Merge pull request #213 from huggingface/python-tests

Add Python tests
This commit is contained in:
Anthony MOI
2020-04-02 14:09:22 -04:00
committed by GitHub
21 changed files with 781 additions and 13 deletions

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@ -59,16 +59,24 @@ jobs:
path: ./bindings/python/target
key: ${{ runner.os }}-cargo-python-build-${{ hashFiles('**/Cargo.toml') }}
- name: Build
uses: actions-rs/cargo@v1
with:
toolchain: nightly
command: build
args: --verbose --manifest-path ./bindings/python/Cargo.toml
- name: Lint with RustFmt
uses: actions-rs/cargo@v1
with:
toolchain: nightly
command: fmt
args: --manifest-path ./bindings/python/Cargo.toml -- --check
- name: Install Python
uses: actions/setup-python@v1
with:
python-version: 3.6
architecture: "x64"
- name: Run tests
working-directory: ./bindings/python
run: |
python -m venv .env
source .env/bin/activate
pip install pytest requests maturin
maturin develop --release
make test

1
.gitignore vendored
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@ -8,6 +8,7 @@ Cargo.lock
/data
tokenizers/data
bindings/python/tests/data
/docs
__pycache__

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@ -1,9 +1,13 @@
.PHONY: style check-style
.PHONY: style check-style test
# Format source code automatically
style:
black --line-length 100 --target-version py35 examples tokenizers
black --line-length 100 --target-version py35 examples tokenizers tests
# Check the source code is formatted correctly
check-style:
black --check --line-length 100 --target-version py35 examples tokenizers
black --check --line-length 100 --target-version py35 examples tokenizers tests
# Launch the test suite
test:
python -m pytest -s -v tests

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@ -1,6 +1,9 @@
from setuptools import setup
from setuptools_rust import Binding, RustExtension
extras = {}
extras["testing"] = ["pytest"]
setup(
name="tokenizers",
version="0.7.0-rc3",
@ -13,6 +16,7 @@ setup(
url="https://github.com/huggingface/tokenizers",
license="Apache License 2.0",
rust_extensions=[RustExtension("tokenizers.tokenizers", binding=Binding.PyO3)],
extras_require=extras,
classifiers=[
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",

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@ -107,7 +107,7 @@ impl BPEDecoder {
#[new]
#[args(kwargs = "**")]
fn new(obj: &PyRawObject, kwargs: Option<&PyDict>) -> PyResult<()> {
let mut suffix = String::from("</w");
let mut suffix = String::from("</w>");
if let Some(kwargs) = kwargs {
for (key, value) in kwargs {

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@ -288,4 +288,11 @@ impl WordLevel {
}),
}
}
#[staticmethod]
fn empty() -> Model {
Model {
model: Container::Owned(Box::new(tk::models::wordlevel::WordLevel::default())),
}
}
}

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@ -46,6 +46,26 @@ impl AddedToken {
obj.init({ AddedToken { token } });
Ok(())
}
#[getter]
fn get_content(&self) -> &str {
&self.token.content
}
#[getter]
fn get_rstrip(&self) -> bool {
self.token.rstrip
}
#[getter]
fn get_lstrip(&self) -> bool {
self.token.lstrip
}
#[getter]
fn get_single_word(&self) -> bool {
self.token.single_word
}
}
#[pyproto]
impl PyObjectProtocol for AddedToken {
@ -54,9 +74,17 @@ impl PyObjectProtocol for AddedToken {
}
fn __repr__(&self) -> PyResult<String> {
let bool_to_python = |p| match p {
true => "True",
false => "False",
};
Ok(format!(
"AddedToken(\"{}\", rstrip={}, lstrip={}, single_word={})",
self.token.content, self.token.rstrip, self.token.lstrip, self.token.single_word
self.token.content,
bool_to_python(self.token.rstrip),
bool_to_python(self.token.lstrip),
bool_to_python(self.token.single_word)
))
}
}

