diff --git a/qlib/contrib/model/pytorch_alstm.py b/qlib/contrib/model/pytorch_alstm.py index 3c008ae9a..b4fbbd504 100644 --- a/qlib/contrib/model/pytorch_alstm.py +++ b/qlib/contrib/model/pytorch_alstm.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_alstm_ts.py b/qlib/contrib/model/pytorch_alstm_ts.py index eb6e856ef..87ebb489b 100644 --- a/qlib/contrib/model/pytorch_alstm_ts.py +++ b/qlib/contrib/model/pytorch_alstm_ts.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_gats.py b/qlib/contrib/model/pytorch_gats.py index 4edbc8bcf..9a077b736 100644 --- a/qlib/contrib/model/pytorch_gats.py +++ b/qlib/contrib/model/pytorch_gats.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_gats_ts.py b/qlib/contrib/model/pytorch_gats_ts.py index dd83c00f9..35fd95ab5 100644 --- a/qlib/contrib/model/pytorch_gats_ts.py +++ b/qlib/contrib/model/pytorch_gats_ts.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py index 0070d1811..8b59e0ee4 100755 --- a/qlib/contrib/model/pytorch_gru.py +++ b/qlib/contrib/model/pytorch_gru.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_gru_ts.py b/qlib/contrib/model/pytorch_gru_ts.py index 4553c7537..514b44c8e 100755 --- a/qlib/contrib/model/pytorch_gru_ts.py +++ b/qlib/contrib/model/pytorch_gru_ts.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py index c7385c6a7..b4920921e 100755 --- a/qlib/contrib/model/pytorch_lstm.py +++ b/qlib/contrib/model/pytorch_lstm.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_lstm_ts.py b/qlib/contrib/model/pytorch_lstm_ts.py index 288bdc202..9d513dff8 100755 --- a/qlib/contrib/model/pytorch_lstm_ts.py +++ b/qlib/contrib/model/pytorch_lstm_ts.py @@ -10,7 +10,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_nn.py b/qlib/contrib/model/pytorch_nn.py index fad466165..326af92db 100644 --- a/qlib/contrib/model/pytorch_nn.py +++ b/qlib/contrib/model/pytorch_nn.py @@ -6,7 +6,6 @@ from __future__ import division from __future__ import print_function import os -import logging import numpy as np import pandas as pd from sklearn.metrics import roc_auc_score, mean_squared_error diff --git a/qlib/contrib/model/pytorch_sfm.py b/qlib/contrib/model/pytorch_sfm.py index f013d81a3..0bb2b4704 100644 --- a/qlib/contrib/model/pytorch_sfm.py +++ b/qlib/contrib/model/pytorch_sfm.py @@ -9,7 +9,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, diff --git a/qlib/contrib/model/pytorch_tabnet.py b/qlib/contrib/model/pytorch_tabnet.py index 6fcabfd21..c831a7f19 100644 --- a/qlib/contrib/model/pytorch_tabnet.py +++ b/qlib/contrib/model/pytorch_tabnet.py @@ -8,7 +8,6 @@ import numpy as np import pandas as pd import copy from sklearn.metrics import roc_auc_score, mean_squared_error -import logging from ...utils import ( unpack_archive_with_buffer, save_multiple_parts_file, @@ -397,7 +396,7 @@ class FinetuneModel(nn.Module): """ def __init__(self, input_dim, output_dim, trained_model): - super(FinetuneModel, self).__init__() + super().__init__() self.model = trained_model self.fc = nn.Linear(input_dim, output_dim) @@ -406,8 +405,9 @@ class FinetuneModel(nn.Module): class DecoderStep(nn.Module): + def __init__(self, inp_dim, out_dim, shared, n_ind, vbs): - super(DecoderStep, self).__init__() + super().__init__() self.fea_tran = FeatureTransformer(inp_dim, out_dim, shared, n_ind, vbs) self.fc = nn.Linear(out_dim, out_dim) @@ -417,13 +417,13 @@ class DecoderStep(nn.Module): class TabNet_Decoder(nn.Module): + def __init__(self, inp_dim, out_dim, n_shared, n_ind, vbs, n_steps): """ TabNet decoder that is used in pre-training """ + super().__init__() self.out_dim = out_dim - - super(TabNet_Decoder, self).__init__() if n_shared > 0: self.shared = nn.ModuleList() self.shared.append(nn.Linear(inp_dim, 2 * out_dim)) @@ -444,6 +444,7 @@ class TabNet_Decoder(nn.Module): class TabNet(nn.Module): + def __init__(self, inp_dim=6, out_dim=6, n_d=64, n_a=64, n_shared=2, n_ind=2, n_steps=5, relax=1.2, vbs=1024): """ TabNet AKA the original encoder @@ -457,7 +458,7 @@ class TabNet(nn.Module): relax coefficient: virtual batch size: """ - super(TabNet, self).__init__() + super().__init__() # set the number of shared step in feature transformer if n_shared > 0: @@ -500,7 +501,7 @@ class GBN(nn.Module): """ def __init__(self, inp, vbs=1024, momentum=0.01): - super(GBN, self).__init__() + super().__init__() self.bn = nn.BatchNorm1d(inp, momentum=momentum) self.vbs = vbs @@ -522,7 +523,7 @@ class GLU(nn.Module): """ def __init__(self, inp_dim, out_dim, fc=None, vbs=1024): - super(GLU, self).__init__() + super().__init__() if fc: self.fc = fc else: @@ -558,8 +559,9 @@ class AttentionTransformer(nn.Module): class FeatureTransformer(nn.Module): + def __init__(self, inp_dim, out_dim, shared, n_ind, vbs): - super(FeatureTransformer, self).__init__() + super().__init__() first = True self.shared = nn.ModuleList() if shared: