🎨 reformat codes

python/core/ltp_core/datamodules/adapters/semantic_role_labeling.py

@@ -1,4 +1,5 @@
 import numpy
+
 from ltp_core.datamodules.components.srl import Srl
 from ltp_core.datamodules.utils.datasets import load_dataset
 

python/core/ltp_core/datamodules/components/bio.py

@@ -8,6 +8,7 @@
 from os.path import join
 
 import datasets
+
 from ltp_core.datamodules.utils.iterator import iter_blocks
 from ltp_core.datamodules.utils.vocab_helper import vocab_builder
 

python/core/ltp_core/datamodules/components/conllu.py

@@ -9,6 +9,7 @@
 from os.path import join
 
 import datasets
+
 from ltp_core.datamodules.utils.iterator import iter_blocks
 from ltp_core.datamodules.utils.vocab_helper import vocab_builder
 

python/core/ltp_core/datamodules/components/srl.py

@@ -8,6 +8,7 @@
 from os.path import join
 
 import datasets
+
 from ltp_core.datamodules.utils.iterator import iter_blocks
 from ltp_core.datamodules.utils.vocab_helper import vocab_builder
 

python/core/ltp_core/datamodules/multi_task_datamodule.py

@@ -1,12 +1,13 @@
 from typing import Any, Dict, Optional
 
 import datasets
-from ltp_core.datamodules.utils.collate import collate
-from ltp_core.datamodules.utils.multitask_dataloader import MultiTaskDataloader
 from pytorch_lightning import LightningDataModule
 from torch.utils.data import DataLoader, Dataset
 from transformers import AutoTokenizer
 
+from ltp_core.datamodules.utils.collate import collate
+from ltp_core.datamodules.utils.multitask_dataloader import MultiTaskDataloader
+
 
 class MultiTaskDataModule(LightningDataModule):
     """LightningDataModule for LTP datasets.

python/core/ltp_core/datamodules/task_datamodule.py

@@ -1,11 +1,12 @@
 from typing import Any, Dict, Optional
 
 import datasets
-from ltp_core.datamodules.utils.collate import collate
 from pytorch_lightning import LightningDataModule
 from torch.utils.data import DataLoader, Dataset
 from transformers import AutoTokenizer
 
+from ltp_core.datamodules.utils.collate import collate
+
 
 class TaskDataModule(LightningDataModule):
     """LightningDataModule for LTP datasets.

python/core/ltp_core/eval.py

@@ -33,11 +33,12 @@
 from typing import List, Tuple
 
 import hydra
-from ltp_core import utils
 from omegaconf import DictConfig
 from pytorch_lightning import LightningDataModule, LightningModule, Trainer
 from pytorch_lightning.loggers import LightningLoggerBase
 
+from ltp_core import utils
+
 log = utils.get_pylogger(__name__)
 
 

python/core/ltp_core/models/components/graph.py

@@ -2,9 +2,10 @@
 # Author: Yunlong Feng <[email protected]>
 from collections import namedtuple
 
+from torch import nn
+
 from ltp_core.models.nn.biaffine import Biaffine
 from ltp_core.models.nn.mlp import MLP
-from torch import nn
 
 GraphResult = namedtuple("GraphResult", ["arc_logits", "rel_logits", "attention_mask"])
 

python/core/ltp_core/models/components/sent.py

@@ -1,8 +1,9 @@
 from collections import namedtuple
 
-from ltp_core.models.nn.mlp import MLP
 from torch import nn
 
+from ltp_core.models.nn.mlp import MLP
+
 SentClassifierResult = namedtuple("SentClassifierResult", ["logits"])
 
 

python/core/ltp_core/models/components/token.py

@@ -1,11 +1,12 @@
 from collections import namedtuple
 from typing import Optional
 
+from torch import nn
+
 from ltp_core.models.nn.biaffine import Biaffine
 from ltp_core.models.nn.crf import CRF
 from ltp_core.models.nn.mlp import MLP
 from ltp_core.models.nn.relative_transformer import RelativeTransformer
-from torch import nn
 
 TokenClassifierResult = namedtuple("TokenClassifierResult", ["logits", "attention_mask", "crf"])
 

python/core/ltp_core/models/criterion/graph.py

@@ -1,8 +1,9 @@
 import torch
-from ltp_core.models.components.graph import GraphResult
 from torch import Tensor
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, Module
 
+from ltp_core.models.components.graph import GraphResult
+
 
 class DEPLoss(Module):
     def __init__(self, loss_interpolation=0.4):

python/core/ltp_core/models/criterion/sent.py

@@ -1,7 +1,8 @@
-from ltp_core.models.components.sent import SentClassifierResult
 from torch import Tensor
 from torch.nn import CrossEntropyLoss, Module
 
