fix: kernels test building errors

flexflow · Dec 16, 2024 · a8ce685 · a8ce685
1 parent d416c27
commit a8ce685
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Showing 3 changed files with 45 additions and 18 deletions.
diff --git a/lib/kernels/test/src/test_concat_kernel.cc b/lib/kernels/test/src/test_concat_kernel.cc
@@ -20,17 +20,16 @@ TEST_SUITE(FF_TEST_SUITE) {
     Allocator allocator = create_local_cuda_memory_allocator();
 
     SUBCASE("forward_kernel") {
-      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));
-      });
+      std::vector<GenericTensorAccessorR> input_accessors =
+          repeat<GenericTensorAccessorR>(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);
 
       Kernels::Concat::forward_kernel(managed_stream.raw_stream(),
-                                      output_accessor,
-                                      input_accessors,
+                                      output_accessor, input_accessors,
                                       concat_axis);
 
       std::vector<float> host_output_data =
@@ -44,14 +43,13 @@ 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(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);
-    }
+      std::vector<GenericTensorAccessorW> input_grad_accessors =
+          repeat<GenericTensorAccessorW>(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
@@ -24,8 +24,8 @@ TEST_SUITE(FF_TEST_SUITE) {
     DropoutPerDeviceState state = Kernels::Dropout::init_kernel(
         managed_handle.raw_handle(), dropout_rate, seed, shape, allocator);
 
-    auto get_zero_count = [](std::vector<float> const &data) {
-      return count(data.begin(), data.end(), [](float x) { return x == 0.0f; });
+    auto get_zero_count = [](const std::vector<float>& data) {
+        return std::count_if(data.begin(), data.end(), [](float x) { return x == 0.0f; });
     };
 
     SUBCASE("forward_kernel") {

diff --git a/lib/kernels/test/src/test_utils.h b/lib/kernels/test/src/test_utils.h
@@ -5,6 +5,10 @@
 #include "kernels/local_cuda_allocator.h"
 #include "kernels/managed_ff_stream.h"
 #include "kernels/managed_per_device_ff_handle.h"
+#include <doctest/doctest.h>
+#include <vector>
+#include <string>
+#include <sstream>
 #include <random>
 
 using namespace FlexFlow;
@@ -48,4 +52,29 @@ bool contains_non_zero(std::vector<T> &data) {
       data.begin(), data.end(), [](T const &val) { return val == 0; });
 }
 
+template <typename T, typename Func>
+std::vector<T> repeat(std::size_t n, Func&& func) {
+    std::vector<T> result;
+    // result.reserve(n); // Sometimes we don't have default constructor for T
+    for (std::size_t i = 0; i < n; ++i) {
+        result.push_back(func());
+    }
+    return result;
+}
+
+// Specialize doctest's StringMaker for std::vector<float>
+template <>
+struct doctest::StringMaker<std::vector<float>> {
+    static doctest::String convert(const std::vector<float>& vec) {
+        std::ostringstream oss;
+        for (size_t i = 0; i < vec.size(); ++i) {
+            oss << vec[i];
+            if (i != vec.size() - 1) {
+                oss << ", ";
+            }
+        }
+        return doctest::String(("[" + oss.str() + "]").c_str());
+    }
+};
+
 #endif