diff --git a/fastNLP/__init__.py b/fastNLP/__init__.py index 5dd5fd54..c67e5919 100644 --- a/fastNLP/__init__.py +++ b/fastNLP/__init__.py @@ -52,8 +52,8 @@ __all__ = [ "cache_results" ] +__version__ = '0.4.0' + from .core import * from . import models from . import modules - -__version__ = '0.4.0' diff --git a/fastNLP/core/batch.py b/fastNLP/core/batch.py index b031d051..c1289adf 100644 --- a/fastNLP/core/batch.py +++ b/fastNLP/core/batch.py @@ -2,6 +2,10 @@ batch 模块实现了 fastNLP 所需的 Batch 类。 """ +__all__ = [ + "Batch" +] + import atexit from queue import Empty, Full @@ -11,10 +15,6 @@ import torch.multiprocessing as mp from .sampler import RandomSampler -__all__ = [ - "Batch" -] - _python_is_exit = False diff --git a/fastNLP/core/callback.py b/fastNLP/core/callback.py index 51495f23..6825ea6e 100644 --- a/fastNLP/core/callback.py +++ b/fastNLP/core/callback.py @@ -49,6 +49,18 @@ callback模块实现了 fastNLP 中的许多 callback 类，用于增强 :class: trainer.train() """ +__all__ = [ + "Callback", + "GradientClipCallback", + "EarlyStopCallback", + "TensorboardCallback", + "LRScheduler", + "ControlC", + + "CallbackException", + "EarlyStopError" +] + import os import torch @@ -62,18 +74,6 @@ except: from ..io.model_io import ModelSaver, ModelLoader -__all__ = [ - "Callback", - "GradientClipCallback", - "EarlyStopCallback", - "TensorboardCallback", - "LRScheduler", - "ControlC", - - "CallbackException", - "EarlyStopError" -] - class Callback(object): """ diff --git a/fastNLP/core/dataset.py b/fastNLP/core/dataset.py index f20dd1f8..2da9f6d9 100644 --- a/fastNLP/core/dataset.py +++ b/fastNLP/core/dataset.py @@ -272,6 +272,10 @@ """ +__all__ = [ + "DataSet" +] + import _pickle as pickle import warnings @@ -282,10 +286,6 @@ from .field import FieldArray from .instance import Instance from .utils import _get_func_signature -__all__ = [ - "DataSet" -] - class DataSet(object): """ diff --git a/fastNLP/core/field.py b/fastNLP/core/field.py index 14e2538d..21ead327 100644 --- a/fastNLP/core/field.py +++ b/fastNLP/core/field.py @@ -3,10 +3,6 @@ field模块实现了 FieldArray 和若干 Padder。 FieldArray 是 :class:`~fas 原理部分请参考 :doc:`fastNLP.core.dataset` """ -from copy import deepcopy - -import numpy as np - __all__ = [ "FieldArray", "Padder", @@ -14,6 +10,10 @@ __all__ = [ "EngChar2DPadder" ] +from copy import deepcopy + +import numpy as np + class FieldArray(object): """ diff --git a/fastNLP/core/losses.py b/fastNLP/core/losses.py index 797b557d..ddc2c49f 100644 --- a/fastNLP/core/losses.py +++ b/fastNLP/core/losses.py @@ -2,6 +2,18 @@ losses 模块定义了 fastNLP 中所需的各种损失函数，一般做为 :class:`~fastNLP.Trainer` 的参数使用。 """ +__all__ = [ + "LossBase", + + "LossFunc", + "LossInForward", + + "CrossEntropyLoss", + "BCELoss", + "L1Loss", + "NLLLoss" +] + import inspect from collections import defaultdict @@ -15,18 +27,6 @@ from .utils import _check_arg_dict_list from .utils import _check_function_or_method from .utils import _get_func_signature -__all__ = [ - "LossBase", - - "LossFunc", - "LossInForward", - - "CrossEntropyLoss", - "BCELoss", - "L1Loss", - "NLLLoss" -] - class LossBase(object): """ diff --git a/fastNLP/core/metrics.py b/fastNLP/core/metrics.py index 5ea2a5f1..f633a80f 100644 --- a/fastNLP/core/metrics.py +++ b/fastNLP/core/metrics.py @@ -2,6 +2,13 @@ metrics 模块实现了 fastNLP 所需的各种常用衡量指标，一般做为 :class:`~fastNLP.Trainer` 的参数使用。 """ +__all__ = [ + "MetricBase", + "AccuracyMetric", + "SpanFPreRecMetric", + "SQuADMetric" +] + import inspect from collections import defaultdict @@ -16,13 +23,6 @@ from .utils import _get_func_signature from .utils import seq_len_to_mask from .vocabulary import Vocabulary -__all__ = [ - "MetricBase", - "AccuracyMetric", - "SpanFPreRecMetric", - "SQuADMetric" -] - class MetricBase(object): """ diff --git a/fastNLP/core/optimizer.py b/fastNLP/core/optimizer.py index 28f618f9..ef619042 100644 --- a/fastNLP/core/optimizer.py +++ b/fastNLP/core/optimizer.py @@ -2,14 +2,14 @@ optimizer 模块定义了 fastNLP 中所需的各种优化器，一般做为 :class:`~fastNLP.Trainer` 的参数使用。 """ -import torch - __all__ = [ "Optimizer", "SGD", "Adam" ] +import torch + class Optimizer(object): """ diff --git a/fastNLP/core/sampler.py b/fastNLP/core/sampler.py index c8577722..c5784f59 100644 --- a/fastNLP/core/sampler.py +++ b/fastNLP/core/sampler.py @@ -1,10 +1,6 @@ """ sampler 子类实现了 fastNLP 所需的各种采样器。 """ -from itertools import chain - -import numpy as np - __all__ = [ "Sampler", "BucketSampler", @@ -12,6 +8,10 @@ __all__ = [ "RandomSampler" ] +from itertools import chain + +import numpy as np + class Sampler(object): """ diff --git a/fastNLP/core/trainer.py b/fastNLP/core/trainer.py index 7efa5d28..702cb6e7 100644 --- a/fastNLP/core/trainer.py +++ b/fastNLP/core/trainer.py @@ -295,6 +295,9 @@ Example2.3 fastNLP已经自带了很多callback函数供使用，可以参考 :doc:`fastNLP.core.callback` 。 """ +__all__ = [ + "Trainer" +] import os import time diff --git a/fastNLP/core/utils.py b/fastNLP/core/utils.py index 6e2f99ff..14ac409f 100644 --- a/fastNLP/core/utils.py +++ b/fastNLP/core/utils.py @@ -1,6 +1,11 @@ """ utils模块实现了 fastNLP 内部和外部所需的很多工具。其中用户可以使用的是 :func:`cache_results` 修饰器。 """ +__all__ = [ + "cache_results", + "seq_len_to_mask" +] + import _pickle import inspect import os @@ -11,10 +16,6 @@ import numpy as np import torch import torch.nn as nn -__all__ = [ - "cache_results", - "seq_len_to_mask" -] _CheckRes = namedtuple('_CheckRes', ['missing', 'unused', 'duplicated', 'required', 'all_needed', 'varargs']) diff --git a/fastNLP/core/vocabulary.py b/fastNLP/core/vocabulary.py index 3d9598a3..43f590fd 100644 --- a/fastNLP/core/vocabulary.py +++ b/fastNLP/core/vocabulary.py @@ -1,12 +1,12 @@ +__all__ = [ + "Vocabulary" +] + from functools import wraps from collections import Counter from .dataset import DataSet -__all__ = [ - "Vocabulary" -] - def _check_build_vocab(func): """A decorator to make sure the indexing is built before used. @@ -322,7 +322,7 @@ class Vocabulary(object): :return str word: the word """ return self.idx2word[idx] - + def clear(self): """ 删除Vocabulary中的词表数据。相当于重新初始化一下。 @@ -333,7 +333,7 @@ class Vocabulary(object): self.word2idx = None self.idx2word = None self.rebuild = True - + def __getstate__(self): """Use to prepare data for pickle. diff --git a/fastNLP/io/__init__.py b/fastNLP/io/__init__.py index 6ce7ebc3..c8d6a441 100644 --- a/fastNLP/io/__init__.py +++ b/fastNLP/io/__init__.py @@ -9,11 +9,6 @@ 这些类的使用方法如下: """ -from .embed_loader import EmbedLoader -from .dataset_loader import DataSetLoader, CSVLoader, JsonLoader, ConllLoader, SNLILoader, SSTLoader, \ - PeopleDailyCorpusLoader, Conll2003Loader -from .model_io import ModelLoader, ModelSaver - __all__ = [ 'EmbedLoader', @@ -29,3 +24,8 @@ __all__ = [ 'ModelLoader', 'ModelSaver', ] + +from .embed_loader import EmbedLoader +from .dataset_loader import DataSetLoader, CSVLoader, JsonLoader, ConllLoader, SNLILoader, SSTLoader, \ + PeopleDailyCorpusLoader, Conll2003Loader +from .model_io import ModelLoader, ModelSaver diff --git a/fastNLP/io/base_loader.py b/fastNLP/io/base_loader.py index 33f59fe5..4ab1e2d0 100644 --- a/fastNLP/io/base_loader.py +++ b/fastNLP/io/base_loader.py @@ -1,10 +1,10 @@ -import _pickle as pickle -import os - __all__ = [ "BaseLoader" ] +import _pickle as pickle +import os + class BaseLoader(object): """ diff --git a/fastNLP/io/config_io.py b/fastNLP/io/config_io.py index e67511ee..4acdbb96 100644 --- a/fastNLP/io/config_io.py +++ b/fastNLP/io/config_io.py @@ -3,18 +3,18 @@ .. todo:: 这个模块中的类可能被抛弃？ """ -import configparser -import json -import os - -from .base_loader import BaseLoader - __all__ = [ "ConfigLoader", "ConfigSection", "ConfigSaver" ] +import configparser +import json +import os + +from .base_loader import BaseLoader + class ConfigLoader(BaseLoader): """ diff --git a/fastNLP/io/dataset_loader.py b/fastNLP/io/dataset_loader.py index a4b233ad..b820af44 100644 --- a/fastNLP/io/dataset_loader.py +++ b/fastNLP/io/dataset_loader.py @@ -10,12 +10,6 @@ dataset_loader模块实现了许多 DataSetLoader, 用于读取不同格式的 # ... do stuff """ -from nltk.tree import Tree - -from ..core.dataset import DataSet -from ..core.instance import Instance -from .file_reader import _read_csv, _read_json, _read_conll - __all__ = [ 'DataSetLoader', 'CSVLoader', @@ -27,6 +21,12 @@ __all__ = [ 'Conll2003Loader', ] +from nltk.tree import Tree + +from ..core.dataset import DataSet +from ..core.instance import Instance +from .file_reader import _read_csv, _read_json, _read_conll + def _download_from_url(url, path): try: diff --git a/fastNLP/io/embed_loader.py b/fastNLP/io/embed_loader.py index 7a845366..fb024e73 100644 --- a/fastNLP/io/embed_loader.py +++ b/fastNLP/io/embed_loader.py @@ -1,3 +1,7 @@ +__all__ = [ + "EmbedLoader" +] + import os import warnings @@ -6,10 +10,6 @@ import numpy as np from ..core.vocabulary import Vocabulary from .base_loader import BaseLoader -__all__ = [ - "EmbedLoader" -] - class EmbedLoader(BaseLoader): """ diff --git a/fastNLP/io/model_io.py b/fastNLP/io/model_io.py index 36393cd4..ffaa4ef5 100644 --- a/fastNLP/io/model_io.py +++ b/fastNLP/io/model_io.py @@ -1,15 +1,15 @@ """ 用于载入和保存模型 """ -import torch - -from .base_loader import BaseLoader - __all__ = [ "ModelLoader", "ModelSaver" ] +import torch + +from .base_loader import BaseLoader + class ModelLoader(BaseLoader): """ diff --git a/fastNLP/models/__init__.py b/fastNLP/models/__init__.py index f9ade153..14314049 100644 --- a/fastNLP/models/__init__.py +++ b/fastNLP/models/__init__.py @@ -7,15 +7,6 @@ fastNLP 在 :mod:`~fastNLP.models` 模块中内置了如 :class:`~fastNLP.models """ -from .base_model import BaseModel -from .bert import BertForMultipleChoice, BertForQuestionAnswering, BertForSequenceClassification, \ - BertForTokenClassification -from .biaffine_parser import BiaffineParser, GraphParser -from .cnn_text_classification import CNNText -from .sequence_labeling import SeqLabeling, AdvSeqLabel -from .snli import ESIM -from .star_transformer import StarTransEnc, STSeqCls, STNLICls, STSeqLabel - __all__ = [ "CNNText", @@ -32,3 +23,12 @@ __all__ = [ "BiaffineParser", "GraphParser" ] + +from .base_model import BaseModel +from .bert import BertForMultipleChoice, BertForQuestionAnswering, BertForSequenceClassification, \ + BertForTokenClassification +from .biaffine_parser import BiaffineParser, GraphParser +from .cnn_text_classification import CNNText +from .sequence_labeling import SeqLabeling, AdvSeqLabel +from .snli import ESIM +from .star_transformer