+from ltp_core.models.components.sent import SentClassifierResult
+
 
 class ClassificationLoss(Module):
     def forward(self, result: SentClassifierResult, labels: Tensor, **kwargs) -> Tensor:

python/core/ltp_core/models/criterion/token.py

@@ -1,11 +1,12 @@
 from typing import Callable
 
 import torch
-from ltp_core.models.components.token import TokenClassifierResult
-from ltp_core.models.functional.distill import kd_ce_loss, kd_mse_loss
 from torch import Tensor
 from torch.nn import CrossEntropyLoss, Module
 
+from ltp_core.models.components.token import TokenClassifierResult
+from ltp_core.models.functional.distill import kd_ce_loss, kd_mse_loss
+
 
 class TokenLoss(Module):
     def forward(self, result: TokenClassifierResult, labels: Tensor, *args, **kwargs) -> Tensor:

python/core/ltp_core/models/lit_model.py

@@ -2,12 +2,13 @@
 from typing import Any, List
 
 import torch
-from ltp_core.models.ltp_model import LTPModule
-from ltp_core.models.utils import instantiate_omega as instantiate
 from pytorch_lightning import LightningModule
 from torch.nn import ModuleDict
 from torchmetrics import MeanMetric, MetricCollection
 
+from ltp_core.models.ltp_model import LTPModule
+from ltp_core.models.utils import instantiate_omega as instantiate
+
 
 class LTPLitModule(LightningModule):
     """LightningModule for ltp_core.

python/core/ltp_core/models/metrics/graph.py

@@ -1,11 +1,12 @@
 from typing import Any, Optional
 
 import torch
-from ltp_core.algorithms import eisner
-from ltp_core.models.components.graph import GraphResult
 from torch import Tensor, tensor
 from torchmetrics import Metric
 
+from ltp_core.algorithms import eisner
+from ltp_core.models.components.graph import GraphResult
+
 
 class DEPLas(Metric):
     is_differentiable: bool = False

python/core/ltp_core/models/metrics/sent.py

@@ -1,9 +1,10 @@
 from typing import Optional
 
-from ltp_core.models.components.sent import SentClassifierResult
 from torch import Tensor
 from torchmetrics import Accuracy
 
+from ltp_core.models.components.sent import SentClassifierResult
+
 
 class ClsAccuracy(Accuracy):
     is_differentiable: bool = False

python/core/ltp_core/models/metrics/token.py

@@ -1,11 +1,12 @@
 from typing import Any, List, Optional, Union
 
 import torch
-from ltp_core.algorithms import get_entities
-from ltp_core.models.components.token import TokenClassifierResult
 from torch import Tensor, tensor
 from torchmetrics import Accuracy, Metric
 
+from ltp_core.algorithms import get_entities
+from ltp_core.models.components.token import TokenClassifierResult
+
 
 class TokenAccuracy(Accuracy):
     is_differentiable: bool = False

python/core/ltp_core/models/nn/relative_transformer.py

@@ -6,9 +6,10 @@
 
 import torch
 import torch.nn.functional as F
-from ltp_core.models.nn.mlp import MLP
 from torch import Tensor, nn
 
+from ltp_core.models.nn.mlp import MLP
+
 
 class RelativeEmbedding(nn.Module):
     """This module produces sinusoidal positional embeddings of any length.

python/core/ltp_core/train.py

@@ -34,11 +34,12 @@
 
 import hydra
 import pytorch_lightning as pl
-from ltp_core import utils
 from omegaconf import DictConfig
 from pytorch_lightning import Callback, LightningDataModule, LightningModule, Trainer
 from pytorch_lightning.loggers import LightningLoggerBase
 
+from ltp_core import utils
+
 log = utils.get_pylogger(__name__)
 
 

python/core/ltp_core/utils/rich_utils.py

@@ -5,11 +5,12 @@
 import rich.syntax
 import rich.tree
 from hydra.core.hydra_config import HydraConfig
-from ltp_core.utils import pylogger
 from omegaconf import DictConfig, OmegaConf, open_dict
 from pytorch_lightning.utilities import rank_zero_only
 from rich.prompt import Prompt
 
+from ltp_core.utils import pylogger
+
 log = pylogger.get_pylogger(__name__)
 