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@ -0,0 +1,61 @@
import pytest
from tokenizers.decoders import Decoder, ByteLevel, WordPiece, Metaspace, BPEDecoder
class TestByteLevel:
def test_instantiate(self):
assert ByteLevel() is not None
assert isinstance(ByteLevel(), Decoder)
def test_decoding(self):
decoder = ByteLevel()
assert decoder.decode(["My", "Ġname", "Ġis", "ĠJohn"]) == "My name is John"
class TestWordPiece:
def test_instantiate(self):
assert WordPiece() is not None
assert WordPiece(prefix="__") is not None
assert WordPiece(cleanup=True) is not None
assert isinstance(WordPiece(), Decoder)
def test_decoding(self):
decoder = WordPiece()
assert decoder.decode(["My", "na", "##me", "is", "Jo", "##hn"]) == "My name is John"
assert decoder.decode(["I", "'m", "Jo", "##hn"]) == "I'm John"
decoder = WordPiece(prefix="__", cleanup=False)
assert decoder.decode(["My", "na", "__me", "is", "Jo", "__hn"]) == "My name is John"
assert decoder.decode(["I", "'m", "Jo", "__hn"]) == "I 'm John"
class TestMetaspace:
def test_instantiate(self):
assert Metaspace() is not None
assert Metaspace(replacement="-") is not None
with pytest.raises(Exception, match="replacement must be a character"):
Metaspace(replacement="")
assert Metaspace(add_prefix_space=True) is not None
assert isinstance(Metaspace(), Decoder)
def test_decoding(self):
decoder = Metaspace()
assert decoder.decode(["▁My", "▁name", "▁is", "▁John"]) == "My name is John"
decoder = Metaspace(replacement="-", add_prefix_space=False)
assert decoder.decode(["-My", "-name", "-is", "-John"]) == " My name is John"
class TestBPEDecoder:
def test_instantiate(self):
assert BPEDecoder() is not None
assert BPEDecoder(suffix="_") is not None
assert isinstance(BPEDecoder(), Decoder)
def test_decoding(self):
decoder = BPEDecoder()
assert (
decoder.decode(["My</w>", "na", "me</w>", "is</w>", "Jo", "hn</w>"])
== "My name is John"
)
decoder = BPEDecoder(suffix="_")
assert decoder.decode(["My_", "na", "me_", "is_", "Jo", "hn_"]) == "My name is John"

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@ -0,0 +1,23 @@
from ..utils import data_dir, roberta_files, bert_files
from tokenizers.models import Model, BPE, WordPiece, WordLevel
class TestBPE:
def test_instantiate(self, roberta_files):
assert isinstance(BPE.empty(), Model)
assert isinstance(BPE.from_files(roberta_files["vocab"], roberta_files["merges"]), Model)
class TestWordPiece:
def test_instantiate(self, bert_files):
assert isinstance(WordPiece.empty(), Model)
assert isinstance(WordPiece.from_files(bert_files["vocab"]), Model)
class TestWordLevel:
def test_instantiate(self, roberta_files):
assert isinstance(WordLevel.empty(), Model)
# The WordLevel model expects a vocab.json using the same format as roberta
# so we can just try to load with this file
assert isinstance(WordLevel.from_files(roberta_files["vocab"]), Model)

