From ea6bc38a619d5b140c83f4fd0c66a5952e1d3b43 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=B5=85=E6=A2=A6?= Date: Sun, 4 Apr 2021 16:08:32 +0800 Subject: [PATCH] update docs update docs --- .github/workflows/ci.yml | 2 +- README.md | 10 +++++----- deepctr_torch/__init__.py | 2 +- deepctr_torch/layers/activation.py | 2 +- deepctr_torch/layers/interaction.py | 2 +- deepctr_torch/models/autoint.py | 2 +- deepctr_torch/models/basemodel.py | 4 ++-- deepctr_torch/models/dcn.py | 2 +- deepctr_torch/models/dcnmix.py | 2 +- deepctr_torch/models/deepfm.py | 2 +- deepctr_torch/models/difm.py | 8 ++++---- deepctr_torch/models/fibinet.py | 2 +- deepctr_torch/models/ifm.py | 6 +++--- deepctr_torch/models/mlr.py | 2 +- deepctr_torch/models/nfm.py | 2 +- deepctr_torch/models/onn.py | 2 +- deepctr_torch/models/pnn.py | 2 +- deepctr_torch/models/wdl.py | 2 +- deepctr_torch/models/xdeepfm.py | 2 +- docs/pics/DIFM.png | Bin 0 -> 101810 bytes docs/pics/IFM.png | Bin 0 -> 60365 bytes docs/source/FAQ.md | 2 +- docs/source/Features.md | 21 +++++++++++++++++++++ docs/source/History.md | 1 + docs/source/Models.rst | 2 ++ docs/source/conf.py | 2 +- docs/source/deepctr_torch.models.difm.rst | 7 +++++++ docs/source/deepctr_torch.models.ifm.rst | 7 +++++++ docs/source/deepctr_torch.models.rst | 3 +++ docs/source/index.rst | 5 ++--- setup.py | 2 +- tests/utils.py | 2 +- 32 files changed, 76 insertions(+), 36 deletions(-) create mode 100644 docs/pics/DIFM.png create mode 100644 docs/pics/IFM.png create mode 100644 docs/source/deepctr_torch.models.difm.rst create mode 100644 docs/source/deepctr_torch.models.ifm.rst diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 7685cfb2..fc3cdae4 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -18,7 +18,7 @@ jobs: strategy: matrix: python-version: [3.6,3.7] - torch-version: [1.1.0,1.2.0,1.3.0,1.4.0,1.5.0,1.6.0,1.7.0] + torch-version: [1.1.0,1.2.0,1.3.0,1.4.0,1.5.0,1.6.0,1.7.0,1.8.1] # exclude: # - python-version: 3.5 diff --git a/README.md b/README.md index 3b7ff5ca..a50aeb93 100644 --- a/README.md +++ b/README.md @@ -84,6 +84,11 @@ Let's [**Get Started!**](https://deepctr-torch.readthedocs.io/en/latest/Quick-St ​ Shen Weichen

Core Dev
Zhejiang Unversity

​ + + ​ pic
+ ​ Zan Shuxun +

Core Dev
Beijing University
of Posts and
Telecommunications

​ + pic
Wang Ze ​ @@ -94,11 +99,6 @@ Let's [**Get Started!**](https://deepctr-torch.readthedocs.io/en/latest/Quick-St Zhang Wutong

Core Dev
Beijing University
of Posts and
Telecommunications

​ - - ​ pic
- ​ Zan Shuxun -

Core Dev
Beijing University
of Posts and
Telecommunications

​ - ​ pic
Zhang Yuefeng diff --git a/deepctr_torch/__init__.py b/deepctr_torch/__init__.py index b3ae817b..b780468d 100644 --- a/deepctr_torch/__init__.py +++ b/deepctr_torch/__init__.py @@ -2,5 +2,5 @@ from . import models from .utils import check_version -__version__ = '0.2.5' +__version__ = '0.2.6' check_version(__version__) \ No newline at end of file diff --git a/deepctr_torch/layers/activation.py b/deepctr_torch/layers/activation.py index 4ba8758e..01624a05 100644 --- a/deepctr_torch/layers/activation.py +++ b/deepctr_torch/layers/activation.py @@ -12,7 +12,7 @@ class Dice(nn.Module): Output shape: - Same shape as input. - + References - [Zhou G, Zhu X, Song C, et al. Deep interest network for click-through rate prediction[C]//Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. ACM, 2018: 1059-1068.](https://arxiv.org/pdf/1706.06978.pdf) - https://github.com/zhougr1993/DeepInterestNetwork, https://github.com/fanoping/DIN-pytorch diff --git a/deepctr_torch/layers/interaction.py b/deepctr_torch/layers/interaction.py index ff9fd9bb..edbfa88b 100644 --- a/deepctr_torch/layers/interaction.py +++ b/deepctr_torch/layers/interaction.py @@ -126,7 +126,7 @@ def __init__(self, filed_size, embedding_size, bilinear_type="interaction", seed self.bilinear = nn.Linear( embedding_size, embedding_size, bias=False) elif self.bilinear_type == "each": - for i in range(filed_size): + for _ in range(filed_size): self.bilinear.append( nn.Linear(embedding_size, embedding_size, bias=False)) elif self.bilinear_type == "interaction": diff --git a/deepctr_torch/models/autoint.py b/deepctr_torch/models/autoint.py index 0465707f..c39effb4 100644 --- a/deepctr_torch/models/autoint.py +++ b/deepctr_torch/models/autoint.py @@ -34,7 +34,7 @@ class AutoInt(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, dnn_feature_columns, att_layer_num=3, att_embedding_size=8, att_head_num=2, diff --git a/deepctr_torch/models/basemodel.py b/deepctr_torch/models/basemodel.py index d09de931..bb9d1f7a 100644 --- a/deepctr_torch/models/basemodel.py +++ b/deepctr_torch/models/basemodel.py @@ -234,7 +234,7 @@ def fit(self, x=None, y=None, batch_size=None, epochs=1, verbose=1, initial_epoc train_result = {} try: with tqdm(enumerate(train_loader), disable=verbose != 1) as t: - for index, (x_train, y_train) in t: + for _, (x_train, y_train) in t: x = x_train.to(self.device).float() y = y_train.to(self.device).float() @@ -333,7 +333,7 @@ def predict(self, x, batch_size=256): pred_ans = [] with torch.no_grad(): - for index, x_test in enumerate(test_loader): + for _, x_test in enumerate(test_loader): x = x_test[0].to(self.device).float() y_pred = model(x).cpu().data.numpy() # .squeeze() diff --git a/deepctr_torch/models/dcn.py b/deepctr_torch/models/dcn.py index 5a6a3fb9..f5ef03bf 100644 --- a/deepctr_torch/models/dcn.py +++ b/deepctr_torch/models/dcn.py @@ -38,7 +38,7 @@ class DCN(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, dnn_feature_columns, cross_num=2, cross_parameterization='vector', diff --git a/deepctr_torch/models/dcnmix.py b/deepctr_torch/models/dcnmix.py index 6796127d..9b0e97d4 100644 --- a/deepctr_torch/models/dcnmix.py +++ b/deepctr_torch/models/dcnmix.py @@ -38,7 +38,7 @@ class DCNMix(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, diff --git a/deepctr_torch/models/deepfm.py b/deepctr_torch/models/deepfm.py index c76ade03..7f90faf7 100644 --- a/deepctr_torch/models/deepfm.py +++ b/deepctr_torch/models/deepfm.py @@ -32,7 +32,7 @@ class DeepFM(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, diff --git a/deepctr_torch/models/difm.py b/deepctr_torch/models/difm.py index 1dffd40a..13a3aaab 100644 --- a/deepctr_torch/models/difm.py +++ b/deepctr_torch/models/difm.py @@ -3,7 +3,7 @@ Author: zanshuxun, zanshuxun@aliyun.com Reference: - Lu W, Yu Y, Chang Y, et al. A Dual Input-aware Factorization Machine for CTR Prediction[C]//IJCAI. 2020: 3139-3145. + [1] Lu W, Yu Y, Chang Y, et al. A Dual Input-aware Factorization Machine for CTR Prediction[C]//IJCAI. 2020: 3139-3145.(https://www.ijcai.org/Proceedings/2020/0434.pdf) """ import torch import torch.nn as nn @@ -29,9 +29,9 @@ class DIFM(BaseModel): :param dnn_use_bn: bool. Whether use BatchNormalization before activation or not in DNN :param task: str, ``"binary"`` for binary logloss or ``"regression"`` for regression loss :param device: str, ``"cpu"`` or ``"cuda:0"`` - :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. + :param gpus: list of int or torch.device for multiple gpus. If None, run on ``device`` . ``gpus[0]`` should be the same gpu with ``device`` . :return: A PyTorch model instance. - + """ def __init__(self, @@ -79,7 +79,7 @@ def __init__(self, self.to(device) def forward(self, X): - sparse_embedding_list, dense_value_list = self.input_from_feature_columns(X, self.dnn_feature_columns, + sparse_embedding_list, _ = self.input_from_feature_columns(X, self.dnn_feature_columns, self.embedding_dict) if not len(sparse_embedding_list) > 0: raise ValueError("there are no sparse features") diff --git a/deepctr_torch/models/fibinet.py b/deepctr_torch/models/fibinet.py index 86683789..67ec4783 100644 --- a/deepctr_torch/models/fibinet.py +++ b/deepctr_torch/models/fibinet.py @@ -33,7 +33,7 @@ class FiBiNET(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, dnn_feature_columns, bilinear_type='interaction', diff --git a/deepctr_torch/models/ifm.py b/deepctr_torch/models/ifm.py index a4794664..4f057833 100644 --- a/deepctr_torch/models/ifm.py +++ b/deepctr_torch/models/ifm.py @@ -3,7 +3,7 @@ Author: zanshuxun, zanshuxun@aliyun.com Reference: - Yu Y, Wang Z, Yuan B. An Input-aware Factorization Machine for Sparse Prediction[C]//IJCAI. 2019: 1466-1472. + [1] Yu Y, Wang Z, Yuan B. An Input-aware Factorization Machine for Sparse Prediction[C]//IJCAI. 2019: 1466-1472.(https://www.ijcai.org/Proceedings/2019/0203.pdf) """ import torch import torch.nn as nn @@ -29,9 +29,9 @@ class IFM(BaseModel): :param dnn_use_bn: bool. Whether use BatchNormalization before activation or not in DNN :param task: str, ``"binary"`` for binary logloss or ``"regression"`` for regression loss :param device: str, ``"cpu"`` or ``"cuda:0"`` - :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. + :param gpus: list of int or torch.device for multiple gpus. If None, run on ``device`` . ``gpus[0]`` should be the same gpu with ``device`` . :return: A PyTorch model instance. - + """ def __init__(self, diff --git a/deepctr_torch/models/mlr.py b/deepctr_torch/models/mlr.py index 9a470899..8cb60090 100644 --- a/deepctr_torch/models/mlr.py +++ b/deepctr_torch/models/mlr.py @@ -28,7 +28,7 @@ class MLR(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, region_feature_columns, base_feature_columns=None, bias_feature_columns=None, diff --git a/deepctr_torch/models/nfm.py b/deepctr_torch/models/nfm.py index d7781823..f01613c7 100644 --- a/deepctr_torch/models/nfm.py +++ b/deepctr_torch/models/nfm.py @@ -31,7 +31,7 @@ class NFM(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, diff --git a/deepctr_torch/models/onn.py b/deepctr_torch/models/onn.py index 49663512..49f59cca 100644 --- a/deepctr_torch/models/onn.py +++ b/deepctr_torch/models/onn.py @@ -52,7 +52,7 @@ class ONN(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, dnn_feature_columns, diff --git a/deepctr_torch/models/pnn.py b/deepctr_torch/models/pnn.py index 54defffa..d72b2d5c 100644 --- a/deepctr_torch/models/pnn.py +++ b/deepctr_torch/models/pnn.py @@ -32,7 +32,7 @@ class PNN(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, dnn_feature_columns, dnn_hidden_units=(128, 128), l2_reg_embedding=1e-5, l2_reg_dnn=0, diff --git a/deepctr_torch/models/wdl.py b/deepctr_torch/models/wdl.py index 2dd9c656..6016eb0a 100644 --- a/deepctr_torch/models/wdl.py +++ b/deepctr_torch/models/wdl.py @@ -30,7 +30,7 @@ class WDL(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, diff --git a/deepctr_torch/models/xdeepfm.py b/deepctr_torch/models/xdeepfm.py index 5506eeb7..7d5efa01 100644 --- a/deepctr_torch/models/xdeepfm.py +++ b/deepctr_torch/models/xdeepfm.py @@ -36,7 +36,7 @@ class xDeepFM(BaseModel): :param device: str, ``"cpu"`` or ``"cuda:0"`` :param gpus: list of int or torch.device for multiple gpus. If None, run on `device`. `gpus[0]` should be the same gpu with `device`. :return: A PyTorch model instance. - + """ def __init__(self, linear_feature_columns, dnn_feature_columns, dnn_hidden_units=(256, 256), diff --git a/docs/pics/DIFM.png b/docs/pics/DIFM.png new file mode 100644 index 0000000000000000000000000000000000000000..76a983b2b29a7ab5afd89974dc3541ef8caaab8b GIT binary patch literal 101810 zcmdqIWm}t3vj*Ch7D{nwp*R$GCpbllOY!3F5ZtW=ic4_`Qi8i%AW$^L-QC^YPw2b% zx!