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Unverified Commit 31f2437f authored by Patrick von Platen's avatar Patrick von Platen Committed by GitHub
Browse files

Merge pull request #3191 from patrickvonplaten/add_integration_tests_lm_generate_torch_tf 

Add integration tests lm generate torch tf
parents 5ca356a4 9050ffe0
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Showing with 1077 additions and 191 deletions
src/transformers/modeling_tf_xlm.py
View file @ 31f2437f
......@@ -408,7 +408,7 @@ class TFXLMMainLayer(tf.keras.layers.Layer):
inputs_embeds = self.embeddings(input_ids)
tensor = inputs_embeds + self.position_embeddings(position_ids)
if langs is not None and self.use_lang_emb:
if langs is not None and self.use_lang_emb and self.n_langs > 1:
tensor = tensor + self.lang_embeddings(langs)
if token_type_ids is not None:
tensor = tensor + self.embeddings(token_type_ids)
......
tests/test_modeling_ctrl.py
View file @ 31f2437f
......@@ -219,30 +219,31 @@ class CTRLModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_ctrl(self):
model = CTRLLMHeadModel.from_pretrained("ctrl")
input_ids = torch.Tensor([[11859, 586, 20984, 8]]).long() # Legal My neighbor is
input_ids = torch.tensor(
[[11859, 0, 1611, 8]], dtype=torch.long, device=torch_device
) # Legal the president is
expected_output_ids = [
11859,
586,
20984,
0,
1611,
8,
13391,
3,
980,
8258,
72,
327,
148,
5,
150,
26449,
2,
53,
29,
226,
3,
780,
49,
19,
348,
469,
3,
980,
] # Legal My neighbor is refusing to pay rent after 2 years and we are having to force him to pay
torch.manual_seed(0)
output_ids = model.generate(input_ids)
2595,
48,
20740,
246533,
246533,
19,
30,
5,
] # Legal the president is a good guy and I don't want to lose my job. \n \n I have a
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_gpt2.py
View file @ 31f2437f
......@@ -223,7 +223,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
# append to next input_ids and attn_mask
next_input_ids = torch.cat([input_ids, next_tokens], dim=-1)
attn_mask = torch.cat(
[attn_mask, torch.ones((attn_mask.shape[0], 1), dtype=torch.long, device=torch_device)], dim=1
[attn_mask, torch.ones((attn_mask.shape[0], 1), dtype=torch.long, device=torch_device)], dim=1,
)
# get two different outputs
......@@ -343,39 +343,36 @@ class GPT2ModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_gpt2(self):
model = GPT2LMHeadModel.from_pretrained("gpt2")
input_ids = torch.Tensor([[464, 3290, 318, 13779]]).long() # The dog is cute
input_ids = torch.tensor([[464, 3290]], dtype=torch.long, device=torch_device) # The dog
expected_output_ids = [
464,
3290,
318,
13779,
1165,
13,
632,
7832,
284,
6437,
319,
502,
373,
1043,
287,
257,
2214,
1474,
262,
16246,
286,
2688,
290,
318,
922,
329,
502,
357,
1169,
2688,
27262,
13,
198,
198,
464,
3290,
] # The dog is cute too. It likes to rub on me and is good for me (the dog
torch.manual_seed(0)
output_ids = model.generate(input_ids)
] # The dog was found in a field near the intersection of West and West Streets.\n\nThe dog
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
@slow
def test_lm_generate_distilgpt2(self):
model = GPT2LMHeadModel.from_pretrained("distilgpt2")
input_ids = torch.Tensor([[464, 1893]]).long() # The president
input_ids = torch.tensor([[464, 1893]], dtype=torch.long, device=torch_device) # The president
expected_output_ids = [
464,
1893,
......
