" outputs for TPUReplicatedOutput, but got ", expected_outputs));
      TF_SetStatus(status, TF_INVALID_ARGUMENT, message.c_str());
      return result;
    }
    if (absl::holds_alternative<TFE_TensorHandle*>(inputs[0])) {
      TF_SetStatus(status, TF_INVALID_ARGUMENT,
                   "Expected the input to "
                   "TPUReplicatedOutput to be a parallel tensor (placed on the "

    TF_AttrBuilder* builder, const char* device_type, TF_Status* status);

// For argument number input_index, fetch the corresponding number_attr that
// needs to be updated with the argument length of the input list.
// Returns nullptr if there is any problem like op_name is not found, or the
// argument does not support this attribute type.
TF_CAPI_EXPORT extern const char* TF_GetNumberAttrForOpListInput(

        } else {
          return TF_SetStatus(status, TF_INVALID_ARGUMENT, "Not a directory!");
        }
      };
  GcsFileStat stat;
  MaybeAppendSlash(&dir);
  gcs_file->stat_cache->LookupOrCompute(dir, &stat, compute_func, status);
  if (TF_GetCode(status) != TF_OK && TF_GetCode(status) != TF_INVALID_ARGUMENT)
    return false;
  if (TF_GetCode(status) == TF_INVALID_ARGUMENT) {
    TF_SetStatus(status, TF_OK, "");
    return false;

  TFE_TensorHandle* tensor(size_t index) const { return tensors_[index].get(); }

  // If the `shape` argument to `FromTensorHandles` is specified, returns that.
  //
  // Otherwise if all of the tensors have the same shape, returns that via the
  // `shape` output argument. This blocks waiting for async tensors, may return
  // a delayed bad status encountered during async execution, and will return a

*   Extends `tf.keras.layers.Lambda` layers to support multi-argument lambdas,
    and keyword arguments when calling the layer.
*   Functional models now get constructed if *any* tensor in a layer call's
    arguments/keyword arguments comes from a keras input. Previously the
    functional api would only work if all of the elements in the first argument
    to the layer came from a keras input.

// Returns the length (number of tensors) of the input argument `input_name`
// found in the provided `op`.
TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op,
                                               const char* input_name,
                                               TF_Status* status);

// Returns the length (number of tensors) of the output argument `output_name`
// found in the provided `op`.

  parser.add_argument('build_log',
                      help='Path to a build log.')
  parser.add_argument('--xml-out-path',
                      required=False,
                      help='Path to which to output '
                           'the JUnit-based XML with ResultStore links.')
  parser.add_argument('--print',
                      action='store_true', dest='print', default=False,

  TF_DeleteFunction(funcs[0]);
}

TEST_F(CApiExperimentalFunctionTest, EmptyGraphRemoveNonExistentFunction) {
  TF_GraphRemoveFunction(func_graph_, "wrong_name", s_);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s_));
  EXPECT_EQ(string("Tried to remove non-existent function 'wrong_name'."),
            string(TF_Message(s_)));
}

TEST_F(CApiExperimentalFunctionTest, GraphRemoveNonExistentFunction) {

 # endif
 #endif
 
+/* Undefine (also defined in libc-symbols.h).  */
+#undef __attribute_copy__
+#if __GNUC_PREREQ (9, 0)
+/* Copies attributes from the declaration or type referenced by
+   the argument.  */
+# define __attribute_copy__(arg) __attribute__ ((__copy__ (arg)))
+#else
+# define __attribute_copy__(arg)
+#endif
+
 #endif	 /* sys/cdefs.h */
diff --git a/stdlib/setenv.c b/stdlib/setenv.c

  // 1) nullptr indicates tensor is compact and row-majored.
  // 2) fill in the strides array as the real case for compact row-major data.
  // Here we choose option 2, since some frameworks didn't handle the strides
  // argument properly.
  dlm_tensor->dl_tensor.strides = stride_arr->data();

  dlm_tensor->dl_tensor.byte_offset =
      0;  // TF doesn't handle the strides and byte_offsets here
  return static_cast<void*>(dlm_tensor);
}