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cleanup tf unittests: part 2 (#6260)

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* cleanup torch unittests: part 2

* remove trailing comma added by isort, and which breaks flake

* one more comma

* revert odd balls

* part 3: odd cases

* more ["key"] -> .key refactoring

* .numpy() is not needed

* more unncessary .numpy() removed

* more simplification
This commit is contained in:
Stas Bekman
2020-08-13 01:29:06 -07:00
committed by GitHub
parent bc820476a5
commit e983da0e7d
21 changed files with 159 additions and 239 deletions
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60
tests/test_modeling_tf_xlnet.py
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@@ -158,12 +158,10 @@ class TFXLNetModelTester:
no_mems_outputs = model(inputs)
self.parent.assertEqual(len(no_mems_outputs), 1)
self.parent.assertEqual(result.last_hidden_state.shape, (self.batch_size, self.seq_length, self.hidden_size))
self.parent.assertListEqual(
list(result["last_hidden_state"].shape), [self.batch_size, self.seq_length, self.hidden_size]
)
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
def create_and_check_xlnet_lm_head(
@@ -191,27 +189,15 @@ class TFXLNetModelTester:
inputs_3 = {"input_ids": input_ids_q, "perm_mask": perm_mask, "target_mapping": target_mapping}
logits, _ = model(inputs_3).to_tuple()
result = {
"mems_1": [mem.numpy() for mem in mems_1],
"all_logits_1": all_logits_1.numpy(),
"mems_2": [mem.numpy() for mem in mems_2],
"all_logits_2": all_logits_2.numpy(),
}
self.parent.assertEqual(all_logits_1.shape, (self.batch_size, self.seq_length, self.vocab_size))
self.parent.assertListEqual(
list(result["all_logits_1"].shape), [self.batch_size, self.seq_length, self.vocab_size]
[mem.shape for mem in mems_1],
[(self.seq_length, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
self.parent.assertEqual(all_logits_2.shape, (self.batch_size, self.seq_length, self.vocab_size))
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_1"]),
[[self.seq_length, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
)
self.parent.assertListEqual(
list(result["all_logits_2"].shape), [self.batch_size, self.seq_length, self.vocab_size]
)
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems_2"]),
[[self.mem_len, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in mems_2],
[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
def create_and_check_xlnet_qa(
@@ -233,11 +219,11 @@ class TFXLNetModelTester:
inputs = {"input_ids": input_ids_1, "attention_mask": input_mask, "token_type_ids": segment_ids}
result = model(inputs)
self.parent.assertListEqual(list(result["start_logits"].shape), [self.batch_size, self.seq_length])
self.parent.assertListEqual(list(result["end_logits"].shape), [self.batch_size, self.seq_length])
self.parent.assertEqual(result.start_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertEqual(result.end_logits.shape, (self.batch_size, self.seq_length))
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
def create_and_check_xlnet_sequence_classif(
@@ -258,10 +244,10 @@ class TFXLNetModelTester:
result = model(input_ids_1)
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.type_sequence_label_size])
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.type_sequence_label_size))
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
def create_and_check_xlnet_for_token_classification(
@@ -286,12 +272,10 @@ class TFXLNetModelTester:
# 'token_type_ids': token_type_ids
}
result = model(inputs)
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.seq_length, config.num_labels))
self.parent.assertListEqual(
list(result["logits"].shape), [self.batch_size, self.seq_length, config.num_labels]
)
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size, self.hidden_size)] * self.num_hidden_layers,
)
def create_and_check_xlnet_for_multiple_choice(
@@ -320,10 +304,10 @@ class TFXLNetModelTester:
}
result = model(inputs)
self.parent.assertListEqual(list(result["logits"].shape), [self.batch_size, self.num_choices])
self.parent.assertEqual(result.logits.shape, (self.batch_size, self.num_choices))
self.parent.assertListEqual(
list(list(mem.shape) for mem in result["mems"]),
[[self.seq_length, self.batch_size * self.num_choices, self.hidden_size]] * self.num_hidden_layers,
[mem.shape for mem in result.mems],
[(self.seq_length, self.batch_size * self.num_choices, self.hidden_size)] * self.num_hidden_layers,
)
def prepare_config_and_inputs_for_common(self):