mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-04 05:10:06 +06:00
c89bdfbe72
* Put models in subfolders * Styling * Fix imports in tests * More fixes in test imports * Sneaky hidden imports * Fix imports in doc files * More sneaky imports * Finish fixing tests * Fix examples * Fix path for copies * More fixes for examples * Fix dummy files * More fixes for example * More model import fixes * Is this why you're unhappy GitHub? * Fix imports in conver command
329 lines
11 KiB
Python
329 lines
11 KiB
Python
# coding=utf-8
|
|
# Copyright 2020 HuggingFace Inc. team.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
|
|
import unittest
|
|
|
|
from transformers import AutoConfig, AutoTokenizer, MarianConfig, MarianTokenizer, is_torch_available
|
|
from transformers.file_utils import cached_property
|
|
from transformers.hf_api import HfApi
|
|
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
|
|
|
|
from .test_modeling_common import ModelTesterMixin
|
|
|
|
|
|
if is_torch_available():
|
|
import torch
|
|
|
|
from transformers import AutoModelWithLMHead, MarianMTModel
|
|
from transformers.models.bart.modeling_bart import shift_tokens_right
|
|
from transformers.models.marian.convert_marian_to_pytorch import (
|
|
ORG_NAME,
|
|
convert_hf_name_to_opus_name,
|
|
convert_opus_name_to_hf_name,
|
|
)
|
|
from transformers.pipelines import TranslationPipeline
|
|
|
|
|
|
class ModelTester:
|
|
def __init__(self, parent):
|
|
self.config = MarianConfig(
|
|
vocab_size=99,
|
|
d_model=24,
|
|
encoder_layers=2,
|
|
decoder_layers=2,
|
|
encoder_attention_heads=2,
|
|
decoder_attention_heads=2,
|
|
encoder_ffn_dim=32,
|
|
decoder_ffn_dim=32,
|
|
max_position_embeddings=48,
|
|
add_final_layer_norm=True,
|
|
)
|
|
|
|
def prepare_config_and_inputs_for_common(self):
|
|
return self.config, {}
|
|
|
|
|
|
@require_torch
|
|
class SelectiveCommonTest(unittest.TestCase):
|
|
all_model_classes = (MarianMTModel,) if is_torch_available() else ()
|
|
|
|
test_save_load_keys_to_never_save = ModelTesterMixin.test_save_load_keys_to_never_save
|
|
|
|
def setUp(self):
|
|
self.model_tester = ModelTester(self)
|
|
|
|
|
|
class ModelManagementTests(unittest.TestCase):
|
|
@slow
|
|
@require_torch
|
|
def test_model_names(self):
|
|
model_list = HfApi().model_list()
|
|
model_ids = [x.modelId for x in model_list if x.modelId.startswith(ORG_NAME)]
|
|
bad_model_ids = [mid for mid in model_ids if "+" in model_ids]
|
|
self.assertListEqual([], bad_model_ids)
|
|
self.assertGreater(len(model_ids), 500)
|
|
|
|
|
|
@require_torch
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class MarianIntegrationTest(unittest.TestCase):
|
|
src = "en"
|
|
tgt = "de"
|
|
src_text = [
|
|
"I am a small frog.",
|
|
"Now I can forget the 100 words of german that I know.",
|
|
"Tom asked his teacher for advice.",
|
|
"That's how I would do it.",
|
|
"Tom really admired Mary's courage.",
|
|
"Turn around and close your eyes.",
|
|
]
|
|
expected_text = [
|
|
"Ich bin ein kleiner Frosch.",
|
|
"Jetzt kann ich die 100 Wörter des Deutschen vergessen, die ich kenne.",
|
|
"Tom bat seinen Lehrer um Rat.",
|
|
"So würde ich das machen.",
|
|
"Tom bewunderte Marias Mut wirklich.",
|
|
"Drehen Sie sich um und schließen Sie die Augen.",
|
|
]
|
|
# ^^ actual C++ output differs slightly: (1) des Deutschen removed, (2) ""-> "O", (3) tun -> machen
|
|
|
|
@classmethod
|
|
def setUpClass(cls) -> None:
|
|
cls.model_name = f"Helsinki-NLP/opus-mt-{cls.src}-{cls.tgt}"
|
|
return cls
|
|
|
|
@cached_property
|
|
def tokenizer(self) -> MarianTokenizer:
|
|
return AutoTokenizer.from_pretrained(self.model_name)
|
|
|
|
@property
|
|
def eos_token_id(self) -> int:
|
|
return self.tokenizer.eos_token_id
|
|
|
|
@cached_property
|
|