import StarTransEnc, STSeqCls, STNLICls, STSeqLabel diff --git a/fastNLP/models/biaffine_parser.py b/fastNLP/models/biaffine_parser.py index 7f16202d..8533e7af 100644 --- a/fastNLP/models/biaffine_parser.py +++ b/fastNLP/models/biaffine_parser.py @@ -1,6 +1,11 @@ """ Biaffine Dependency Parser 的 Pytorch 实现. """ +__all__ = [ + "BiaffineParser", + "GraphParser" +] + import numpy as np import torch import torch.nn as nn @@ -19,11 +24,6 @@ from ..modules.utils import get_embeddings from .base_model import BaseModel from ..core.utils import seq_len_to_mask -__all__ = [ - "BiaffineParser", - "GraphParser" -] - def _mst(scores): """ diff --git a/fastNLP/models/cnn_text_classification.py b/fastNLP/models/cnn_text_classification.py index a9ccc568..3a71a80a 100644 --- a/fastNLP/models/cnn_text_classification.py +++ b/fastNLP/models/cnn_text_classification.py @@ -1,13 +1,13 @@ +__all__ = [ + "CNNText" +] + import torch import torch.nn as nn from ..core.const import Const as C from ..modules import encoder -__all__ = [ - "CNNText" -] - class CNNText(torch.nn.Module): """ diff --git a/fastNLP/models/enas_utils.py b/fastNLP/models/enas_utils.py index 68c170ed..4e402a9a 100644 --- a/fastNLP/models/enas_utils.py +++ b/fastNLP/models/enas_utils.py @@ -1,6 +1,5 @@ # Code Modified from https://github.com/carpedm20/ENAS-pytorch -from __future__ import print_function from collections import defaultdict import collections diff --git a/fastNLP/models/sequence_labeling.py b/fastNLP/models/sequence_labeling.py index 503c79ba..8e6a5db1 100644 --- a/fastNLP/models/sequence_labeling.py +++ b/fastNLP/models/sequence_labeling.py @@ -1,6 +1,11 @@ """ 本模块实现了两种序列标注模型 """ +__all__ = [ + "SeqLabeling", + "AdvSeqLabel" +] + import torch import torch.nn as nn @@ -10,11 +15,6 @@ from ..modules.decoder.crf import allowed_transitions from ..core.utils import seq_len_to_mask from ..core.const import Const as C -__all__ = [ - "SeqLabeling", - "AdvSeqLabel" -] - class SeqLabeling(BaseModel): """ diff --git a/fastNLP/models/snli.py b/fastNLP/models/snli.py index 606bcc42..395a9bbf 100644 --- a/fastNLP/models/snli.py +++ b/fastNLP/models/snli.py @@ -1,3 +1,7 @@ +__all__ = [ + "ESIM" +] + import torch import torch.nn as nn @@ -8,10 +12,6 @@ from ..modules import encoder as Encoder from ..modules import aggregator as Aggregator from ..core.utils import seq_len_to_mask -__all__ = [ - "ESIM" -] - my_inf = 10e12 diff --git a/fastNLP/models/star_transformer.py b/fastNLP/models/star_transformer.py index 2e55f7e4..c67e5938 100644 --- a/fastNLP/models/star_transformer.py +++ b/fastNLP/models/star_transformer.py @@ -1,6 +1,13 @@ """ Star-Transformer 的 Pytorch 实现。 """ +__all__ = [ + "StarTransEnc", + "STNLICls", + "STSeqCls", + "STSeqLabel", +] + import torch from torch import nn @@ -9,13 +16,6 @@ from ..core.utils import seq_len_to_mask from ..modules.utils import get_embeddings from ..core.const import Const -__all__ = [ - "StarTransEnc", - "STNLICls", - "STSeqCls", - "STSeqLabel", -] - class StarTransEnc(nn.Module): """ diff --git a/fastNLP/modules/__init__.py b/fastNLP/modules/__init__.py index cd54c8db..194fda4e 100644 --- a/fastNLP/modules/__init__.py +++ b/fastNLP/modules/__init__.py @@ -22,15 +22,6 @@ +-----------------------+-----------------------+-----------------------+ """ -from . import aggregator -from . import decoder -from . import encoder -from .aggregator import * -from .decoder import * -from .dropout import TimestepDropout -from .encoder import * -from .utils import get_embeddings - __all__ = [ # "BertModel", "ConvolutionCharEncoder", @@ -54,3 +45,12 @@ __all__ = [ "viterbi_decode", "allowed_transitions", ] + +from . import aggregator +from . import decoder +from . import encoder +from .aggregator import * +from .decoder import * +from .dropout import TimestepDropout +from .encoder import * +from .utils import get_embeddings diff --git a/fastNLP/modules/aggregator/__init__.py b/fastNLP/modules/aggregator/__init__.py index 117dad83..a82138e7 100644 --- a/fastNLP/modules/aggregator/__init__.py +++ b/fastNLP/modules/aggregator/__init__.py @@ -1,10 +1,3 @@ -from .pooling import MaxPool -from .pooling import MaxPoolWithMask -from .pooling import AvgPool -from .pooling import AvgPoolWithMask - -from .attention import MultiHeadAttention - __all__ = [ "MaxPool", "MaxPoolWithMask", @@ -12,3 +5,10 @@ __all__ = [ "MultiHeadAttention", ] + +from .pooling import MaxPool +from .pooling import MaxPoolWithMask +from .pooling import AvgPool +from .pooling import AvgPoolWithMask + +from .attention import MultiHeadAttention diff --git a/fastNLP/modules/aggregator/attention.py b/fastNLP/modules/aggregator/attention.py index a1a7fda8..4101b033 100644 --- a/fastNLP/modules/aggregator/attention.py +++ b/fastNLP/modules/aggregator/attention.py @@ -1,3 +1,7 @@ +__all__ = [ + "MultiHeadAttention" +] + import math import torch @@ -8,10 +12,6 @@ from ..dropout import TimestepDropout from ..utils import initial_parameter -__all__ = [ - "MultiHeadAttention" -] - class DotAttention(nn.Module): """ diff --git a/fastNLP/modules/aggregator/pooling.py b/fastNLP/modules/aggregator/pooling.py index be454d7b..51438aae 100644 --- a/fastNLP/modules/aggregator/pooling.py +++ b/fastNLP/modules/aggregator/pooling.py @@ -1,4 +1,8 @@ -__all__ = ["MaxPool", "MaxPoolWithMask", "AvgPool"] +__all__ = [ + "MaxPool", + "MaxPoolWithMask", + "AvgPool" +] import torch import torch.nn as nn @@ -16,6 +20,7 @@ class MaxPool(nn.Module): :param kernel_size: max pooling的窗口大小，默认为tensor最后k维，其中k为dimension :param ceil_mode: """ + def __init__(self, stride=None, padding=0, dilation=1, dimension=1, kernel_size=None, ceil_mode=False): super(MaxPool, self).__init__() @@ -125,7 +130,7 @@ class AvgPoolWithMask(nn.Module): 给定形如[batch_size, max_len, hidden_size]的输入，在最后一维进行avg pooling. 输出为[batch_size, hidden_size], pooling 的时候只会考虑mask为1的位置 """ - + def __init__(self): super(AvgPoolWithMask, self).__init__() self.inf = 10e12 diff --git a/fastNLP/modules/decoder/__init__.py b/fastNLP/modules/decoder/__init__.py index 5df48c43..664618b2 100644 --- a/fastNLP/modules/decoder/__init__.py +++ b/fastNLP/modules/decoder/__init__.py @@ -1,11 +1,11 @@ -from .crf import ConditionalRandomField -from .mlp import MLP -from .utils import viterbi_decode -from .crf import allowed_transitions - __all__ = [ "MLP", "ConditionalRandomField", "viterbi_decode", "allowed_transitions" ] + +from .crf import ConditionalRandomField +from .mlp import MLP +from .utils import viterbi_decode +from .crf import allowed_transitions diff --git a/fastNLP/modules/decoder/crf.py b/fastNLP/modules/decoder/crf.py index 130ed40e..beb2b9be 100644 --- a/fastNLP/modules/decoder/crf.py +++ b/fastNLP/modules/decoder/crf.py @@ -1,13 +1,13 @@ -import torch -from torch import nn - -from ..utils import initial_parameter - __all__ = [ "ConditionalRandomField", "allowed_transitions" ] +import torch +from torch import nn + +from ..utils