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@ -0,0 +1,82 @@
from tokenizers import Tokenizer
from tokenizers.models import BPE
from tokenizers.normalizers import BertNormalizer, Sequence, Lowercase, Strip
class TestBertNormalizer:
def test_strip_accents(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = BertNormalizer(
strip_accents=True, lowercase=False, handle_chinese_chars=False, clean_text=False
)
output = tokenizer.normalize("Héllò")
assert output == "Hello"
def test_handle_chinese_chars(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = BertNormalizer(
strip_accents=False, lowercase=False, handle_chinese_chars=True, clean_text=False
)
output = tokenizer.normalize("你好")
assert output == " 你 好 "
def test_clean_text(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = BertNormalizer(
strip_accents=False, lowercase=False, handle_chinese_chars=False, clean_text=True
)
output = tokenizer.normalize("\ufeffHello")
assert output == "Hello"
def test_lowercase(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = BertNormalizer(
strip_accents=False, lowercase=True, handle_chinese_chars=False, clean_text=False
)
output = tokenizer.normalize("Héllò")
assert output == "héllò"
class TestSequence:
def test_can_make_sequences(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = Sequence([Lowercase(), Strip()])
output = tokenizer.normalize(" HELLO ")
assert output == "hello"
class TestLowercase:
def test_lowercase(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = Lowercase()
output = tokenizer.normalize("HELLO")
assert output == "hello"
class TestStrip:
def test_left_strip(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = Strip(left=True, right=False)
output = tokenizer.normalize(" hello ")
assert output == "hello "
def test_right_strip(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = Strip(left=False, right=True)
output = tokenizer.normalize(" hello ")
assert output == " hello"
def test_full_strip(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.normalizer = Strip(left=True, right=True)
output = tokenizer.normalize(" hello ")
assert output == "hello"

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@ -0,0 +1,59 @@
import pytest
from tokenizers.pre_tokenizers import (
PreTokenizer,
ByteLevel,
Whitespace,
WhitespaceSplit,
BertPreTokenizer,
Metaspace,
CharDelimiterSplit,
)
class TestByteLevel:
def test_instantiate(self):
assert ByteLevel() is not None
assert ByteLevel(add_prefix_space=True) is not None
assert ByteLevel(add_prefix_space=False) is not None
assert isinstance(ByteLevel(), PreTokenizer)
def test_has_alphabet(self):
assert isinstance(ByteLevel.alphabet(), list)
assert len(ByteLevel.alphabet()) == 256
class TestWhitespace:
def test_instantiate(self):
assert Whitespace() is not None
assert isinstance(Whitespace(), PreTokenizer)
class TestWhitespaceSplit:
def test_instantiate(self):
assert WhitespaceSplit() is not None
assert isinstance(WhitespaceSplit(), PreTokenizer)
class TestBertPreTokenizer:
def test_instantiate(self):
assert BertPreTokenizer() is not None
assert isinstance(BertPreTokenizer(), PreTokenizer)
class TestMetaspace:
def test_instantiate(self):
assert Metaspace() is not None
assert Metaspace(replacement="-") is not None
with pytest.raises(Exception, match="replacement must be a character"):
Metaspace(replacement="")
assert Metaspace(add_prefix_space=True) is not None
assert isinstance(Metaspace(), PreTokenizer)
class TestCharDelimiterSplit:
def test_instantiate(self):
assert CharDelimiterSplit("-") is not None
with pytest.raises(Exception, match="delimiter must be a single character"):
CharDelimiterSplit("")
assert isinstance(CharDelimiterSplit(" "), PreTokenizer)

