diff --git a/lib/kernels/test/src/test_concat_kernel.cc b/lib/kernels/test/src/test_concat_kernel.cc
index bf2a521b4e..eb6791fc14 100644
--- a/lib/kernels/test/src/test_concat_kernel.cc
+++ b/lib/kernels/test/src/test_concat_kernel.cc
@@ -20,11 +20,11 @@ TEST_SUITE(FF_TEST_SUITE) {
     Allocator allocator = create_local_cuda_memory_allocator();
 
     SUBCASE("forward_kernel") {
-      std::vector<GenericTensorAccessorR> input_accessors =
-          repeat(num_inputs, [&]() {
-            return read_only_accessor_from_write_accessor(
-                create_random_filled_accessor_w(input_shape, allocator));
-          });
+      std::vector<GenericTensorAccessorR> input_accessors(num_inputs);
+      generate_n(input_accessors.begin(), num_inputs, [&]() {
+        return read_only_accessor_from_write_accessor(
+            create_random_filled_accessor_w(input_shape, allocator));
+      });
       GenericTensorAccessorW output_accessor =
           allocator.allocate_tensor(output_shape);
 
@@ -44,13 +44,14 @@ TEST_SUITE(FF_TEST_SUITE) {
       GenericTensorAccessorR output_grad_accessor =
           read_only_accessor_from_write_accessor(
               create_random_filled_accessor_w(output_shape, allocator));
-      std::vector<GenericTensorAccessorW> input_grad_accessors = repeat(
-          num_inputs, [&]() { return allocator.allocate_tensor(input_shape); });
-
-      Kernels::Concat::backward_kernel(managed_stream.raw_stream(),
-                                       output_grad_accessor,
-                                       input_grad_accessors,
-                                       concat_axis);
+      std::vector<GenericTensorAccessorW> input_grad_accessors(num_inputs);
+      generate_n(input_grad_accessors.begin(), num_inputs, [&]() {
+        return allocator.allocate_tensor(input_shape);
+
+        Kernels::Concat::backward_kernel(managed_stream.raw_stream(),
+                                         output_grad_accessor,
+                                         input_grad_accessors,
+                                         concat_axis);
+    }
     }
   }
-}
diff --git a/lib/kernels/test/src/test_dropout.cc b/lib/kernels/test/src/test_dropout.cc
index 81f3c7183a..8a7c21c0fb 100644
--- a/lib/kernels/test/src/test_dropout.cc
+++ b/lib/kernels/test/src/test_dropout.cc
@@ -25,7 +25,7 @@ TEST_SUITE(FF_TEST_SUITE) {
         managed_handle.raw_handle(), dropout_rate, seed, shape, allocator);
 
     auto get_zero_count = [](std::vector<float> const &data) {
-      return count(data, [](float x) { return x == 0.0f; });
+      return count(data.begin(), data.end(), [](float x) { return x == 0.0f; });
     };
 
     SUBCASE("forward_kernel") {
diff --git a/lib/kernels/test/src/test_split_kernel.cc b/lib/kernels/test/src/test_split_kernel.cc
index 7cc2b28c9e..f2346c9244 100644
--- a/lib/kernels/test/src/test_split_kernel.cc
+++ b/lib/kernels/test/src/test_split_kernel.cc
@@ -23,7 +23,8 @@ TEST_SUITE(FF_TEST_SUITE) {
       GenericTensorAccessorW input_accessor =
           create_random_filled_accessor_w(input_shape, allocator);
 
-      std::vector<float *> output_ptrs = repeat(num_outputs, [&]() {
+      std::vector<float *> output_ptrs(num_outputs);
+      generate_n(output_ptrs.begin(), num_outputs, [&]() {
         GenericTensorAccessorW output_accessor =
             allocator.allocate_tensor(output_shape);
         return output_accessor.get_float_ptr();
diff --git a/lib/kernels/test/src/test_utils.h b/lib/kernels/test/src/test_utils.h
index abce3fd444..264d66c08a 100644
--- a/lib/kernels/test/src/test_utils.h
+++ b/lib/kernels/test/src/test_utils.h
@@ -7,6 +7,8 @@
 #include "kernels/managed_per_device_ff_handle.h"
 #include <random>
 
+using namespace FlexFlow;
+
 GenericTensorAccessorW create_random_filled_accessor_w(TensorShape const &shape,
                                                        Allocator &allocator,
                                                        bool cpu_fill = false);
@@ -42,7 +44,8 @@ std::vector<T> load_data_to_host_from_device(GenericTensorAccessorR accessor) {
 
 template <typename T>
 bool contains_non_zero(std::vector<T> &data) {
-  return !all_of(data, [](T const &val) { return val == 0; });
+  return !all_of(
+      data.begin(), data.end(), [](T const &val) { return val == 0; });
 }
 
 #endif