tests/test_modeling_openai.py
View file @ 31f2437f
......@@ -123,7 +123,15 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
head_mask = ids_tensor([self.num_hidden_layers, self.num_attention_heads], 2)
return config, input_ids, head_mask, token_type_ids, sequence_labels, token_labels, choice_labels
return (
config,
input_ids,
head_mask,
token_type_ids,
sequence_labels,
token_labels,
choice_labels,
)
def check_loss_output(self, result):
self.parent.assertListEqual(list(result["loss"].size()), [])
......@@ -139,7 +147,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
result = {"sequence_output": sequence_output}
self.parent.assertListEqual(
list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size]
list(result["sequence_output"].size()), [self.batch_size, self.seq_length, self.hidden_size],
)
def create_and_check_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
......@@ -153,7 +161,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size]
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)
def create_and_check_double_lm_head_model(self, config, input_ids, head_mask, token_type_ids, *args):
......@@ -167,7 +175,7 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size]
list(result["lm_logits"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)
def prepare_config_and_inputs_for_common(self):
......@@ -181,7 +189,11 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
token_labels,
choice_labels,
) = config_and_inputs
inputs_dict = {"input_ids": input_ids, "token_type_ids": token_type_ids, "head_mask": head_mask}
inputs_dict = {
"input_ids": input_ids,
"token_type_ids": token_type_ids,
"head_mask": head_mask,
}
return config, inputs_dict
......@@ -215,30 +227,29 @@ class OPENAIGPTModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_openai_gpt(self):
model = OpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
input_ids = torch.Tensor([[481, 2585, 544, 4957]]).long() # The dog is cute
input_ids = torch.tensor([[481, 4735, 544]], dtype=torch.long, device=torch_device) # the president is
expected_output_ids = [
481,
2585,
4735,
544,
4957,
669,
512,
761,
5990,
271,
645,
246,
963,
870,
762,
239,
244,
40477,
244,
249,
719,
881,
487,
535,
976,
2479,
544,
240,
487,
804,
1296,
2891,
512,
] # the dog is cute when you're annoyed : if he's really stupid, he 'll stop fighting you
torch.manual_seed(0)
output_ids = model.generate(input_ids)
244,
603,
481,
] # the president is a very good man. " \n " i\'m sure he is, " said the
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_tf_ctrl.py
View file @ 31f2437f
......@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_tf, slow
if is_tf_available():
import tensorflow as tf
from transformers.modeling_tf_ctrl import TFCTRLModel, TFCTRLLMHeadModel, TF_CTRL_PRETRAINED_MODEL_ARCHIVE_MAP
......@@ -202,3 +203,35 @@ class TFCTRLModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in list(TF_CTRL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFCTRLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
class TFCTRLModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_ctrl(self):
model = TFCTRLLMHeadModel.from_pretrained("ctrl")
input_ids = tf.convert_to_tensor([[11859, 0, 1611, 8]], dtype=tf.int32) # Legal the president is
expected_output_ids = [
11859,
0,
1611,
8,
5,
150,
26449,
2,
19,
348,
469,
3,
2595,
48,
