if (attr == null) {
                continue;
            }

            for (int i = 0; i < attr.size(); i++) {
                final Object attrValue = attr.get(i);
                if (attrValue != null) {
                    final String entryDn = attrValue.toString();

                    if (logger.isDebugEnabled()) {
                        logger.debug("entryDn: {}", entryDn);
                    }

                                                TF_Status* status);

// `proto` should point to a sequence of bytes of length `proto_len`
// representing a binary serialization of an AttrValue protocol
// buffer.
TF_CAPI_EXPORT extern void TF_SetAttrValueProto(TF_OperationDescription* desc,
                                                const char* attr_name,

                        const char* attr_name, const char* attr_value,
                        TF_Operation** op) {
  TF_OperationDescription* desc = TF_NewOperation(graph, "Placeholder", name);
  TF_SetAttrType(desc, "dtype", TF_INT32);
  TF_SetAttrString(desc, attr_name, attr_value, strlen(attr_value));
  *op = TF_FinishOperation(desc, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TFE_DeleteTensorHandle(tensor_handle);

  tensorflow::AttrValue i_list_values;
  for (int i = 0; i < 4; ++i) {
    i_list_values.mutable_list()->add_i(1);
  }
  SetOpAttrValueScalar(ctx, op, i_list_values, "ksize", status);
  SetOpAttrValueScalar(ctx, op, i_list_values, "strides", status);

  tensorflow::AttrValue padding_value;
  *padding_value.mutable_s() = "VALID";

  EXPECT_EQ(0, TF_OperationNumControlInputs(feed));
  EXPECT_EQ(0, TF_OperationNumControlOutputs(feed));

  tensorflow::AttrValue attr_value;
  ASSERT_TRUE(GetAttrValue(feed, "dtype", &attr_value, s)) << TF_Message(s);
  EXPECT_EQ(attr_value.type(), tensorflow::DT_INT32);

  // Test not found errors in TF_Operation*() query functions.
  EXPECT_EQ(-1, TF_OperationOutputListLength(feed, "bogus", s));