import initial_parameter + def allowed_transitions(id2target, encoding_type='bio', include_start_end=True): """ diff --git a/fastNLP/modules/decoder/mlp.py b/fastNLP/modules/decoder/mlp.py index 27019432..c1579224 100644 --- a/fastNLP/modules/decoder/mlp.py +++ b/fastNLP/modules/decoder/mlp.py @@ -1,12 +1,12 @@ +__all__ = [ + "MLP" +] + import torch import torch.nn as nn from ..utils import initial_parameter -__all__ = [ - "MLP" -] - class MLP(nn.Module): """ diff --git a/fastNLP/modules/decoder/utils.py b/fastNLP/modules/decoder/utils.py index 434873c7..249f3ff6 100644 --- a/fastNLP/modules/decoder/utils.py +++ b/fastNLP/modules/decoder/utils.py @@ -1,8 +1,7 @@ -import torch - __all__ = [ "viterbi_decode" ] +import torch def viterbi_decode(logits, transitions, mask=None, unpad=False): diff --git a/fastNLP/modules/dropout.py b/fastNLP/modules/dropout.py index 34b426fd..1363165c 100644 --- a/fastNLP/modules/dropout.py +++ b/fastNLP/modules/dropout.py @@ -1,6 +1,8 @@ -import torch __all__ = [] +import torch + + class TimestepDropout(torch.nn.Dropout): """ 别名：:class:`fastNLP.modules.TimestepDropout` @@ -8,7 +10,7 @@ class TimestepDropout(torch.nn.Dropout): 接受的参数shape为``[batch_size, num_timesteps, embedding_dim)]`` 使用同一个mask(shape为``(batch_size, embedding_dim)``) 在每个timestamp上做dropout。 """ - + def forward(self, x): dropout_mask = x.new_ones(x.shape[0], x.shape[-1]) torch.nn.functional.dropout(dropout_mask, self.p, self.training, inplace=True) diff --git a/fastNLP/modules/encoder/__init__.py b/fastNLP/modules/encoder/__init__.py index 3d65867a..bdc4cbf3 100644 --- a/fastNLP/modules/encoder/__init__.py +++ b/fastNLP/modules/encoder/__init__.py @@ -1,12 +1,3 @@ -from .bert import BertModel -from .char_encoder import ConvolutionCharEncoder, LSTMCharEncoder -from .conv_maxpool import ConvMaxpool -from .embedding import Embedding -from .lstm import LSTM -from .star_transformer import StarTransformer -from .transformer import TransformerEncoder -from .variational_rnn import VarRNN, VarLSTM, VarGRU - __all__ = [ # "BertModel", @@ -27,3 +18,11 @@ __all__ = [ "VarLSTM", "VarGRU" ] +from .bert import BertModel +from .char_encoder import ConvolutionCharEncoder, LSTMCharEncoder +from .conv_maxpool import ConvMaxpool +from .embedding import Embedding +from .lstm import LSTM +from .star_transformer import StarTransformer +from .transformer import TransformerEncoder +from .variational_rnn import VarRNN, VarLSTM, VarGRU diff --git a/fastNLP/modules/encoder/char_encoder.py b/fastNLP/modules/encoder/char_encoder.py index 8aefd284..481ad7ad 100644 --- a/fastNLP/modules/encoder/char_encoder.py +++ b/fastNLP/modules/encoder/char_encoder.py @@ -1,12 +1,11 @@ -import torch -import torch.nn as nn - -from ..utils import initial_parameter - __all__ = [ "ConvolutionCharEncoder", "LSTMCharEncoder" ] +import torch +import torch.nn as nn + +from ..utils import initial_parameter # from torch.nn.init import xavier_uniform diff --git a/fastNLP/modules/encoder/conv_maxpool.py b/fastNLP/modules/encoder/conv_maxpool.py index 5e714e88..ae6bea04 100644 --- a/fastNLP/modules/encoder/conv_maxpool.py +++ b/fastNLP/modules/encoder/conv_maxpool.py @@ -1,13 +1,12 @@ +__all__ = [ + "ConvMaxpool" +] import torch import torch.nn as nn import torch.nn.functional as F from ..utils import initial_parameter -__all__ = [ - "ConvMaxpool" -] - class ConvMaxpool(nn.Module): """ diff --git a/fastNLP/modules/encoder/embedding.py b/fastNLP/modules/encoder/embedding.py