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Unverified Commit 17c45c39 authored by Patrick von Platen's avatar Patrick von Platen Committed by GitHub
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Add slow generate tests for pretrained lm models (#2909) 

* add slow generate lm_model tests

* fix conflicts

* merge conflicts

* fix conflicts

* add slow generate lm_model tests

* make style

* delete unused variable

* fix conflicts

* fix conflicts

* fix conflicts

* delete unused variable

* fix conflicts

* finished hard coded tests
parent 8194df8e
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Showing with 991 additions and 6 deletions
src/transformers/modeling_xlm.py
View file @ 17c45c39
...@@ -512,7 +512,7 @@ class XLMModel(XLMPreTrainedModel): ...@@ -512,7 +512,7 @@ class XLMModel(XLMPreTrainedModel):
inputs_embeds = self.embeddings(input_ids) inputs_embeds = self.embeddings(input_ids)
tensor = inputs_embeds + self.position_embeddings(position_ids).expand_as(inputs_embeds) tensor = inputs_embeds + self.position_embeddings(position_ids).expand_as(inputs_embeds)
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) tensor = tensor + self.lang_embeddings(langs)
if token_type_ids is not None: if token_type_ids is not None:
tensor = tensor + self.embeddings(token_type_ids) tensor = tensor + self.embeddings(token_type_ids)
......
tests/test_modeling_common.py
View file @ 17c45c39
...@@ -641,7 +641,7 @@ global_rng = random.Random() ...@@ -641,7 +641,7 @@ global_rng = random.Random()
def ids_tensor(shape, vocab_size, rng=None, name=None): def ids_tensor(shape, vocab_size, rng=None, name=None):
"""Creates a random int32 tensor of the shape within the vocab size.""" # Creates a random int32 tensor of the shape within the vocab size
if rng is None: if rng is None:
rng = global_rng rng = global_rng
......
tests/test_modeling_ctrl.py
View file @ 17c45c39
...@@ -23,6 +23,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device ...@@ -23,6 +23,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device
if is_torch_available(): if is_torch_available():
import torch
from transformers import CTRLConfig, CTRLModel, CTRL_PRETRAINED_MODEL_ARCHIVE_MAP, CTRLLMHeadModel from transformers import CTRLConfig, CTRLModel, CTRL_PRETRAINED_MODEL_ARCHIVE_MAP, CTRLLMHeadModel
...@@ -212,3 +213,36 @@ class CTRLModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -212,3 +213,36 @@ class CTRLModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(CTRL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(CTRL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = CTRLModel.from_pretrained(model_name, cache_dir=CACHE_DIR) model = CTRLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
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
expected_output_ids = [
11859,
586,
20984,
8,
13391,
3,
980,
8258,
72,
327,
148,
2,
53,
29,
226,
3,
780,
49,
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)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_gpt2.py
View file @ 17c45c39
...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device ...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device
if is_torch_available(): if is_torch_available():
import torch
from transformers import ( from transformers import (
GPT2Config, GPT2Config,
GPT2Model, GPT2Model,
...@@ -165,7 +166,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -165,7 +166,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
"presents": presents, "presents": presents,
} }
self.parent.assertListEqual( 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],
) )
self.parent.assertEqual(len(result["presents"]), config.n_layer) self.parent.assertEqual(len(result["presents"]), config.n_layer)
...@@ -180,7 +181,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -180,7 +181,7 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), []) self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual( 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( def create_and_check_double_lm_head_model(
...@@ -208,7 +209,8 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -208,7 +209,8 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
self.parent.assertListEqual(list(result["loss"].size()), []) self.parent.assertListEqual(list(result["loss"].size()), [])
self.parent.assertListEqual( self.parent.assertListEqual(
list(result["lm_logits"].size()), [self.batch_size, self.num_choices, self.seq_length, self.vocab_size] list(result["lm_logits"].size()),
[self.batch_size, self.num_choices, self.seq_length, self.vocab_size],
) )
self.parent.assertListEqual(list(result["mc_logits"].size()), [self.batch_size, self.num_choices]) self.parent.assertListEqual(list(result["mc_logits"].size()), [self.batch_size, self.num_choices])
...@@ -227,7 +229,11 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -227,7 +229,11 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
choice_labels, choice_labels,
) = config_and_inputs ) = 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 return config, inputs_dict
...@@ -255,3 +261,84 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -255,3 +261,84 @@ class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(GPT2_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(GPT2_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = GPT2Model.from_pretrained(model_name, cache_dir=CACHE_DIR) model = GPT2Model.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
def prepare_generation_special_tokens():
return {"bos_token_id": 50256, "eos_token_id": 50256}
class GPT2ModelLanguageGenerationTest(unittest.TestCase):
special_tokens = prepare_generation_special_tokens()
@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