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@ -0,0 +1,62 @@
from ..utils import data_dir, roberta_files
from tokenizers import Tokenizer
from tokenizers.models import BPE
from tokenizers.pre_tokenizers import ByteLevel as ByteLevelPreTokenizer
from tokenizers.processors import PostProcessor, BertProcessing, RobertaProcessing, ByteLevel
class TestBertProcessing:
def test_instantiate(self):
processor = BertProcessing(("[SEP]", 0), ("[CLS]", 1))
assert processor is not None
assert isinstance(processor, PostProcessor)
def test_processing(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_special_tokens(["[SEP]", "[CLS]"])
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
tokenizer.post_processor = BertProcessing(("[SEP]", 0), ("[CLS]", 1))
output = tokenizer.encode("my name", "pair")
assert output.tokens == ["[CLS]", "my", "name", "[SEP]", "pair", "[SEP]"]
assert output.ids == [1, 2, 3, 0, 6, 0]
class TestRobertaProcessing:
def test_instantiate(self):
processor = RobertaProcessing(("</s>", 1), ("<s>", 0))
assert processor is not None
assert isinstance(processor, PostProcessor)
def test_processing(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_special_tokens(["<s>", "</s>"])
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
tokenizer.post_processor = RobertaProcessing(("</s>", 1), ("<s>", 0))
output = tokenizer.encode("my name", "pair")
assert output.tokens == ["<s>", "my", "name", "</s>", "</s>", "pair", "</s>"]
assert output.ids == [0, 2, 3, 1, 1, 6, 1]
class TestByteLevelProcessing:
def test_instantiate(self):
assert ByteLevel() is not None
assert ByteLevel(trim_offsets=True) is not None
assert isinstance(ByteLevel(), PostProcessor)
def test_processing(self, roberta_files):
tokenizer = Tokenizer(BPE.from_files(roberta_files["vocab"], roberta_files["merges"]))
tokenizer.pre_tokenizer = ByteLevelPreTokenizer(add_prefix_space=True)
# Keeps original offsets
output = tokenizer.encode("My name is John")
assert output.tokens == ["ĠMy", "Ġname", "Ġis", "ĠJohn"]
assert output.offsets == [(0, 2), (2, 7), (7, 10), (10, 15)]
# Trims offsets when activated
tokenizer.post_processor = ByteLevel(trim_offsets=True)
output = tokenizer.encode("My name is John")
assert output.tokens == ["ĠMy", "Ġname", "Ġis", "ĠJohn"]
assert output.offsets == [(0, 2), (3, 7), (8, 10), (11, 15)]