20740,
246533,
246533,
19,
30,
5,
] # Legal the president is a good guy and I don't want to lose my job. \n \n I have a
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_tf_gpt2.py
View file @ 31f2437f
......@@ -328,13 +328,35 @@ class TFGPT2ModelTest(TFModelTesterMixin, unittest.TestCase):
self.assertIsNotNone(model)
def prepare_generation_special_tokens():
return {"bos_token_id": 50256, "eos_token_id": 50256}
class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
special_tokens = prepare_generation_special_tokens()
@slow
def test_lm_generate_gpt2(self):
model = TFGPT2LMHeadModel.from_pretrained("gpt2")
input_ids = tf.convert_to_tensor([[464, 3290]], dtype=tf.int32) # The dog
expected_output_ids = [
464,
3290,
373,
1043,
287,
257,
2214,
1474,
262,
16246,
286,
2688,
290,
2688,
27262,
13,
198,
198,
464,
3290,
] # The dog was found in a field near the intersection of West and West Streets.\n\nThe dog
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
@slow
def test_lm_generate_distilgpt2(self):
......@@ -363,11 +385,5 @@ class TFGPT2ModelLanguageGenerationTest(unittest.TestCase):
2635,
] # The president of the United States, and the president of the United Kingdom, have been in the White
output_ids = model.generate(
input_ids,
do_sample=False,
bos_token_id=self.special_tokens["bos_token_id"],
eos_token_ids=self.special_tokens["eos_token_id"],
)
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_tf_openai_gpt.py
View file @ 31f2437f
......@@ -238,3 +238,35 @@ class TFOpenAIGPTModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in list(TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFOpenAIGPTModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
class TFOPENAIGPTModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_openai_gpt(self):
model = TFOpenAIGPTLMHeadModel.from_pretrained("openai-gpt")
input_ids = tf.convert_to_tensor([[481, 4735, 544]], dtype=tf.int32) # the president is
expected_output_ids = [
481,
4735,
544,
246,
963,
870,
762,
239,
244,
40477,
244,
249,
719,
881,
487,
544,
240,
244,
603,
481,
] # the president is a very good man. " \n " i\'m sure he is, " said the
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_tf_transfo_xl.py
View file @ 31f2437f
......@@ -212,3 +212,366 @@ class TFTransfoXLModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in list(TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFTransfoXLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
class TFTransfoXLModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_transfo_xl_wt103(self):
model = TFTransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
input_ids = tf.convert_to_tensor(
[
[
33,
1297,
2,
1,
1009,
4,
1109,
11739,
4762,
358,
5,
25,
245,
22,
1706,
17,
20098,
5,
3215,
21,
37,
1110,
3,
13,
1041,
4,
24,
603,
490,
2,
71477,
20098,
104447,
2,
20961,
1,
2604,
4,
1,
329,
3,
6224,
831,
16002,
2,
8,
603,
78967,
29546,
23,
803,
20,
25,
416,
5,
8,
232,
4,
277,
6,
1855,
4601,
3,
29546,
54,
8,
3609,
5,
57211,
49,
4,
1,
277,
18,
8,
1755,
15691,
3,
341,
25,
416,
693,
42573,
71,
17,
401,
94,
31,
17919,
2,
29546,
7873,
18,
1,
435,
23,
11011,
755,
5,
5167,
3,
7983,
98,
84,
2,
29546,
3267,
8,
3609,
4,
1,
4865,
1075,
2,
6087,
71,
6,
346,
8,
5854,
3,
29546,
824,
1400,
1868,
2,
19,
160,
2,
311,
8,
5496,
2,
20920,
17,
25,
15097,
3,
24,
24,
0,
]
],
dtype=tf.int31,
)
