diff --git a/tensorflow/c/eager/BUILD b/tensorflow/c/eager/BUILD
index 65f537c7e31..1a075e8f610 100644
--- a/tensorflow/c/eager/BUILD
+++ b/tensorflow/c/eager/BUILD
@@ -428,6 +428,32 @@ tf_cuda_cc_test(
     ],
 )
 
+cc_library(
+    name = "mnist_gradients_util",
+    srcs = [
+        "mnist_gradients_util.cc",
+        "mnist_gradients_util.h",
+    ],
+    hdrs = [
+        "gradients.h",
+    ],
+    visibility = [
+        "//tensorflow:internal",
+    ],
+    deps = [
+        ":abstract_context",
+        ":abstract_operation",
+        ":abstract_tensor_handle",
+        ":c_api_unified_internal",
+        ":gradients_internal",
+        ":tape",
+        "//tensorflow/core/common_runtime/eager:attr_builder",
+        "//tensorflow/core/lib/llvm_rtti",
+        "@com_google_absl//absl/container:flat_hash_map",
+        "@com_google_absl//absl/strings",
+    ],
+)
+
 tf_cuda_cc_test(
     name = "mnist_gradients_test",
     size = "small",
@@ -444,6 +470,7 @@ tf_cuda_cc_test(
         ":c_api_test_util",
         ":c_api_unified_internal",
         ":gradients_internal",
+        ":mnist_gradients_util",
         "//tensorflow/c:c_api",
         "//tensorflow/c:c_test_util",
         "//tensorflow/c:tf_status_helper",
diff --git a/tensorflow/c/eager/mnist_gradients.cc b/tensorflow/c/eager/mnist_gradients.cc
index 665d6a6d8a7..89a02dd4276 100644
--- a/tensorflow/c/eager/mnist_gradients.cc
+++ b/tensorflow/c/eager/mnist_gradients.cc
@@ -29,7 +29,6 @@ limitations under the License.
 #include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
 
 
-
 namespace tensorflow {
 namespace gradients {
 namespace internal {
diff --git a/tensorflow/c/eager/mnist_gradients_test.cc b/tensorflow/c/eager/mnist_gradients_test.cc
index a7ef9fbca5e..db1966e7015 100644
--- a/tensorflow/c/eager/mnist_gradients_test.cc
+++ b/tensorflow/c/eager/mnist_gradients_test.cc
@@ -460,6 +460,9 @@ TEST_P(CppGradients, TestMatMulGrad) {
   s = MatMulGradModel(ctx.get(), {A.get(), B.get()}, absl::MakeSpan(outputs), registry);
   ASSERT_EQ(errors::OK, s.code()) << s.error_message();
 
+  // s = MatMulGradModel(ctx.get(), {A.get(), B.get()}, absl::MakeSpan(outputs), registry);
+  // ASSERT_EQ(errors::OK, s.code()) << s.error_message();
+
   TF_Tensor* dA_tensor;
   s = getValue(outputs[0], &dA_tensor);
   ASSERT_EQ(errors::OK, s.code()) << s.error_message();
@@ -584,13 +587,9 @@ TEST_P(CppGradients, TestMNISTForward2) {
  
   // Run the Forward Pass
   std::vector<AbstractTensorHandle*> outputs(2);
-<<<<<<< HEAD
   Status s = RunModel(MNISTForwardModel, ctx.get(), {X.get(), W1.get(), W2.get(), y.get()},
                absl::MakeSpan(outputs),
                /*use_function=*/!std::get<2>(GetParam()), registry);
-=======
-  Status s = MNISTForwardModel(ctx.get(), {X.get(), W1.get(), W2.get(), y.get()}, absl::MakeSpan(outputs), registry);
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
   ASSERT_EQ(errors::OK, s.code()) << s.error_message();
 
   // Verify the Results
@@ -601,10 +600,6 @@ TEST_P(CppGradients, TestMNISTForward2) {
   float result_data[6] = {0};
   memcpy(&result_data[0], TF_TensorData(scores_tensor), TF_TensorByteSize(scores_tensor));
   
-<<<<<<< HEAD
-=======
-  //float expected_scores [6] = {0f, 12.0f, -1.0f, -17.0f, 16.8f, -28.0f};
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
   float expected_scores [6] = {3.6f, -6.0f, 10.2f, -17.0f, 16.8f, -28.0f};
   float tolerance = 1e-3;
   for(int j = 0; j < 6; j++){
@@ -638,10 +633,7 @@ Status MatMulTransposeModel(AbstractContext* ctx,
  
   TapeVSpace vspace(ctx);
   auto tape = new Tape(/*persistent=*/false);
-<<<<<<< HEAD
   tape->Watch(ToId(X));
-=======
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
   tape->Watch(ToId(W1));  // Watch W1.
   std::vector<AbstractTensorHandle*> temp_outputs(1);
 
@@ -682,15 +674,11 @@ TEST_P(CppGradients, TestMatMulTranspose) {
   
   // Run the MatMul Op
   std::vector<AbstractTensorHandle*> outputs(1);
-<<<<<<< HEAD
   
   Status s = RunModel(MatMulTransposeModel, ctx.get(), {X.get(), W1.get()},
                absl::MakeSpan(outputs),
                /*use_function=*/!std::get<2>(GetParam()), registry);
 
-=======
-  Status s = MatMulTransposeModel(ctx.get(), {X.get(), W1.get()}, absl::MakeSpan(outputs), registry);
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
   ASSERT_EQ(errors::OK, s.code()) << s.error_message();
   
   // Verify the Results
@@ -701,10 +689,6 @@ TEST_P(CppGradients, TestMatMulTranspose) {
   float result_data[6] = {0};
   memcpy(&result_data[0], TF_TensorData(scores_tensor), TF_TensorByteSize(scores_tensor));
   
-<<<<<<< HEAD
-=======
-  
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
   float expected_scores [6] = {13.0f, 18.0f, 17.0f, 24.0f, 21.0f, 30.0f};
   float tolerance = 1e-3;
 
@@ -714,7 +698,6 @@ TEST_P(CppGradients, TestMatMulTranspose) {
   
 }
 
-<<<<<<< HEAD
 // Test Model to verify ReluGrad functionality
 Status ReluGradModel(AbstractContext* ctx,
                     absl::Span<AbstractTensorHandle* const> inputs,
@@ -927,8 +910,6 @@ TEST_P(CppGradients, TestSoftmaxLossGrad) {
   TF_DeleteTensor(dX_tensor);
 }
 
-=======
->>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
 
 // TODO(b/160888630): Enable this test with mlir after AddInputList is
 // supported. It is needed for AddN op which is used for gradient aggregation.