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@ -0,0 +1,221 @@
from ..utils import data_dir, roberta_files
from tokenizers import AddedToken, Tokenizer
from tokenizers.models import Model, BPE
from tokenizers.pre_tokenizers import ByteLevel
from tokenizers.processors import RobertaProcessing
from tokenizers.normalizers import Lowercase
class TestAddedToken:
def test_instantiate_with_content_only(self):
added_token = AddedToken("<mask>")
assert type(added_token) == AddedToken
assert str(added_token) == "<mask>"
assert (
repr(added_token)
== 'AddedToken("<mask>", rstrip=False, lstrip=False, single_word=False)'
)
assert added_token.rstrip == False
assert added_token.lstrip == False
assert added_token.single_word == False
def test_can_set_rstrip(self):
added_token = AddedToken("<mask>", rstrip=True)
assert added_token.rstrip == True
assert added_token.lstrip == False
assert added_token.single_word == False
def test_can_set_lstrip(self):
added_token = AddedToken("<mask>", lstrip=True)
assert added_token.rstrip == False
assert added_token.lstrip == True
assert added_token.single_word == False
def test_can_set_single_world(self):
added_token = AddedToken("<mask>", single_word=True)
assert added_token.rstrip == False
assert added_token.lstrip == False
assert added_token.single_word == True
class TestTokenizer:
def test_has_expected_type_and_methods(self):
tokenizer = Tokenizer(BPE.empty())
assert type(tokenizer) == Tokenizer
assert callable(tokenizer.num_special_tokens_to_add)
assert callable(tokenizer.get_vocab)
assert callable(tokenizer.get_vocab_size)
assert callable(tokenizer.enable_truncation)
assert callable(tokenizer.no_truncation)
assert callable(tokenizer.enable_padding)
assert callable(tokenizer.no_padding)
assert callable(tokenizer.normalize)
assert callable(tokenizer.encode)
assert callable(tokenizer.encode_batch)
assert callable(tokenizer.decode)
assert callable(tokenizer.decode_batch)
assert callable(tokenizer.token_to_id)
assert callable(tokenizer.id_to_token)
assert callable(tokenizer.add_tokens)
assert callable(tokenizer.add_special_tokens)
assert callable(tokenizer.train)
assert callable(tokenizer.post_process)
assert isinstance(tokenizer.model, Model)
assert tokenizer.normalizer is None
assert tokenizer.pre_tokenizer is None
assert tokenizer.post_processor is None
assert tokenizer.decoder is None
def test_add_tokens(self):
tokenizer = Tokenizer(BPE.empty())
added = tokenizer.add_tokens(["my", "name", "is", "john"])
assert added == 4
added = tokenizer.add_tokens([AddedToken("the"), AddedToken("quick", rstrip=True)])
assert added == 2
def test_add_special_tokens(self):
tokenizer = Tokenizer(BPE.empty())
# Can add special tokens as `str`
added = tokenizer.add_special_tokens(["my", "name", "is", "john"])
assert added == 4
# Can add special tokens as `AddedToken`
added = tokenizer.add_special_tokens([AddedToken("the"), AddedToken("quick", rstrip=True)])
assert added == 2
def test_encode(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
# Can encode single sequence
output = tokenizer.encode("my name is john")
assert output.tokens == ["my", "name", "is", "john"]
assert type(output.ids) == list
assert type(output.type_ids) == list
assert type(output.offsets) == list
assert type(output.words) == list
assert type(output.special_tokens_mask) == list
assert type(output.attention_mask) == list
assert type(output.overflowing) == list
# Can encode a pair of sequences
output = tokenizer.encode("my name is john", "pair")
assert output.tokens == ["my", "name", "is", "john", "pair"]
# Can encode a batch with both a single sequence and a pair of sequences
output = tokenizer.encode_batch(["my name is john", ("my name is john", "pair")])
assert len(output) == 2
def test_encode_add_special_tokens(self, roberta_files):
tokenizer = Tokenizer(BPE.from_files(roberta_files["vocab"], roberta_files["merges"]))
tokenizer.add_special_tokens(["<s>", "</s>"])
tokenizer.pre_tokenizer = ByteLevel(add_prefix_space=True)
tokenizer.post_processor = RobertaProcessing(
("</s>", tokenizer.token_to_id("</s>")), ("<s>", tokenizer.token_to_id("<s>")),
)
# Can encode with special tokens
output_with_specials = tokenizer.encode("My name is John", add_special_tokens=True)
assert output_with_specials.tokens == ["<s>", "ĠMy", "Ġname", "Ġis", "ĠJohn", "</s>"]
# Can encode without special tokens
output_without_specials = tokenizer.encode("My name is John", add_special_tokens=False)
assert output_without_specials.tokens == ["ĠMy", "Ġname", "Ġis", "ĠJohn"]
def test_truncation(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
tokenizer.enable_truncation(2)
# Can truncate single sequences
output = tokenizer.encode("my name is john")
assert output.tokens == ["my", "name"]
# Can truncate pair sequences as well
output = tokenizer.encode("my name is john", "pair")
assert output.tokens == ["my", "pair"]
def test_padding(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
# By default it does nothing when encoding single sequence
tokenizer.enable_padding()
output = tokenizer.encode("my name")
assert output.tokens == ["my", "name"]
# Can pad to the longest in a batch
output = tokenizer.encode_batch(["my name", "my name is john"])
assert all([len(encoding) == 4 for encoding in output])
# Can pad to the specified max length otherwise
tokenizer.enable_padding(max_length=4)
output = tokenizer.encode("my name")
assert output.tokens == ["my", "name", "[PAD]", "[PAD]"]
output = tokenizer.encode("my name", "pair")
assert output.tokens == ["my", "name", "pair", "[PAD]"]
def test_decode(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
# Can decode single sequences
output = tokenizer.decode([0, 1, 2, 3])
assert output == "my name is john"
# Can decode batch
output = tokenizer.decode_batch([[0, 1, 2, 3], [4]])
assert output == ["my name is john", "pair"]
def test_get_vocab(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
# Can retrieve vocab with added tokens
vocab = tokenizer.get_vocab(with_added_tokens=True)
assert vocab == {"is": 2, "john": 3, "my": 0, "name": 1, "pair": 4}
# Can retrieve vocab without added tokens
vocab = tokenizer.get_vocab(with_added_tokens=False)
assert vocab == {}
def test_get_vocab_size(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
# Can retrieve vocab's size with added tokens
size = tokenizer.get_vocab_size(with_added_tokens=True)
assert size == 5
# Can retrieve vocab's size without added tokens
size = tokenizer.get_vocab_size(with_added_tokens=False)
assert size == 0
def test_normalize(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
tokenizer.normalizer = Lowercase()
output = tokenizer.normalize("My Name Is John")
assert output == "my name is john"
def test_post_process(self):
tokenizer = Tokenizer(BPE.empty())
tokenizer.add_tokens(["my", "name", "is", "john", "pair"])
tokenizer.enable_truncation(2)
tokenizer.enable_padding(max_length=4)
encoding = tokenizer.encode("my name is john")
pair_encoding = tokenizer.encode("pair")
# Can post process a single encoding
output = tokenizer.post_process(encoding)
assert output.tokens == ["my", "name", "[PAD]", "[PAD]"]
# Can post process a pair of encodings
output = tokenizer.post_process(encoding, pair_encoding)
assert output.tokens == ["my", "pair", "[PAD]", "[PAD]"]

