TF_Buffer* value = TF_NewBuffer();
  TF_OperationGetAttrTensorShapeProto(oper, "v", value, s_);
  EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  EXPECT_EQ(bytes.length(), value->length);
  EXPECT_EQ(0, memcmp(bytes.data(), value->data, value->length));
  TF_DeleteBuffer(value);
}

TEST_F(CApiAttributesTest, TensorShapeProtoList) {
  string bytes1, bytes2;
  tensorflow::TensorShapeProto proto;

    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    const float* resolved_data =
        static_cast<const float*>(TF_TensorData(resolved));
    EXPECT_EQ(0, memcmp(m_float, resolved_data, 4 * sizeof(float)));
    TF_DeleteTensor(resolved);
    TFE_DeleteTensorHandle(copy_aliased);  // Note that this will delete copy.
    TFE_DeleteTensorHandle(on_host);
  }

-      && (__s1_len = strlen (s1), __s2_len = strlen (s2),		      \
-	  (!__string2_1bptr_p (s1) || __s1_len >= 4)			      \
-	  && (!__string2_1bptr_p (s2) || __s2_len >= 4))		      \
-      ? memcmp ((const char *) (s1), (const char *) (s2),		      \
-		(__s1_len < __s2_len ? __s1_len : __s2_len) + 1)	      \
-      : (__builtin_constant_p (s1) && __string2_1bptr_p (s1)		      \

    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag;
      continue;
    }
    EXPECT_EQ(TF_TensorByteSize(t), TF_TensorByteSize(tcopy)) << tag;
    EXPECT_EQ(
        0, memcmp(TF_TensorData(t), TF_TensorData(tcopy), TF_TensorByteSize(t)))
        << tag;
    TF_DeleteTensor(tcopy);
  }

  TF_DeleteDeviceList(devices);
  TF_DeleteTensor(t);
  TFE_DeleteTensorHandle(hcpu);

  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.
  int num_elems = TF_TensorElementCount(theta_tensor);
  vector<float> theta_data(num_elems);
  memcpy(theta_data.data(), TF_TensorData(theta_tensor),
         TF_TensorByteSize(theta_tensor));

  // Initialize space for the numerical gradient.
  vector<float> dtheta_approx(num_elems);

TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value) {
  float data[] = {value};
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, nullptr, 0, status);
  memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
  TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteTensor(t);

/* A trivial example of wrapping a C library using SWIG.  */

%{
#include <stdio.h>
#include <stdlib.h>
%}

%typemap(gotype) const char * "string"
%typemap(in) const char * %{
	$1 = malloc($input.n + 1);
	memcpy($1, $input.p, $input.n);
	$1[$input.n] = '\0';
%}
%typemap(freearg) const char * %{
	free($1);
%}

FILE *fopen(const char *name, const char *mode);
int fclose(FILE *);

    ASSERT_EQ(num_elem_numerical, num_elem_analytical);

    float* dnumerical = new float[num_elem_numerical]{0};
    memcpy(&dnumerical[0], TF_TensorData(numerical_tensor),
           TF_TensorByteSize(numerical_tensor));
    float* danalytical = new float[num_elem_analytical]{0};
    memcpy(&danalytical[0], TF_TensorData(analytical_tensor),
           TF_TensorByteSize(analytical_tensor));

        boolean unicode = getFlag(NTLMSSP_NEGOTIATE_UNICODE);
        String oemCp = unicode ? null : getOEMEncoding();

        String domainName = getDomain();
        byte[] domainBytes = null;
        if ( domainName != null && domainName.length() != 0 ) {
            domainBytes = unicode ? domainName.getBytes(UNI_ENCODING) : domainName.getBytes(oemCp);
            size += domainBytes.length;
        }

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retvals[0]);
  float sum = 0;
  EXPECT_EQ(sizeof(sum), TF_TensorByteSize(t));
  memcpy(&sum, TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  EXPECT_EQ(sum, 6.0);

  TFE_DeleteTensorHandle(h0);
  TFE_DeleteTensorHandle(h1);
  TFE_DeleteTensorHandle(h2);