def testSetTensorShapeEmpty(self):
tensor = array_ops.placeholder(shape=[None, 3, 5],
dtype=dtypes.float32)
self.assertEqual([None, 3, 5], tensor.shape.as_list())
convert_saved_model.set_tensor_shapes([tensor], {})
self.assertEqual([None, 3, 5], tensor.shape.as_list())
def testSetTensorShapeNoneValid(self):
tensor = array_ops.placeholder(dtype=dtypes.float32)
self.assertEqual(None, tensor.shape)
convert_saved_model.set_tensor_shapes([tensor],
{"Placeholder": [1, 3, 5]})
self.assertEqual([1, 3, 5], tensor.shape.as_list())
def testSetTensorShapeDimensionInvalid(self):
# Tests set_tensor_shape where the shape passed in is incompatiable.
tensor = array_ops.placeholder(shape=[None, 3, 5], dtype=dtypes.float32)
self.assertEqual([None, 3, 5], tensor.shape.as_list())
with self.assertRaises(ValueError) as error:
convert_saved_model.set_tensor_shapes([tensor],
{"Placeholder": [1, 5, 5]})
self.assertIn("The shape of tensor 'Placeholder' cannot be changed",
str(error.exception))
self.assertEqual([None, 3, 5], tensor.shape.as_list())
def testSetTensorShapeInvalid(self):
tensor = array_ops.placeholder(shape=[None, 3, 5],
dtype=dtypes.float32)
self.assertEqual([None, 3, 5], tensor.shape.as_list())
with self.assertRaises(ValueError) as error:
convert_saved_model.set_tensor_shapes([tensor],
{"invalid-input": [5, 3, 5]})
self.assertEqual(
"Invalid tensor 'invalid-input' found in tensor shapes map.",
str(error.exception))
self.assertEqual([None, 3, 5], tensor.shape.as_list())
def testSetTensorShapeArrayInvalid(self):
# Tests set_tensor_shape where the tensor name passed in doesn't exist.
tensor = array_ops.placeholder(shape=[None, 3, 5], dtype=dtypes.float32)
self.assertEqual([None, 3, 5], tensor.shape.as_list())
with self.assertRaises(ValueError) as error:
convert_saved_model.set_tensor_shapes([tensor],
{"invalid-input": [5, 3, 5]})
self.assertEqual(
"Invalid tensor 'invalid-input' found in tensor shapes map.",
str(error.exception))
self.assertEqual([None, 3, 5], tensor.shape.as_list())
def testSetTensorShapeNoneValid(self):
tensor = array_ops.placeholder(dtype=dtypes.float32)
self.assertEqual(None, tensor.shape)
convert_saved_model.set_tensor_shapes([tensor], {"Placeholder": [1, 3, 5]})
self.assertEqual([1, 3, 5], tensor.shape.as_list())
def testSetTensorShapeEmpty(self):
tensor = array_ops.placeholder(shape=[None, 3, 5], dtype=dtypes.float32)
self.assertEqual([None, 3, 5], tensor.shape.as_list())
convert_saved_model.set_tensor_shapes([tensor], {})
self.assertEqual([None, 3, 5], tensor.shape.as_list())