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@ -0,0 +1,21 @@
from ..utils import data_dir, bert_files
from tokenizers import BertWordPieceTokenizer
class TestBertWordPieceBPE:
def test_basic_encode(self, bert_files):
tokenizer = BertWordPieceTokenizer(bert_files["vocab"])
# Encode with special tokens by default
output = tokenizer.encode("My name is John", "pair")
assert output.ids == [101, 2026, 2171, 2003, 2198, 102, 3940, 102]
assert output.tokens == ["[CLS]", "my", "name", "is", "john", "[SEP]", "pair", "[SEP]"]
assert output.offsets == [(0, 0), (0, 2), (3, 7), (8, 10), (11, 15), (0, 0), (0, 4), (0, 0)]
assert output.type_ids == [0, 0, 0, 0, 0, 0, 1, 1]
# Can encode without the special tokens
output = tokenizer.encode("My name is John", "pair", add_special_tokens=False)
assert output.ids == [2026, 2171, 2003, 2198, 3940]
assert output.tokens == ["my", "name", "is", "john", "pair"]
assert output.offsets == [(0, 2), (3, 7), (8, 10), (11, 15), (0, 4)]
assert output.type_ids == [0, 0, 0, 0, 1]

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@ -0,0 +1,81 @@
from ..utils import data_dir, roberta_files
from tokenizers import ByteLevelBPETokenizer
class TestByteLevelBPE:
def test_basic_encode(self, roberta_files):
tokenizer = ByteLevelBPETokenizer(roberta_files["vocab"], roberta_files["merges"])
output = tokenizer.encode("The quick brown fox jumps over the lazy dog")
assert output.ids == [133, 2119, 6219, 23602, 13855, 81, 5, 22414, 2335]
assert output.tokens == [
"The",
"Ġquick",
"Ġbrown",
"Ġfox",
"Ġjumps",
"Ġover",
"Ġthe",
"Ġlazy",
"Ġdog",
]
assert output.offsets == [
(0, 3),
(3, 9),
(9, 15),
(15, 19),
(19, 25),
(25, 30),
(30, 34),
(34, 39),
(39, 43),
]
def test_add_prefix_space(self, roberta_files):
tokenizer = ByteLevelBPETokenizer(
roberta_files["vocab"], roberta_files["merges"], add_prefix_space=True
)
output = tokenizer.encode("The quick brown fox jumps over the lazy dog")
assert output.ids == [20, 2119, 6219, 23602, 13855, 81, 5, 22414, 2335]
assert output.tokens == [
"ĠThe",
"Ġquick",
"Ġbrown",
"Ġfox",
"Ġjumps",
"Ġover",
"Ġthe",
"Ġlazy",
"Ġdog",
]
assert output.offsets == [
(0, 3),
(3, 9),
(9, 15),
(15, 19),
(19, 25),
(25, 30),
(30, 34),
(34, 39),
(39, 43),
]
def test_lowerspace(self, roberta_files):
tokenizer = ByteLevelBPETokenizer(
roberta_files["vocab"], roberta_files["merges"], add_prefix_space=True, lowercase=True
)
output = tokenizer.encode("The Quick Brown Fox Jumps Over The Lazy Dog")
assert output.ids == [5, 2119, 6219, 23602, 13855, 81, 5, 22414, 2335]
assert output.tokens == [
"Ġthe",
"Ġquick",
"Ġbrown",
"Ġfox",
"Ġjumps",
"Ġover",
"Ġthe",
"Ġlazy",
"Ġdog",
]