def model(self):
|
|
model: MarianMTModel = AutoModelWithLMHead.from_pretrained(self.model_name).to(torch_device)
|
|
c = model.config
|
|
self.assertListEqual(c.bad_words_ids, [[c.pad_token_id]])
|
|
self.assertEqual(c.max_length, 512)
|
|
self.assertEqual(c.decoder_start_token_id, c.pad_token_id)
|
|
|
|
if torch_device == "cuda":
|
|
return model.half()
|
|
else:
|
|
return model
|
|
|
|
def _assert_generated_batch_equal_expected(self, **tokenizer_kwargs):
|
|
generated_words = self.translate_src_text(**tokenizer_kwargs)
|
|
self.assertListEqual(self.expected_text, generated_words)
|
|
|
|
def translate_src_text(self, **tokenizer_kwargs):
|
|
model_inputs = self.tokenizer.prepare_seq2seq_batch(src_texts=self.src_text, **tokenizer_kwargs).to(
|
|
torch_device
|
|
)
|
|
self.assertEqual(self.model.device, model_inputs.input_ids.device)
|
|
generated_ids = self.model.generate(
|
|
model_inputs.input_ids, attention_mask=model_inputs.attention_mask, num_beams=2, max_length=128
|
|
)
|
|
generated_words = self.tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
|
|
return generated_words
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_EN_DE_More(MarianIntegrationTest):
|
|
@slow
|
|
def test_forward(self):
|
|
src, tgt = ["I am a small frog"], ["Ich bin ein kleiner Frosch."]
|
|
expected_ids = [38, 121, 14, 697, 38848, 0]
|
|
|
|
model_inputs: dict = self.tokenizer.prepare_seq2seq_batch(src, tgt_texts=tgt).to(torch_device)
|
|
|
|
self.assertListEqual(expected_ids, model_inputs.input_ids[0].tolist())
|
|
|
|
desired_keys = {
|
|
"input_ids",
|
|
"attention_mask",
|
|
"labels",
|
|
}
|
|
self.assertSetEqual(desired_keys, set(model_inputs.keys()))
|
|
model_inputs["decoder_input_ids"] = shift_tokens_right(model_inputs.labels, self.tokenizer.pad_token_id)
|
|
model_inputs["return_dict"] = True
|
|
model_inputs["use_cache"] = False
|
|
with torch.no_grad():
|
|
outputs = self.model(**model_inputs)
|
|
max_indices = outputs.logits.argmax(-1)
|
|
self.tokenizer.batch_decode(max_indices)
|
|
|
|
def test_unk_support(self):
|
|
t = self.tokenizer
|
|
ids = t.prepare_seq2seq_batch(["||"]).to(torch_device).input_ids[0].tolist()
|
|
expected = [t.unk_token_id, t.unk_token_id, t.eos_token_id]
|
|
self.assertEqual(expected, ids)
|
|
|
|
def test_pad_not_split(self):
|
|
input_ids_w_pad = self.tokenizer.prepare_seq2seq_batch(["I am a small frog <pad>"]).input_ids[0].tolist()
|
|
expected_w_pad = [38, 121, 14, 697, 38848, self.tokenizer.pad_token_id, 0] # pad
|
|
self.assertListEqual(expected_w_pad, input_ids_w_pad)
|
|
|
|
@slow
|
|
def test_batch_generation_en_de(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
def test_auto_config(self):
|
|
config = AutoConfig.from_pretrained(self.model_name)
|
|
self.assertIsInstance(config, MarianConfig)
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_EN_FR(MarianIntegrationTest):
|
|
src = "en"
|
|
tgt = "fr"
|
|
src_text = [
|
|
"I am a small frog.",
|
|
"Now I can forget the 100 words of german that I know.",
|
|
]
|
|
expected_text = [
|
|
"Je suis une petite grenouille.",
|
|
"Maintenant, je peux oublier les 100 mots d'allemand que je connais.",
|
|
]
|
|
|
|
@slow
|
|
def test_batch_generation_en_fr(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_FR_EN(MarianIntegrationTest):
|
|
src = "fr"
|
|
tgt = "en"
|
|
src_text = [
|
|
"Donnez moi le micro.",
|
|
"Tom et Mary étaient assis à une table.", # Accents
|
|
]
|
|
expected_text = [
|
|
"Give me the microphone.",
|
|
"Tom and Mary were sitting at a table.",
|
|
]
|
|
|
|
@slow
|
|
def test_batch_generation_fr_en(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_RU_FR(MarianIntegrationTest):
|
|
src = "ru"
|
|
tgt = "fr"
|
|
src_text = ["Он показал мне рукопись своей новой пьесы."]