(QZ{DJc!SDqwK=2v|vzT94Kqep~$Mk>miX0REVPPSCIfLv6 zWkaW+ct}%I+L5-41i~oGS z=*$%LFL=HPyjGFI{P28%>Guv9{O@8_kz7Re`5V!DI?9lD&le%WKVK{TlW~&&i;Vt1 z!ruS?L70fED|b&%4<$8qY-*~Efs*DMVC5T9ccb1w_Tf8r@GmF{qaqgmf7| zTn|K(nA6#|XA=g~`Hja*39}_5jmEko=UaS0)6?G;#-INU`}gmVhzQgSL9cHAo3ovT zzCfkK08KVKJ|sZ-YVU~dbOvwW!A!@zfX^?K;JRw-1!dfUw9a2Y9@q}1qUAx{t9yIl z64@gIO3!m-44($2zlCihb911Zv#pVOH$~e9)quR}gD?IW3)G8S$SG~W^+1mn`W+UX z&=c>Fr!|m39dE};I$<(5kP<=euF_#m;u8ghixVDvd_rmP$$VECAOC(ZQ+Q}u1R+Jp zmvXA~66gAy+w#Yt-RmKJhM6o9NGdD04!en4zaCCBV$)tVu 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+75,5 @@ model = DeepFM(...,device=device) ## 5. How to run the demo with multiple GPUs ? ```python - model = DeepFM(..., device=device, gpus=[0, 1]) +model = DeepFM(..., device=device, gpus=[0, 1]) ``` diff --git a/docs/source/Features.md b/docs/source/Features.md index cce54b89..2aaf6787 100644 --- a/docs/source/Features.md +++ b/docs/source/Features.md @@ -241,6 +241,27 @@ Feature Importance and Bilinear feature Interaction NETwork is proposed to dynam [Huang T, Zhang Z, Zhang J. FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction[J]. arXiv preprint arXiv:1905.09433, 2019.](https://arxiv.org/pdf/1905.09433.pdf) +### IFM(Input-aware Factorization Machine) + +Input-aware Factorization Machine (IFM) learns a unique input-aware factor for the same feature in different instances via a neural network. + +[**IFM Model API**](./deepctr_torch.models.ifm.html) + +![IFM](../pics/IFM.png) + +[Yu Y, Wang Z, Yuan B. An Input-aware Factorization Machine for Sparse Prediction[C]//IJCAI. 2019: 1466-1472.](https://www.ijcai.org/Proceedings/2019/0203.pdf) + +### DIFM(Dual Input-aware Factorization Machine) + +Dual Inputaware Factorization Machines (DIFM) can adaptively reweight the original feature representations at the bit-wise and vector-wise levels simultaneously.Furthermore, DIFMs strategically integrate various components including Multi-Head Self-Attention, Residual Networks and DNNs into a unified end-to-end model. + +[**DFM Model API**](./deepctr_torch.models.difm.html) + +![DIFM](../pics/DIFM.png) + +[Lu W, Yu Y, Chang Y, et al. A Dual Input-aware Factorization Machine for CTR Prediction[C]//IJCAI. 2020: 3139-3145.](https://www.ijcai.org/Proceedings/2020/0434.pdf) + + ## Layers diff --git a/docs/source/History.md b/docs/source/History.md index 78f4b463..eef2f07b 100644 --- a/docs/source/History.md +++ b/docs/source/History.md @@ -1,4 +1,5 @@ # History +- 04/04/2021 : [v0.2.6](https://github.com/shenweichen/DeepCTR-Torch/releases/tag/v0.2.6) released.Add add [IFM](./Features.html#ifm-input-aware-factorization-machine) and [DIFM](./Features.html#difm-dual-input-aware-factorization-machine);Support multi-gpus running([example](./FAQ.html#how-to-run-the-demo-with-multiple-gpus)). - 02/12/2021 : [v0.2.5](https://github.com/shenweichen/DeepCTR-Torch/releases/tag/v0.2.5) released.Fix bug in DCN-M. - 12/05/2020 : [v0.2.4](https://github.com/shenweichen/DeepCTR-Torch/releases/tag/v0.2.4) released.Imporve compatibility & fix issues.Add History callback.