expected_output_ids = [
464,
3290,
318,
13779,
1165,
13,
632,
7832,
284,
6437,
319,
502,
290,
318,
922,
329,
502,
357,
1169,
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,
bos_token_id=self.special_tokens["bos_token_id"],
eos_token_ids=self.special_tokens["eos_token_id"],
)
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, 3290, 318, 13779]]).long() # The dog is cute
expected_output_ids = [
464,
3290,
318,
13779,
996,
339,
460,
3360,
655,
2513,
287,
262,
3952,
13,
632,
318,
407,
845,
3621,
284,
] # The dog is cute though he can sometimes just walk in the park. It is not very nice to
torch.manual_seed(0)
output_ids = model.generate(
input_ids,
bos_token_id=self.special_tokens["bos_token_id"],
eos_token_ids=self.special_tokens["eos_token_id"],
)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_openai.py
View file @ 17c45c39
...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device ...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device
if is_torch_available(): if is_torch_available():
import torch
from transformers import ( from transformers import (
OpenAIGPTConfig, OpenAIGPTConfig,
OpenAIGPTModel, OpenAIGPTModel,
...@@ -208,3 +209,36 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -208,3 +209,36 @@ class OpenAIGPTModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = OpenAIGPTModel.from_pretrained(model_name, cache_dir=CACHE_DIR) model = OpenAIGPTModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
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
expected_output_ids = [
481,
2585,
544,
4957,
669,
512,
761,
5990,
271,
645,
487,
535,
976,
2479,
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)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_transfo_xl.py
View file @ 17c45c39
...@@ -212,3 +212,372 @@ class TransfoXLModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -212,3 +212,372 @@ class TransfoXLModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = TransfoXLModel.from_pretrained(model_name, cache_dir=CACHE_DIR) model = TransfoXLModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
def prepare_generation_special_tokens():
return {"eos_token_id": 0}
class TransfoXLModelLanguageGenerationTest(unittest.TestCase):
special_tokens = prepare_generation_special_tokens()
@slow
def test_lm_generate_transfo_xl_wt103(self):
model = TransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103")
input_ids = torch.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,
]
]
).long()
# 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,
29546,
40,
1092,
18,
8,
5854,
7,
1143,
2,
7,
1,
159,
99,
16,
1,
1009,
4,
1109,
11739,
4762,
358,
5,
25,
245,
28,
1110,
3,
57,
629,
38,
3493,
47,
1094,
7,
1297,
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. 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)
output_ids = model.generate(input_ids, eos_token_ids=self.special_tokens["eos_token_id"], max_length=200)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_xlm.py
View file @ 17c45c39
...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device ...@@ -24,6 +24,7 @@ from .utils import CACHE_DIR, require_torch, slow, torch_device
if is_torch_available(): if is_torch_available():
import torch
from transformers import ( from transformers import (
XLMConfig, XLMConfig,
XLMModel, XLMModel,
...@@ -396,3 +397,48 @@ class XLMModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -396,3 +397,48 @@ class XLMModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(XLM_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(XLM_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = XLMModel.from_pretrained(model_name, cache_dir=CACHE_DIR) model = XLMModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
def prepare_generation_special_tokens():
return {"bos_token_id": 0, "pad_token_id": 2}
class XLMModelLanguageGenerationTest(unittest.TestCase):
special_tokens = prepare_generation_special_tokens()
@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
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,
bos_token_id=self.special_tokens["bos_token_id"],
pad_token_id=self.special_tokens["pad_token_id"],
)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
tests/test_modeling_xlnet.py
View file @ 17c45c39
...@@ -511,3 +511,418 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase): ...@@ -511,3 +511,418 @@ class XLNetModelTest(ModelTesterMixin, unittest.TestCase):
for model_name in list(XLNET_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]: for model_name in list(XLNET_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = XLNetModel.from_pretrained(model_name, cache_dir=CACHE_DIR) model = XLNetModel.from_pretrained(model_name, cache_dir=CACHE_DIR)
self.assertIsNotNone(model) self.assertIsNotNone(model)
def prepare_generation_special_tokens():
return {"bos_token_id": 1, "pad_token_id": 5, "eos_token_id": 2}
class XLNetModelLanguageGenerationTest(unittest.TestCase):
special_tokens = prepare_generation_special_tokens()
@slow
def test_lm_generate_xlnet_base_cased(self):
model = XLNetLMHeadModel.from_pretrained("xlnet-base-cased")
input_ids = torch.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,
]
]
).long()
# 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,
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# 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.
# 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,
bos_token_id=self.special_tokens["bos_token_id"],
pad_token_id=self.special_tokens["pad_token_id"],
eos_token_ids=self.special_tokens["eos_token_id"],
max_length=200,
)
self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
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