def testMultipleInputs(self):
inputs_info = {
"x": tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=False),
"y": tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=False),
}
def _check(dict_inputs):
self.assertEqual(len(dict_inputs), 2)
for key in ("x", "y"):
self.assertEqual(dict_inputs[key].dtype, tf.float32)
self.assertTrue(dict_inputs[key].shape.is_compatible_with([None]))
_check(module._convert_dict_inputs({"x": [1, 2], "y": [1, 2]},
inputs_info))
with self.assertRaisesRegexp(TypeError, r"missing \['x', 'y'\]"):
module._convert_dict_inputs(None, inputs_info)
with self.assertRaisesRegexp(TypeError, r"missing \['x', 'y'\]"):
module._convert_dict_inputs({}, inputs_info)
with self.assertRaisesRegexp(TypeError, r"missing \['x', 'y'\]"):
module._convert_dict_inputs({"z": 1}, inputs_info)
with self.assertRaisesRegexp(
TypeError, "Signature expects multiple inputs. Use a dict."):
module._convert_dict_inputs(1, inputs_info)
def get_output_info_dict(self, signature=None, tags=None):
result = {
"default": tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=False),
}
if tags == set(["special"]) and signature == "extra":
result["z"] = result["default"]
return result
def get_input_info_dict(self, signature=None, tags=None):
result = {
"x":
tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=(signature == "sparse"
and tags == set(["special"]))),
}
if tags == set(["special"]) and signature == "extra":
result["y"] = result["x"]
return result
def testSingleInput(self):
inputs_info = {
"x": tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=False),
}
def _check(dict_inputs):
self.assertEqual(len(dict_inputs), 1)
self.assertEqual(dict_inputs["x"].dtype, tf.float32)
self.assertTrue(dict_inputs["x"].shape.is_compatible_with([None]))
_check(module._convert_dict_inputs([1, 2], inputs_info))
_check(module._convert_dict_inputs({"x": [1, 2]}, inputs_info))
with self.assertRaisesRegexp(TypeError, r"missing \['x'\]"):
module._convert_dict_inputs(None, inputs_info)
with self.assertRaisesRegexp(TypeError, r"extra given \['y'\]"):
module._convert_dict_inputs({"x": [1, 2], "y": [1, 2]}, inputs_info)
def get_input_info_dict(self, signature=None, tags=None):
if signature == "ragged" and tags == set(["special"]):
result = {
"x":
tensor_info.ParsedTensorInfo.from_type_spec(
type_spec=tf.RaggedTensorSpec(
shape=[None, None, None, 3], dtype=tf.float32,
ragged_rank=2)),
}
else:
result = {
"x":
tensor_info.ParsedTensorInfo(
tf.float32,
tf.TensorShape([None]),
is_sparse=(signature == "sparse" and
tags == set(["special"]))),
}
if tags == set(["special"]) and signature == "extra":
result["y"] = result["x"]
return result
