" || arg == "--help") {
             print_usage(argc, argv, benchmark_params);
             exit(0);
-        }     
+        }
         if (invalid_param) {
             fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
             print_usage(argc, argv, benchmark_params);
@@ -101,41 +101,41 @@ int main(int argc, char ** argv)  {
 
     // create the ggml context
     printf("Starting Test\n");
-    
 
-    
+
+
     struct ggml_context * ctx;
     //const int sizex = 4096;
     //const int sizey = 11008;
 
 #undef VERBOSE_DEBUGGING
 #ifndef VERBOSE_DEBUGGING
     const int sizey = 4096;
-    const int sizex = 11008;  
+    const int sizex = 11008;
     const int sizez = 128;
 #else
     /* Working - let's increase size */
     const int sizey = 1;
-    const int sizex = (8*32);  
+    const int sizex = (8*32);
     const int sizez = 1;
 
     /*const int sizey = 1;
-    const int sizex = 3*(8*32);  
+    const int sizex = 3*(8*32);
     const int sizez = 1;*/
 #endif
 
     //printf("Memsize required = %i\n", sizex*sizex);
-    ggml_type wtype = GGML_TYPE_F32;    
-    
+    ggml_type wtype = GGML_TYPE_F32;
+
     size_t ctx_size = 0;
     ctx_size += sizex*sizey*ggml_type_sizef(wtype);
     ctx_size += sizex*sizey*ggml_type_sizef(wtype);
     ctx_size += sizex*sizey*ggml_type_sizef(GGML_TYPE_F32);
     ctx_size += sizex*sizeof(float);
-    ctx_size += 1024*1024*100;    
-    
+    ctx_size += 1024*1024*100;
+
     printf("Allocating Memory of size %li byes, %li MB\n",ctx_size, (ctx_size/1024/1024));
-    
+
     struct ggml_init_params params = {
         /*.mem_size   =*/ ctx_size,
         /*.mem_buffer =*/ NULL,
@@ -147,88 +147,88 @@ int main(int argc, char ** argv)  {
         fprintf(stderr, "%s: ggml_init() failed\n", __func__);
         return false;
     }
-    
-    
+
+
     printf("Creating new tensors\n");
     // printf("Creating new tensor m1\n");
     struct ggml_tensor * m11 = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, sizex, sizey);
     ggml_set_f32(m11, 1.0f);
-    
+
     // printf("Creating new tensor m1\n");
     struct ggml_tensor * m12 = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, sizex, sizey);
     ggml_set_f32(m12, 1.5f);
-    
+
     // printf("Creating new tensor m2\n");
     struct ggml_tensor * m2 = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, sizex, sizez);
     ggml_set_f32(m2, 2.0f);
-    
+
     printf("\n------ Test 1 - Matrix Mult via F32 code ------------------------------------------------------------------------------\n");
     // printf("Creating new tensor m11xm2\n");
     struct ggml_tensor * m11xm2 = ggml_mul_mat(ctx, m11, m2);
-    
+
     // printf("Creating compute graph\n");
     struct ggml_cgraph gf = ggml_build_forward(m11xm2);
-    
+
     gf.n_threads=benchmark_params.n_threads;
-    printf("cgraph->n_threads=%i\n",gf.n_threads); 
-    
+    printf("cgraph->n_threads=%i\n",gf.n_threads);
+
     TENSOR_DUMP(m11);
     TENSOR_DUMP(m2);
-    
+
     ggml_graph_compute(ctx, &gf);
 
     TENSOR_DUMP(gf.nodes[0]);
-    
+
     printf("\n------ Test 2 - Matrix Mult via Q4_0 code ------------------------------------------------------------------------------\n");
-        
+
     int32_t nelements = sizex*sizey;
     int32_t ne[2] = { sizex, sizey };
-        
-    std::vector<int64_t> hist_cur(1 << 4, 0);    
+
+    std::vector<int64_t> hist_cur(1 << 4, 0);
 
     // Set up a the benchmark matrices
     // printf("Creating new tensor q11 & Running quantize\n");
     struct ggml_tensor * q11 = ggml_new_tensor_2d(ctx, GGML_TYPE_Q4_0, sizex, sizey);
     ggml_quantize_q4_0((const float *) m11->data, q11->data, nelements, ne[0], hist_cur.data());
-    
+
     // Set up a the compute graph
     // printf("Creating new tensor q31\n");
     struct ggml_tensor * q31 = ggml_mul_mat(ctx, q11, m2);
-        
+
     // printf("Creating compute graph\n");
     struct ggml_cgraph gf31 = ggml_build_forward(q31);
     gf31.n_threads=benchmark_params.n_threads;
-    
-    // Set up a second graph computation to make sure we override the CPU cache lines    
+
+    // Set up a second graph computation to make sure we override the CPU cache lines
     // printf("Creating new tensor q12 & Running quantize\n");
     struct ggml_tensor * q12 = ggml_new_tensor_2d(ctx, GGML_TYPE_Q4_0, sizex, sizey);
     ggml_quantize_q4_0((const float *) m12->data, q12->data, nelements, ne[0], hist_cur.data());
 
     // printf("Creating new tensor q32\n");
     struct ggml_tensor * q32 = ggml_mul_mat(ctx, q12, m2);
-        
+
     //printf("Creating compute graph\n");
     struct ggml_cgraph gf32 = ggml_build_forward(q32);
     gf32.n_threads=benchmark_params.n_threads;
-    printf("cgraph->n_threads=%i\n",gf31.n_threads); 
-    
+    printf("cgraph->n_threads=%i\n",gf31.n_threads);
+
     const int dimx = sizex;
     const int dimy = sizey;
     const int dimz = sizez;
     long long int flops_per_dot_product = dimy + dimy;
     long long int flops_per_matrix = flops_per_dot_product * dimx * dimz; ;
     printf("Matrix Multiplication of (%i,%i,%i) x (%i,%i,%i) - aboout %6.2f gFLOPS\n\n", sizex, sizey, 1, sizex, sizez, 1, 1.0f*flops_per_matrix / 1000 / 1000 / 1000);
-   
+
 
     // Let's use the F32 result from above as a reference for the q4_0 multiplication
     float sum_of_F32_reference = tensor_sum_elements(gf.nodes[0]);
-    
+
 
     printf("Iteration;NThreads; SizeX; SizeY; SizeZ; Required_FLOPS; Elapsed_u_Seconds; FLOPS_per_u_Second\n");
     printf("==============================================================================================\n");
-    
+
     for (int i=0;i<benchmark_params.n_iterations ;i++) {
-    
+
         long long int start = ggml_time_us();
         //printf("Running ggml_graph_compute\n");
         ggml_graph_compute(ctx, &gf31);
@@ -238,33 +238,33 @@ int main(int argc, char ** argv)  {
         float flops_per_usec = (1.0f*flops_per_matrix)/usec;
         printf("%9i;%8i;%6i;%6i;%6i;%15lli;%18lli;%19.2f\n",
             i,
-            gf31.n_threads, 
-            sizex, sizey, sizez, flops_per_matrix, 
+            gf31.n_threads,
+            sizex, sizey, sizez, flops_per_matrix,
             usec,flops_per_usec);
 
 #ifdef VERBOSE_DEBUGGING
         TENSOR_DUMP("res",gf31.nodes[0])
 #endif
 
-        // Check that the matrix multiplication result is in the right ballpark        
+        // Check that the matrix multiplication result is in the right ballpark
         // We cannot use the exact value from the F32 multiplication because the quantizuation will be slightly different
         float sum_of_Q4_result = tensor_sum_elements(gf31.nodes[0]);
         float delta = abs(sum_of_Q4_result - sum_of_F32_reference);
         float allowed_delta = (sum_of_F32_reference) / 1000 / 1000; //  Let's accept an epsilon of 10^-6
 
         if (delta > allowed_delta)  {
             printf("\nABORT - ERROR in Matrix Multiplication result - expected %6.2f, got %6.2f (delta %6.2f > allowed_delta %6.2f)\n",
-                sum_of_F32_reference, 
+                sum_of_F32_reference,
                 sum_of_Q4_result,
                 delta,
                 allowed_delta
             );
             exit(0);
         }
-        
-        // Running a different graph computation to make sure we override the CPU cache lines    
+
+        // Running a different graph computation to make sure we override the CPU cache lines
         ggml_graph_compute(ctx, &gf32);
-        
+
     }
-    
+
 }