# In 1991 , the remains of Russian Tsar Nicholas II and his family
# ( except for Alexei and Maria ) are discovered .
# The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
# remainder of the story . 1883 Western Siberia ,
# a young Grigori Rasputin is asked by his father and a group of men to perform magic .
# Rasputin has a vision and denounces one of the men as a horse thief . Although his
# father initially slaps him for making such an accusation , Rasputin watches as the
# man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
# the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
# with people , even a bishop , begging for his blessing . <eod> </s> <eos>
expected_output_ids = [
33,
1297,
2,
1,
1009,
4,
1109,
11739,
4762,
358,
5,
25,
245,
22,
1706,
17,
20098,
5,
3215,
21,
37,
1110,
3,
13,
1041,
4,
24,
603,
490,
2,
71477,
20098,
104447,
2,
20961,
1,
2604,
4,
1,
329,
3,
6224,
831,
16002,
2,
8,
603,
78967,
29546,
23,
803,
20,
25,
416,
5,
8,
232,
4,
277,
6,
1855,
4601,
3,
29546,
54,
8,
3609,
5,
57211,
49,
4,
1,
277,
18,
8,
1755,
15691,
3,
341,
25,
416,
693,
42573,
71,
17,
401,
94,
31,
17919,
2,
29546,
7873,
18,
1,
435,
23,
11011,
755,
5,
5167,
3,
7983,
98,
84,
2,
29546,
3267,
8,
3609,
4,
1,
4865,
1075,
2,
6087,
71,
6,
346,
8,
5854,
3,
29546,
824,
1400,
1868,
2,
19,
160,
2,
311,
8,
5496,
2,
20920,
17,
25,
15097,
3,
24,
24,
0,
33,
1,
1857,
2,
1,
1009,
4,
1109,
11739,
4762,
358,
5,
25,
245,
28,
1110,
3,
13,
1041,
4,
24,
603,
490,
2,
71477,
20098,
104447,
2,
20961,
1,
2604,
4,
1,
329,
3,
0,
]
# In 1991, the remains of Russian Tsar Nicholas II and his family (
# except for Alexei and Maria ) are discovered. The voice of young son,
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
# 1883 Western Siberia, a young Grigori Rasputin is asked by his father
# and a group of men to perform magic. Rasputin has a vision and
# denounces one of the men as a horse thief. Although his father initially
# slaps him for making such an accusation, Rasputin watches as the man
# is chased outside and beaten. Twenty years later, Rasputin sees a vision
# of the Virgin Mary, prompting him to become a priest.
# Rasputin quickly becomes famous, with people, even a bishop, begging for
# his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
# Nicholas II and his family were discovered. The voice of <unk> young son,
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>
# TODO: add this test when trasnfo-xl-lmhead is implemented
with self.assertRaises(NotImplementedError):
model.generate(input_ids, max_length=200, do_sample=False)
print(expected_output_ids)
# self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids) TODO: (PVP) to add when transfo-xl is implemented
tests/test_modeling_tf_xlm.py
View file @ 31f2437f
......@@ -311,3 +311,35 @@ class TFXLMModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in list(TF_XLM_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFXLMModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
class TFXLMModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_xlm_mlm_en_2048(self):
model = TFXLMWithLMHeadModel.from_pretrained("xlm-mlm-en-2048")
input_ids = tf.convert_to_tensor([[14, 447]], dtype=tf.int32) # the president
expected_output_ids = [
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
] # the president the president the president the president the president the president the president the president the president the president
# TODO(PVP): this and other input_ids I tried for generation give pretty bad results. Not sure why. Model might just not be made for auto-regressive inference
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_tf_xlnet.py
View file @ 31f2437f
......@@ -413,3 +413,405 @@ class TFXLNetModelTest(TFModelTesterMixin, unittest.TestCase):
for model_name in list(TF_XLNET_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TFXLNetModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model)
class TFXLNetModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_xlnet_base_cased(self):
model = TFXLNetLMHeadModel.from_pretrained("xlnet-base-cased")
input_ids = tf.convert_to_tensor(
[
[
67,
2840,
19,
18,
1484,
20,
965,
29077,
8719,
1273,
21,
45,
273,
17,
10,
15048,
28,
27511,
21,
4185,
11,
41,
2444,
9,
32,
1025,
20,
8719,
26,
23,
673,
966,
19,
29077,
20643,
27511,
20822,
20643,
19,
17,
6616,
17511,
18,
8978,
20,
18,
777,
9,
19233,
1527,
17669,
19,
24,
673,
17,
28756,
150,
12943,
4354,
153,
27,
442,
37,
45,
668,
21,
24,
256,
20,
416,
22,
2771,
4901,
9,
12943,
4354,
153,
51,
24,
3004,
21,
28142,
23,
65,
20,
18,
416,
34,
24,
2958,
22947,
9,
1177,
45,
668,
3097,
13768,
23,
103,
28,
441,
148,
48,
20522,
19,
12943,
4354,
153,
12860,
34,
18,
326,
27,
17492,
684,
21,
6709,
9,
8585,
123,
266,
19,
12943,
4354,
153,
6872,
24,
3004,
20,
18,
9225,
2198,
19,
12717,
103,
22,
401,
24,
6348,
9,
12943,
4354,
153,
1068,
2768,
2286,
19,
33,
104,
19,
176,
24,
9313,
19,
20086,
28,
45,
10292,
9,
4,
3,
]
],
dtype=tf.int32,
)