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@ -0,0 +1,44 @@
from ..utils import data_dir, openai_files
from tokenizers import CharBPETokenizer
class TestBertWordPieceBPE:
def test_basic_encode(self, openai_files):
tokenizer = CharBPETokenizer(openai_files["vocab"], openai_files["merges"])
output = tokenizer.encode("My name is John", "pair")
assert output.ids == [0, 253, 1362, 544, 0, 7, 12662, 2688]
assert output.tokens == [
"<unk>",
"y</w>",
"name</w>",
"is</w>",
"<unk>",
"o",
"hn</w>",
"pair</w>",
]
assert output.offsets == [
(0, 1),
(1, 2),
(3, 7),
(8, 10),
(11, 12),
(12, 13),
(13, 15),
(0, 4),
]
assert output.type_ids == [0, 0, 0, 0, 0, 0, 0, 1]
def test_lowercase(self, openai_files):
tokenizer = CharBPETokenizer(openai_files["vocab"], openai_files["merges"], lowercase=True)
output = tokenizer.encode("My name is John", "pair", add_special_tokens=False)
assert output.ids == [547, 1362, 544, 2476, 2688]
assert output.tokens == ["my</w>", "name</w>", "is</w>", "john</w>", "pair</w>"]
assert output.offsets == [(0, 2), (3, 7), (8, 10), (11, 15), (0, 4)]
assert output.type_ids == [0, 0, 0, 0, 1]
def test_decoding(self, openai_files):
tokenizer = CharBPETokenizer(openai_files["vocab"], openai_files["merges"], lowercase=True)
decoded = tokenizer.decode(tokenizer.encode("my name is john").ids)
assert decoded == "my name is john"

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@ -0,0 +1,58 @@
import os
import requests
import pytest
DATA_PATH = os.path.join("tests", "data")
def download(url):
filename = url.rsplit("/")[-1]
filepath = os.path.join(DATA_PATH, filename)
if not os.path.exists(filepath):
with open(filepath, "wb") as f:
response = requests.get(url, stream=True)
response.raise_for_status()
for chunk in response.iter_content(1024):
f.write(chunk)
return filepath
@pytest.fixture(scope="session")
def data_dir():
assert os.getcwd().endswith("python")
exist = os.path.exists(DATA_PATH) and os.path.isdir(DATA_PATH)
if not exist:
os.mkdir(DATA_PATH)
@pytest.fixture(scope="session")
def roberta_files(data_dir):
return {
"vocab": download(
"https://s3.amazonaws.com/models.huggingface.co/bert/roberta-base-vocab.json"
),
"merges": download(
"https://s3.amazonaws.com/models.huggingface.co/bert/roberta-base-merges.txt"
),
}
@pytest.fixture(scope="session")
def bert_files(data_dir):
return {
"vocab": download(
"https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt"
),
}
@pytest.fixture(scope="session")
def openai_files(data_dir):
return {
"vocab": download(
"https://s3.amazonaws.com/models.huggingface.co/bert/openai-gpt-vocab.json"
),
"merges": download(
"https://s3.amazonaws.com/models.huggingface.co/bert/openai-gpt-merges.txt"
),
}

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@ -158,3 +158,7 @@ class WordLevel(Model):
The unknown token to be used by the model.
"""
pass
@staticmethod
def empty() -> Model:
""" Instantiate an empty WordLevel Model. """
pass