def run_test(arr, axes=None):
for fn1 in self.array_transforms:
for fn2 in self.array_transforms:
arr_arg = fn1(arr)
axes_arg = fn2(axes) if axes is not None else None
self.match(array_ops.transpose(arr_arg, axes_arg),
np.transpose(arr_arg, axes))
def run_test(arr, axes=None):
for fn1 in self.array_transforms:
for fn2 in self.array_transforms:
arr_arg = fn1(arr)
axes_arg = fn2(axes) if axes is not None else None
# If transpose is called on a Tensor, it calls out to the
# Tensor.transpose method.
np_arr_arg = arr_arg
if isinstance(np_arr_arg, tf.Tensor):
np_arr_arg = np_arr_arg.numpy()
self.match(array_ops.transpose(arr_arg, axes_arg),
np.transpose(np_arr_arg, axes))