# In 1991, the remains of Russian Tsar Nicholas II and his family
# (except for Alexei and Maria) are discovered.
# The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich, narrates the
# remainder of the story. 1883 Western Siberia,
# a young Grigori Rasputin is asked by his father and a group of men to perform magic.
# Rasputin has a vision and denounces one of the men as a horse thief. Although his
# father initially slaps him for making such an accusation, Rasputin watches as the
# man is chased outside and beaten. Twenty years later, Rasputin sees a vision of
# the Virgin Mary, prompting him to become a priest. Rasputin quickly becomes famous,
# with people, even a bishop, begging for his blessing. """
expected_output_ids = [
67,
2840,
19,
18,
1484,
20,
965,
29077,
8719,
1273,
21,
45,
273,
17,
10,
15048,
28,
27511,
21,
4185,
11,
41,
2444,
9,
32,
1025,
20,
8719,
26,
23,
673,
966,
19,
29077,
20643,
27511,
20822,
20643,
19,
17,
6616,
17511,
18,
8978,
20,
18,
777,
9,
19233,
1527,
17669,
19,
24,
673,
17,
28756,
150,
12943,
4354,
153,
27,
442,
37,
45,
668,
21,
24,
256,
20,
416,
22,
2771,
4901,
9,
12943,
4354,
153,
51,
24,
3004,
21,
28142,
23,
65,
20,
18,
416,
34,
24,
2958,
22947,
9,
1177,
45,
668,
3097,
13768,
23,
103,
28,
441,
148,
48,
20522,
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2768,
2286,
19,
33,
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19,
176,
24,
9313,
19,
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9,
4,
3,
19,
12943,
4354,
153,
27,
442,
22,
2771,
4901,
9,
69,
27,
50,
551,
22,
2771,
4901,
19,
21,
45,
668,
21,
18,
416,
41,
1499,
22,
755,
18,
14285,
9,
12943,
4354,
153,
27,
1499,
22,
642,
22,
]
# In 1991, the remains of Russian Tsar Nicholas II and his family (except for Alexei and Maria)
# are discovered. The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich,
# narrates the remainder of the story. 1883 Western Siberia, a young Grigori Rasputin
# is asked by his father and a group of men to perform magic. Rasputin has a vision and
# denounces one of the men as a horse thief. Although his father initially slaps
# him for making such an accusation, Rasputin watches as the man is chased outside and beaten.
# Twenty years later, Rasputin sees a vision of the Virgin Mary, prompting him to become a priest.
# Rasputin quickly becomes famous, with people, even a bishop, begging for his blessing.
# <sep><cls>, Rasputin is asked to perform magic.
# He is not able to perform magic, and his father and
# the men are forced to leave the monastery. Rasputin is forced to return to
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_transfo_xl.py
View file @ 31f2437f
......@@ -218,7 +218,7 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_transfo_xl_wt103(self):
model = TransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
input_ids = torch.Tensor(
input_ids = torch.tensor(
[
[
33,
......@@ -363,8 +363,10 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
24,
0,
]
]
).long()
],
dtype=torch.long,
device=torch_device,
)