 

python/core/ltp_core/utils/utils.py

@@ -5,12 +5,13 @@
 from typing import Any, Callable, Dict, List
 
 import hydra
-from ltp_core.utils import pylogger, rich_utils
 from omegaconf import DictConfig
 from pytorch_lightning import Callback
 from pytorch_lightning.loggers import LightningLoggerBase
 from pytorch_lightning.utilities import rank_zero_only
 
+from ltp_core.utils import pylogger, rich_utils
+
 log = pylogger.get_pylogger(__name__)
 
 

python/core/tests/helpers/run_if.py

@@ -10,6 +10,7 @@
 import torch
 from packaging.version import Version
 from pkg_resources import get_distribution
+
 from tests.helpers.package_available import (
     _COMET_AVAILABLE,
     _DEEPSPEED_AVAILABLE,

python/core/tests/helpers/run_sh_command.py

@@ -1,6 +1,7 @@
 from typing import List
 
 import pytest
+
 from tests.helpers.package_available import _SH_AVAILABLE
 
 if _SH_AVAILABLE:

python/core/tests/test_eval.py

@@ -2,9 +2,10 @@
 
 import pytest
 from hydra.core.hydra_config import HydraConfig
+from omegaconf import open_dict
+
 from ltp_core.eval import evaluate
 from ltp_core.train import train
-from omegaconf import open_dict
 
 
 @pytest.mark.slow

python/core/tests/test_sweeps.py

@@ -1,4 +1,5 @@
 import pytest
+
 from tests.helpers.run_if import RunIf
 from tests.helpers.run_sh_command import run_sh_command
 

python/core/tests/test_train.py

@@ -2,8 +2,9 @@
 
 import pytest
 from hydra.core.hydra_config import HydraConfig
-from ltp_core.train import train
 from omegaconf import open_dict
+
+from ltp_core.train import train
 from tests.helpers.run_if import RunIf
 
 

python/extension/examples/legacy_train.py

@@ -1,11 +1,4 @@
-from ltp_extension.perceptron import (
-    Algorithm,
-    CWSModel,
-    CWSTrainer,
-    Model,
-    ModelType,
-    Trainer,
-)
+from ltp_extension.perceptron import Algorithm, CWSModel, CWSTrainer, Model, ModelType, Trainer
 
 
 def train_cws():

python/interface/examples/issues.py

@@ -0,0 +1,32 @@
+from ltp import LTP
+
+
+def issue590():
+    ltp = LTP("LTP/tiny")
+    ltp.add_words(words=["[ENT]"])
+    print(ltp.pipeline(["[ENT] Info"], tasks=["cws"]))
+
+    ltp.add_words(words=["[EOS]"])
+    print(ltp.pipeline(["[EOS] Info"], tasks=["cws"]))
+
+
+def issue592():
+    legacy_ltp = LTP("LTP/legacy")
+
+    legacy_ltp.add_words(words=["SCSG", "IP地址"])
+    print(legacy_ltp.pipeline(["SCSGIP地址"], tasks=["cws"]))
+
+    neural_ltp = LTP("LTP/tiny")
+
+    # not bug, but not work because of the bert tokenizer
+    neural_ltp.add_words(words=["SCSG", "IP地址"])
+    print(neural_ltp.pipeline(["SCSGIP地址"], tasks=["cws"]))
+
+
+def main():
+    issue590()
+    issue592()
+
+
+if __name__ == "__main__":
+    main()

python/interface/examples/simple.py

@@ -1,5 +1,4 @@
 import torch
-
 from ltp import LTP
 
 
@@ -48,33 +47,9 @@ def neural():
     print(result.sdp)
 
 
-def issue590():
-    ltp = LTP("LTP/tiny")
-    ltp.add_words(words=["[ENT]"])
-    print(ltp.pipeline(["[ENT] Info"], tasks=["cws"]))
-
-    ltp.add_words(words=["[EOS]"])
-    print(ltp.pipeline(["[EOS] Info"], tasks=["cws"]))
-
-
-def issue592():
-    legacy_ltp = LTP("LTP/legacy")
-
-    legacy_ltp.add_words(words=['SCSG', 'IP地址'])
-    print(legacy_ltp.pipeline(['SCSGIP地址'], tasks=["cws"]))
-
-    neural_ltp = LTP("LTP/tiny")
-
-    # not bug, but not work because of the bert tokenizer
-    neural_ltp.add_words(words=['SCSG', 'IP地址'])
-    print(neural_ltp.pipeline(['SCSGIP地址'], tasks=["cws"]))
-
-
 def main():
-    # legacy()
-    # neural()
-    # issue590()
-    issue592()
+    legacy()
+    neural()
 
 
 if __name__ == "__main__":