index 9fa89e7f..f3c1f475 100644 --- a/fastNLP/modules/encoder/embedding.py +++ b/fastNLP/modules/encoder/embedding.py @@ -1,9 +1,8 @@ -import torch.nn as nn -from ..utils import get_embeddings - __all__ = [ "Embedding" ] +import torch.nn as nn +from ..utils import get_embeddings class Embedding(nn.Embedding): diff --git a/fastNLP/modules/encoder/lstm.py b/fastNLP/modules/encoder/lstm.py index bc9cb155..b4f960e7 100644 --- a/fastNLP/modules/encoder/lstm.py +++ b/fastNLP/modules/encoder/lstm.py @@ -2,16 +2,16 @@ 轻量封装的 Pytorch LSTM 模块. 可在 forward 时传入序列的长度, 自动对padding做合适的处理. """ +__all__ = [ + "LSTM" +] + import torch import torch.nn as nn import torch.nn.utils.rnn as rnn from ..utils import initial_parameter -__all__ = [ - "LSTM" -] - class LSTM(nn.Module): """ diff --git a/fastNLP/modules/encoder/star_transformer.py b/fastNLP/modules/encoder/star_transformer.py index 677af48a..5a7f3d67 100644 --- a/fastNLP/modules/encoder/star_transformer.py +++ b/fastNLP/modules/encoder/star_transformer.py @@ -1,15 +1,15 @@ """ Star-Transformer 的encoder部分的 Pytorch 实现 """ +__all__ = [ + "StarTransformer" +] + import numpy as NP import torch from torch import nn from torch.nn import functional as F -__all__ = [ - "StarTransformer" -] - class StarTransformer(nn.Module): """ diff --git a/fastNLP/modules/encoder/transformer.py b/fastNLP/modules/encoder/transformer.py index 2532d90a..698ff95c 100644 --- a/fastNLP/modules/encoder/transformer.py +++ b/fastNLP/modules/encoder/transformer.py @@ -1,12 +1,11 @@ +__all__ = [ + "TransformerEncoder" +] from torch import nn from ..aggregator.attention import MultiHeadAttention from ..dropout import TimestepDropout -__all__ = [ - "TransformerEncoder" -] - class TransformerEncoder(nn.Module): """ diff --git a/fastNLP/modules/encoder/variational_rnn.py b/fastNLP/modules/encoder/variational_rnn.py index 753741de..29b728e5 100644 --- a/fastNLP/modules/encoder/variational_rnn.py +++ b/fastNLP/modules/encoder/variational_rnn.py @@ -1,6 +1,12 @@ """ Variational RNN 的 Pytorch 实现 """ +__all__ = [ + "VarRNN", + "VarLSTM", + "VarGRU" +] + import torch import torch.nn as nn from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence, pad_packed_sequence @@ -17,25 +23,19 @@ except ImportError: from ..utils import initial_parameter -__all__ = [ - "VarRNN", - "VarLSTM", - "VarGRU" -] - class VarRnnCellWrapper(nn.Module): """ Wrapper for normal RNN Cells, make it support variational dropout """ - + def __init__(self, cell, hidden_size, input_p, hidden_p): super(VarRnnCellWrapper, self).__init__() self.cell = cell self.hidden_size = hidden_size self.input_p = input_p self.hidden_p = hidden_p - + def forward(self, input_x, hidden, mask_x, mask_h, is_reversed=False): """ :param PackedSequence input_x: [seq_len, batch_size, input_size] @@ -47,13 +47,13 @@ class VarRnnCellWrapper(nn.Module): hidden: for LSTM, tuple of (h_n, c_n), [batch_size, hidden_size] for other RNN, h_n, [batch_size, hidden_size] """ - + def get_hi(hi, h0, size): h0_size = size - hi.size(0) if h0_size > 0: return torch.cat([hi, h0[:h0_size]], dim=0) return hi[:size] - + is_lstm = isinstance(hidden, tuple) input, batch_sizes = input_x.data, input_x.batch_sizes output = [] @@ -64,7 +64,7 @@ class VarRnnCellWrapper(nn.Module): else: batch_iter = batch_sizes idx = 0 - + if is_lstm: hn = (hidden[0].clone(), hidden[1].clone()) else: @@ -91,7 +91,7 @@ class VarRnnCellWrapper(nn.Module): hi = cell(input_i, hi) hn[:size] = hi