([example](https://deepctr-torch.readthedocs.io/en/latest/FAQ.html#set-learning-rate-and-use-earlystopping)). - 10/18/2020 : [v0.2.3](https://github.com/shenweichen/DeepCTR-Torch/releases/tag/v0.2.3) released.Add [DCN-M](./Features.html#dcn-deep-cross-network)&[DCN-Mix](./Features.html#dcn-mix-improved-deep-cross-network-with-mix-of-experts-and-matrix-kernel).Add EarlyStopping and ModelCheckpoint callbacks([example](https://deepctr-torch.readthedocs.io/en/latest/FAQ.html#set-learning-rate-and-use-earlystopping)). diff --git a/docs/source/Models.rst b/docs/source/Models.rst index 52d96c28..a5eeb102 100644 --- a/docs/source/Models.rst +++ b/docs/source/Models.rst @@ -21,3 +21,5 @@ DeepCTR-Torch Models API ONN FGCNN FiBiNET + IFM + DIFM \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py index 1dd328ae..d43d0eea 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -26,7 +26,7 @@ # The short X.Y version version = '' # The full version, including alpha/beta/rc tags -release = '0.2.5' +release = '0.2.6' # -- General configuration --------------------------------------------------- diff --git a/docs/source/deepctr_torch.models.difm.rst b/docs/source/deepctr_torch.models.difm.rst new file mode 100644 index 00000000..ae16a5b7 --- /dev/null +++ b/docs/source/deepctr_torch.models.difm.rst @@ -0,0 +1,7 @@ +deepctr\_torch.models.difm module +================================ + +.. automodule:: deepctr_torch.models.difm + :members: + :no-undoc-members: + :no-show-inheritance: diff --git a/docs/source/deepctr_torch.models.ifm.rst b/docs/source/deepctr_torch.models.ifm.rst new file mode 100644 index 00000000..e625757b --- /dev/null +++ b/docs/source/deepctr_torch.models.ifm.rst @@ -0,0 +1,7 @@ +deepctr\_torch.models.ifm module +================================ + +.. automodule:: deepctr_torch.models.ifm + :members: + :no-undoc-members: + :no-show-inheritance: diff --git a/docs/source/deepctr_torch.models.rst b/docs/source/deepctr_torch.models.rst index 25041a55..599710b6 100644 --- a/docs/source/deepctr_torch.models.rst +++ b/docs/source/deepctr_torch.models.rst @@ -10,6 +10,7 @@ Submodules deepctr_torch.models.autoint deepctr_torch.models.basemodel deepctr_torch.models.dcn + deepctr_torch.models.dcnmix deepctr_torch.models.deepfm deepctr_torch.models.fibinet deepctr_torch.models.mlr @@ -20,6 +21,8 @@ Submodules deepctr_torch.models.xdeepfm deepctr_torch.models.din deepctr_torch.models.dien + deepctr_torch.models.ifm + deepctr_torch.models.difm Module contents --------------- diff --git a/docs/source/index.rst b/docs/source/index.rst index 2205e11d..bc4d2b1d 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -34,13 +34,12 @@ You can read the latest code at https://github.com/shenweichen/DeepCTR-Torch and News ----- +04/04/2021 : Add `IFM <./Features.html#ifm-input-aware-factorization-machine>`_ and `DIFM <./Features.html#difm-dual-input-aware-factorization-machine>`_ . Support multi-gpus running(`example <./FAQ.html#how-to-run-the-demo-with-multiple-gpus>`_). `Changelog `_ + 02/12/2021 : Fix bug in DCN-M. `Changelog `_ 12/05/2020 : Imporve compatibility & fix issues.Add History callback(`example `_). `Changelog `_ -10/18/2020 : Add `DCN-M <./Features.html#dcn-deep-cross-network>`_ and `DCN-Mix <./Features.html#dcn-mix-improved-deep-cross-network-with-mix-of-experts-and-matrix-kernel>`_ . Add EarlyStopping and ModelCheckpoint callbacks(`example `_). `Changelog `_ - - DisscussionGroup ----------------------- diff --git a/setup.py b/setup.py index 4d77342e..7060df42 100644 --- a/setup.py +++ b/setup.py @@ -9,7 +9,7 @@ setuptools.setup( name="deepctr-torch", - version="0.2.5", + version="0.2.6", author="Weichen Shen", author_email="weichenswc@163.com", description="Easy-to-use,Modular and Extendible package of deep learning based CTR(Click Through Rate) prediction models with PyTorch", diff --git a/tests/utils.py b/tests/utils.py index d8a8d6cb..4c79631e 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -70,7 +70,7 @@ def layer_test(layer_cls, kwargs = {}, input_shape=None, input_dtype=torch.float32, input_data=None, expected_output=None, expected_output_shape=None, expected_output_dtype=None, fixed_batch_size=False): '''check layer is valid or not - + :param layer_cls: :param input_shape: :param input_dtype: