Merge pull request #8 from roboticarm2000/fixwarnings

Fix warnings reported by VS 2019 and its code analyzer

include/k2c_activations.c

@@ -35,7 +35,7 @@ k2c_activationType * k2c_linear = k2c_linear_func;
 void k2c_exponential_func(float * x, const size_t size) {
 
     for (size_t i=0; i<size; ++i) {
-        x[i] = exp(x[i]);
+        x[i] = expf(x[i]);
     }
 }
 k2c_activationType * k2c_exponential = k2c_exponential_func;
@@ -95,7 +95,7 @@ k2c_activationType * k2c_hard_sigmoid = k2c_hard_sigmoid_func;
 void k2c_tanh_func(float * x, const size_t size) {
 
     for (size_t i=0; i<size; ++i) {
-        x[i] = tanh(x[i]);
+        x[i] = tanhf(x[i]);
     }
 }
 k2c_activationType * k2c_tanh = k2c_tanh_func;
@@ -111,7 +111,7 @@ k2c_activationType * k2c_tanh = k2c_tanh_func;
 void k2c_sigmoid_func(float * x, const size_t size) {
 
     for (size_t i=0; i < size; ++i) {
-        x[i] = 1/(1+exp(-x[i]));
+        x[i] = 1/(1+expf(-x[i]));
     }
 }
 k2c_activationType * k2c_sigmoid = k2c_sigmoid_func;
@@ -136,7 +136,7 @@ void k2c_softmax_func(float * x, const size_t size) {
     }
 
     for (size_t i=0; i < size; ++i) {
-        x[i] = exp(x[i]-xmax);
+        x[i] = expf(x[i]-xmax);
     }
 
     for (size_t i=0; i < size; ++i) {
@@ -161,7 +161,7 @@ k2c_activationType * k2c_softmax = k2c_softmax_func;
 void k2c_softplus_func(float * x, const size_t size) {
 
     for (size_t i=0; i < size; ++i) {
-        x[i] = log1p(exp(x[i]));
+        x[i] = log1pf(expf(x[i]));
     }
 }
 k2c_activationType * k2c_softplus = k2c_softplus_func;
@@ -177,7 +177,7 @@ k2c_activationType * k2c_softplus = k2c_softplus_func;
 void k2c_softsign_func(float * x, const size_t size) {
 
     for (size_t i=0; i < size; ++i) {
-        x[i] = x[i]/(1.0f + fabs(x[i]));
+        x[i] = x[i]/(1.0f + fabsf(x[i]));
     }
 }
 k2c_activationType * k2c_softsign = k2c_softsign_func;
@@ -237,7 +237,7 @@ void k2c_ELU(float * x, const size_t size, const float alpha) {
 
     for (size_t i=0; i < size; ++i) {
         if (x[i] <= 0.0f) {
-            x[i] = alpha*expm1(x[i]);
+            x[i] = alpha*expm1f(x[i]);
         }
     }
 }

include/k2c_helper_functions.c

@@ -330,6 +330,10 @@ void k2c_flip(k2c_tensor *A, const size_t axis) {
  */
 float* k2c_read_array(const char* filename, const size_t array_size) {
     float* ptr = (float*) malloc(array_size * sizeof(float));
+    if (!ptr) {
+        printf("cannot allocate memory %s \n", filename);
+        exit(-1);
+    }
     size_t ctr = 0;
     FILE *finp;
     int foo;

include/k2c_recurrent_layers.c

@@ -383,7 +383,7 @@ void k2c_gru(k2c_tensor* output, const k2c_tensor* input, float * state,
         }
     }
     else {
-        for (int i=0; i<in_height; ++i) {
+        for (size_t i=0; i<in_height; ++i) {
             k2c_grucell(state, &input->array[i*in_width], kernel, recurrent_kernel, bias,
                         fwork, reset_after, recurrent_activation, output_activation);
             if (return_sequences) {

keras2c/make_test_suite.py

@@ -73,8 +73,6 @@ def make_test_suite(model, function_name, malloc_vars, num_tests=10, stateful=Fa
     s += 'float maxabs(k2c_tensor *tensor1, k2c_tensor *tensor2);\n'
     s += 'struct timeval GetTimeStamp(); \n \n'
     file.write(s)
-    s = 'int main(){\n'
-    file.write(s)
     for i in range(num_tests):
         if i == num_tests//2 and stateful:
             model.reset_states()
@@ -109,6 +107,9 @@ def make_test_suite(model, function_name, malloc_vars, num_tests=10, stateful=Fa
                                          model_outputs[j] + '_test' + str(i+1)))
             file.write(Weights2C.array2c(np.zeros(output.shape), 'c_' +
                                          model_outputs[j] + '_test' + str(i+1)))
+    s = 'int main(){\n'
+    file.write(s)
+
     s = ' float errors[' + str(num_tests*num_outputs) + '];\n'
     s += ' size_t num_tests = ' + str(num_tests) + '; \n'
     s += 'size_t num_outputs = ' + str(num_outputs) + '; \n'
@@ -138,7 +139,7 @@ def make_test_suite(model, function_name, malloc_vars, num_tests=10, stateful=Fa
     file.write('\n')
     s = 'clock_t t1 = clock(); \n'
     s += 'printf("Average time over ' + str(num_tests) + \
-        ' tests: %e s \\n\", \n (double)(t1-t0)/(double)CLOCKS_PER_SEC/(double)' + \
+        ' tests: %e s \\n\", \n ((double)t1-t0)/(double)CLOCKS_PER_SEC/(double)' + \
         str(num_tests) + '); \n'
     file.write(s)
 
@@ -169,7 +170,7 @@ def make_test_suite(model, function_name, malloc_vars, num_tests=10, stateful=Fa
     float x = 0; \n
     float y = 0; \n
     for(size_t i=0; i<tensor1->numel; i++){\n
-    y = fabs(tensor1->array[i]-tensor2->array[i]);
+    y = fabsf(tensor1->array[i]-tensor2->array[i]);
     if (y>x) {x=y;}}
     return x;}\n\n"""
     file.write(s)

keras2c/weights2c.py

@@ -80,9 +80,9 @@ def array2c(array, name, malloc=False):
                     elif temp[i] == -np.inf:
                         s += "-HUGE_VALF,"
                     else:
-                        s += "{:+.8e}".format(temp[i]) + ','
+                        s += "{:+.8e}f".format(temp[i]) + ','
                     count += 1
-                    if (count) % 5 is 0:
+                    if (count) % 5 == 0:
                         s += '\n'
                 s += '}; \n'
             s += 'k2c_tensor ' + name + ' = {&' + name + \