output.append(hi) - + if is_reversed: output = list(reversed(output)) output = torch.cat(output, dim=0) @@ -117,7 +117,7 @@ class VarRNNBase(nn.Module): :param hidden_dropout: 对每个隐状态的dropout概率. Default: 0 :param bidirectional: 若为 ``True``, 使用双向的RNN. Default: ``False`` """ - + def __init__(self, mode, Cell, input_size, hidden_size, num_layers=1, bias=True, batch_first=False, input_dropout=0, hidden_dropout=0, bidirectional=False): @@ -141,7 +141,7 @@ class VarRNNBase(nn.Module): cell, self.hidden_size, input_dropout, hidden_dropout)) initial_parameter(self) self.is_lstm = (self.mode == "LSTM") - + def _forward_one(self, n_layer, n_direction, input, hx, mask_x, mask_h): is_lstm = self.is_lstm idx = self.num_directions * n_layer + n_direction @@ -150,7 +150,7 @@ class VarRNNBase(nn.Module): output_x, hidden_x = cell( input, hi, mask_x, mask_h, is_reversed=(n_direction == 1)) return output_x, hidden_x - + def forward(self, x, hx=None): """ @@ -170,13 +170,13 @@ class VarRNNBase(nn.Module): else: max_batch_size = int(x.batch_sizes[0]) x, batch_sizes = x.data, x.batch_sizes - + if hx is None: hx = x.new_zeros(self.num_layers * self.num_directions, max_batch_size, self.hidden_size, requires_grad=True) if is_lstm: hx = (hx, hx.new_zeros(hx.size(), requires_grad=True)) - + mask_x = x.new_ones((max_batch_size, self.input_size)) mask_out = x.new_ones( (max_batch_size, self.hidden_size * self.num_directions)) @@ -185,7 +185,7 @@ class VarRNNBase(nn.Module): training=self.training, inplace=True) nn.functional.dropout(mask_out, p=self.hidden_dropout, training=self.training, inplace=True) - + hidden = x.new_zeros( (self.num_layers * self.num_directions, max_batch_size, self.hidden_size)) if is_lstm: @@ -207,16 +207,16 @@ class VarRNNBase(nn.Module): else: hidden[idx] = hidden_x x = torch.cat(output_list, dim=-1) - + if is_lstm: hidden = (hidden, cellstate) - + if is_packed: output = PackedSequence(x, batch_sizes) else: x = PackedSequence(x, batch_sizes) output, _ = pad_packed_sequence(x, batch_first=self.batch_first) - + return output, hidden @@ -236,11 +236,11 @@ class VarLSTM(VarRNNBase): :param hidden_dropout: 对每个隐状态的dropout概率. Default: 0 :param bidirectional: 若为 ``True``, 使用双向的LSTM. Default: ``False`` """ - + def __init__(self, *args, **kwargs): super(VarLSTM, self).__init__( mode="LSTM", Cell=nn.LSTMCell, *args, **kwargs) - + def forward(self, x, hx=None): return super(VarLSTM, self).forward(x, hx) @@ -261,11 +261,11 @@ class VarRNN(VarRNNBase): :param hidden_dropout: 对每个隐状态的dropout概率. Default: 0 :param bidirectional: 若为 ``True``, 使用双向的RNN. Default: ``False`` """ - + def __init__(self, *args, **kwargs): super(VarRNN, self).__init__( mode="RNN", Cell=nn.RNNCell, *args, **kwargs) - + def forward(self, x, hx=None): return super(VarRNN, self).forward(x, hx) @@ -286,10 +286,10 @@ class VarGRU(VarRNNBase): :param hidden_dropout: 对每个隐状态的dropout概率. Default: 0 :param bidirectional: 若为 ``True``, 使用双向的GRU. Default: ``False`` """ - + def __init__(self, *args, **kwargs): super(VarGRU, self).__init__( mode="GRU", Cell=nn.GRUCell, *args, **kwargs) - + def forward(self, x, hx=None): return super(VarGRU, self).forward(x, hx) diff --git a/fastNLP/modules/utils.py b/fastNLP/modules/utils.py index 0aba7e62..c9a1f682 100644 --- a/fastNLP/modules/utils.py +++ b/fastNLP/modules/utils.py @@ -1,5 +1,5 @@ from functools import reduce -from collections import OrderedDict + import numpy as np import torch import torch.nn as nn