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Clean up deprecation warnings (#19654)

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* Clean up deprecation warnings

Notes:
Changed some strings in tests to raw strings, which will change the literal content of the strings as they are fed into whatever machine handles them.
Test cases for past in the past/past_key_values switch changed/removed due to warning of impending removal

* Add PILImageResampling abstraction for PIL.Image.Resampling
This commit is contained in:
David Yang
2022-10-19 01:34:47 +08:00
committed by GitHub
parent af556a09f6
commit a23819ed6a
51 changed files with 280 additions and 202 deletions
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42
tests/test_modeling_tf_common.py
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@@ -1984,9 +1984,14 @@ class UtilsFunctionsTest(unittest.TestCase):
@unpack_inputs
def call(
self, input_ids=None, past=None, output_attentions=None, output_hidden_states=None, return_dict=None
self,
input_ids=None,
past_key_values=None,
output_attentions=None,
output_hidden_states=None,
return_dict=None,
):
return input_ids, past, output_attentions, output_hidden_states, return_dict
return input_ids, past_key_values, output_attentions, output_hidden_states, return_dict
@unpack_inputs
def foo(self, pixel_values, output_attentions=None, output_hidden_states=None, return_dict=None):
@@ -1994,55 +1999,48 @@ class UtilsFunctionsTest(unittest.TestCase):
dummy_model = DummyModel()
input_ids = tf.constant([0, 1, 2, 3], dtype=tf.int64)
past = tf.constant([4, 5, 6, 7], dtype=tf.int64)
past_key_values = tf.constant([4, 5, 6, 7], dtype=tf.int64)
pixel_values = tf.constant([8, 9, 10, 11], dtype=tf.int64)
# test case 1: Pass inputs as keyword arguments; Booleans are inherited from the config.
output = dummy_model.call(input_ids=input_ids, past=past)
output = dummy_model.call(input_ids=input_ids, past_key_values=past_key_values)
tf.debugging.assert_equal(output[0], input_ids)
tf.debugging.assert_equal(output[1], past)
tf.debugging.assert_equal(output[1], past_key_values)
self.assertFalse(output[2])
self.assertFalse(output[3])
self.assertFalse(output[4])
# test case 2: Same as above, but with positional arguments.
output = dummy_model.call(input_ids, past)
output = dummy_model.call(input_ids, past_key_values)
tf.debugging.assert_equal(output[0], input_ids)
tf.debugging.assert_equal(output[1], past)
tf.debugging.assert_equal(output[1], past_key_values)
self.assertFalse(output[2])
self.assertFalse(output[3])
self.assertFalse(output[4])
# test case 3: We can also pack everything in the first input.
output = dummy_model.call(input_ids={"input_ids": input_ids, "past": past})
output = dummy_model.call(input_ids={"input_ids": input_ids, "past_key_values": past_key_values})
tf.debugging.assert_equal(output[0], input_ids)
tf.debugging.assert_equal(output[1], past)
tf.debugging.assert_equal(output[1], past_key_values)
self.assertFalse(output[2])
self.assertFalse(output[3])
self.assertFalse(output[4])
# test case 4: Explicit boolean arguments should override the config.
output = dummy_model.call(input_ids=input_ids, past=past, output_attentions=False, return_dict=True)
output = dummy_model.call(
input_ids=input_ids, past_key_values=past_key_values, output_attentions=False, return_dict=True
)
tf.debugging.assert_equal(output[0], input_ids)
tf.debugging.assert_equal(output[1], past)
tf.debugging.assert_equal(output[1], past_key_values)
self.assertFalse(output[2])
self.assertFalse(output[3])
self.assertTrue(output[4])
# test case 5: Unexpected arguments should raise an exception.
with self.assertRaises(ValueError):
output = dummy_model.call(input_ids=input_ids, past=past, foo="bar")
output = dummy_model.call(input_ids=input_ids, past_key_values=past_key_values, foo="bar")
# test case 6: Despite the above, `past_key_values` should be interchangeable with `past`
# (the decorator moves it to `past`, or vice-versa, depending on the signature).
output = dummy_model.call(input_ids=input_ids, past_key_values=past)
tf.debugging.assert_equal(output[0], input_ids)
tf.debugging.assert_equal(output[1], past)
self.assertFalse(output[2])
self.assertFalse(output[3])
self.assertFalse(output[4])
# test case 7: the decorator is independent from `main_input_name` -- it treats the first argument of the
# test case 6: the decorator is independent from `main_input_name` -- it treats the first argument of the
# decorated function as its main input.
output = dummy_model.foo(pixel_values=pixel_values)
tf.debugging.assert_equal(output[0], pixel_values)