|
|
expected_text = ["Il m'a montré le manuscrit de sa nouvelle pièce."]
|
|
|
|
@slow
|
|
def test_batch_generation_ru_fr(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_MT_EN(MarianIntegrationTest):
|
|
"""Cover low resource/high perplexity setting. This breaks without adjust_logits_generation overwritten"""
|
|
|
|
src = "mt"
|
|
tgt = "en"
|
|
src_text = ["Billi messu b'mod ġentili, Ġesù fejjaq raġel li kien milqut bil - marda kerha tal - ġdiem."]
|
|
expected_text = ["Touching gently, Jesus healed a man who was affected by the sad disease of leprosy."]
|
|
|
|
@slow
|
|
def test_batch_generation_mt_en(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_en_zh(MarianIntegrationTest):
|
|
src = "en"
|
|
tgt = "zh"
|
|
src_text = ["My name is Wolfgang and I live in Berlin"]
|
|
expected_text = ["我叫沃尔夫冈 我住在柏林"]
|
|
|
|
@slow
|
|
def test_batch_generation_eng_zho(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
|
|
@require_sentencepiece
|
|
@require_tokenizers
|
|
class TestMarian_en_ROMANCE(MarianIntegrationTest):
|
|
"""Multilingual on target side."""
|
|
|
|
src = "en"
|
|
tgt = "ROMANCE"
|
|
src_text = [
|
|
">>fr<< Don't spend so much time watching TV.",
|
|
">>pt<< Your message has been sent.",
|
|
">>es<< He's two years older than me.",
|
|
]
|
|
expected_text = [
|
|
"Ne passez pas autant de temps à regarder la télé.",
|
|
"A sua mensagem foi enviada.",
|
|
"Es dos años más viejo que yo.",
|
|
]
|
|
|
|
@slow
|
|
def test_batch_generation_en_ROMANCE_multi(self):
|
|
self._assert_generated_batch_equal_expected()
|
|
|
|
def test_tokenizer_handles_empty(self):
|
|
normalized = self.tokenizer.normalize("")
|
|
self.assertIsInstance(normalized, str)
|
|
with self.assertRaises(ValueError):
|
|
self.tokenizer.prepare_seq2seq_batch([""])
|
|
|
|
@slow
|
|
def test_pipeline(self):
|
|
device = 0 if torch_device == "cuda" else -1
|
|
pipeline = TranslationPipeline(self.model, self.tokenizer, framework="pt", device=device)
|
|
output = pipeline(self.src_text)
|
|
self.assertEqual(self.expected_text, [x["translation_text"] for x in output])
|
|
|
|
|
|
@require_torch
|
|
class TestConversionUtils(unittest.TestCase):
|
|
def test_renaming_multilingual(self):
|
|
old_names = [
|
|
"opus-mt-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh-fi",
|
|
"opus-mt-cmn+cn-fi", # no group
|
|
"opus-mt-en-de", # standard name
|
|
"opus-mt-en-de", # standard name
|
|
]
|
|
expected = ["opus-mt-ZH-fi", "opus-mt-cmn_cn-fi", "opus-mt-en-de", "opus-mt-en-de"]
|
|
self.assertListEqual(expected, [convert_opus_name_to_hf_name(x) for x in old_names])
|
|
|
|
def test_undoing_renaming(self):
|
|
hf_names = ["opus-mt-ZH-fi", "opus-mt-cmn_cn-fi", "opus-mt-en-de", "opus-mt-en-de"]
|
|
converted_opus_names = [convert_hf_name_to_opus_name(x) for x in hf_names]
|
|
expected_opus_names = [
|
|
"cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh-fi",
|
|
"cmn+cn-fi",
|
|
"en-de", # standard name
|
|
"en-de",
|
|
]
|
|
self.assertListEqual(expected_opus_names, converted_opus_names)
|