# In 1991 , the remains of Russian Tsar Nicholas II and his family
# ( except for Alexei and Maria ) are discovered .
# The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
......@@ -374,6 +376,7 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
# father initially slaps him for making such an accusation , Rasputin watches as the
# man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
# the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
# with people , even a bishop , begging for his blessing . <eod> </s> <eos>
expected_output_ids = [
......@@ -518,20 +521,10 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
24,
24,
0,
29546,
40,
1092,
18,
8,
5854,
7,
1143,
2,
7,
33,
1,
159,
99,
16,
1857,
2,
1,
1009,
4,
......@@ -545,14 +538,23 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
28,
1110,
3,
57,
629,
38,
3493,
47,
1094,
7,
1297,
13,
1041,
4,
24,
603,
490,
2,
71477,
20098,
104447,
2,
20961,
1,
2604,
4,
1,
329,
3,
0,
]
......@@ -566,10 +568,9 @@ class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
# is chased outside and beaten. Twenty years later, Rasputin sees a vision
# of the Virgin Mary, prompting him to become a priest.
# Rasputin quickly becomes famous, with people, even a bishop, begging for
# his blessing. Rasputin first appears as a priest in 1996, in the same year
# that the remains of Russian Tsar Nicholas II and his family were discovered. H
torch.manual_seed(0)
# his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
# Nicholas II and his family were discovered. The voice of <unk> young son,
# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>
output_ids = model.generate(input_ids, max_length=200)
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_xlm.py
View file @ 31f2437f
......@@ -403,31 +403,29 @@ class XLMModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_xlm_mlm_en_2048(self):
model = XLMWithLMHeadModel.from_pretrained("xlm-mlm-en-2048")
input_ids = torch.Tensor([[1, 14, 2232, 26, 1]]).long() # The dog is cute
input_ids = torch.tensor([[14, 447]], dtype=torch.long, device=torch_device) # the president
expected_output_ids = [
1,
14,
2232,
26,
1,
567,
26,
32,
149,
149,
149,
149,
149,
149,
149,
149,
149,
149,
149,
149,
] # The dog is nothing is it!!!!!!!!!!!! TODO (PVP): this sentence (and others I tried) does not make much sense, there seems to be a problem with xlm language generation.
torch.manual_seed(0)
output_ids = model.generate(input_ids)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
14,
447,
] # the president the president the president the president the president the president the president the president the president the president
# TODO(PVP): this and other input_ids I tried for generation give pretty bad results. Not sure why. Model might just not be made for auto-regressive inference
output_ids = model.generate(input_ids, do_sample=False)
self.assertListEqual(output_ids[0].numpy().tolist(), expected_output_ids)
tests/test_modeling_xlnet.py
View file @ 31f2437f
......@@ -119,11 +119,11 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
input_ids_q = ids_tensor([self.batch_size, self.seq_length + 1], self.vocab_size)
perm_mask = torch.zeros(
self.batch_size, self.seq_length + 1, self.seq_length + 1, dtype=torch.float, device=torch_device
self.batch_size, self.seq_length + 1, self.seq_length + 1, dtype=torch.float, device=torch_device,
)
perm_mask[:, :, -1] = 1.0 # Previous tokens don't see last token
target_mapping = torch.zeros(
self.batch_size, 1, self.seq_length + 1, dtype=torch.float, device=torch_device
self.batch_size, 1, self.seq_length + 1, dtype=torch.float, device=torch_device,
)
target_mapping[:, 0, -1] = 1.0 # predict last token
......@@ -212,7 +212,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertEqual(len(no_mems_outputs), 1)
self.parent.assertListEqual(
list(result["outputs"].size()), [self.batch_size, self.seq_length, self.hidden_size]
list(result["outputs"].size()), [self.batch_size, self.seq_length, self.hidden_size],
)
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_1"]),
......@@ -283,7 +283,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss_1"].size()), [])
self.parent.assertListEqual(
list(result["all_logits_1"].size()), [self.batch_size, self.seq_length, self.vocab_size]
list(result["all_logits_1"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_1"]),
......@@ -292,7 +292,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss_2"].size()), [])
self.parent.assertListEqual(
list(result["all_logits_2"].size()), [self.batch_size, self.seq_length, self.vocab_size]
list(result["all_logits_2"].size()), [self.batch_size, self.seq_length, self.vocab_size],
)
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_2"]),
......@@ -319,7 +319,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
model.eval()
outputs = model(input_ids_1)
start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits, mems = outputs
(start_top_log_probs, start_top_index, end_top_log_probs, end_top_index, cls_logits, mems,) = outputs
outputs = model(
input_ids_1,
......@@ -340,7 +340,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
total_loss, mems = outputs
outputs = model(input_ids_1, start_positions=sequence_labels, end_positions=sequence_labels)
outputs = model(input_ids_1, start_positions=sequence_labels, end_positions=sequence_labels,)
total_loss, mems = outputs
......@@ -356,10 +356,10 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["start_top_log_probs"].size()), [self.batch_size, model.config.start_n_top]
list(result["start_top_log_probs"].size()), [self.batch_size, model.config.start_n_top],
)
self.parent.assertListEqual(
list(result["start_top_index"].size()), [self.batch_size, model.config.start_n_top]
list(result["start_top_index"].size()), [self.batch_size, model.config.start_n_top],
)
self.parent.assertListEqual(
list(result["end_top_log_probs"].size()),
......@@ -405,7 +405,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["logits"].size()), [self.batch_size, self.seq_length, self.type_sequence_label_size]
list(result["logits"].size()), [self.batch_size, self.seq_length, self.type_sequence_label_size],
)
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_1"]),
......@@ -442,7 +442,7 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual(
list(result["logits"].size()), [self.batch_size, self.type_sequence_label_size]
list(result["logits"].size()), [self.batch_size, self.type_sequence_label_size],
)
self.parent.assertListEqual(
list(list(mem.size()) for mem in result["mems_1"]),
......@@ -517,7 +517,7 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
@slow
def test_lm_generate_xlnet_base_cased(self):
model = XLNetLMHeadModel.from_pretrained("xlnet-base-cased")
input_ids = torch.Tensor(
input_ids = torch.tensor(
[
[
67,
......@@ -682,8 +682,10 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
4,
3,
]
]
).long()
],
dtype=torch.long,
device=torch_device,
)
# In 1991, the remains of Russian Tsar Nicholas II and his family
# (except for Alexei and Maria) are discovered.
# The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich, narrates the
......@@ -857,45 +859,45 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
9,
4,
3,
1722,
19,
24,
6348,
61,
977,
176,
1772,
33,
45,
970,
19,
4185,
19,
12943,
4354,
153,
27,
442,
22,
2771,
4901,
25,
18,
2059,
20,
24,
303,
1775,
691,
9,
1147,
19,
634,
69,
27,
50,
551,
22,
2771,
4901,
19,
43,
51,
54,
6157,
2999,
33,
4185,
21,
45,
668,
21,
18,
416,
41,
1499,
22,
755,
18,
14285,
9,
12943,
4354,
153,
27,
1499,
22,
642,
22,
]
# In 1991, the remains of Russian Tsar Nicholas II and his family (except for Alexei and Maria)
# are discovered. The voice of Nicholas's young son, Tsarevich Alexei Nikolaevich,
......@@ -905,11 +907,9 @@ class XLNetModelLanguageGenerationTest(unittest.TestCase):
# him for making such an accusation, Rasputin watches as the man is chased outside and beaten.
# Twenty years later, Rasputin sees a vision of the Virgin Mary, prompting him to become a priest.
# Rasputin quickly becomes famous, with people, even a bishop, begging for his blessing.
# 1990, a priest who cannot even walk with his wife, Maria, is asked to perform magic
# in the presence of a local religious leader.
# Since, however, he has had difficulty walking with Maria
torch.manual_seed(0)
output_ids = model.generate(input_ids, max_length=200)
# <sep><cls>, Rasputin is asked to perform magic.
# He is not able to perform magic, and his father and
# the men are forced to leave the monastery. Rasputin is forced to return to
output_ids = model.generate(input_ids, max_length=200, do_sample=False)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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