0.6.0 minor changes

senseppi/__init__.py

-__version__ = "0.5.9"
+__version__ = "0.6.0"
 __author__ = "Konstantin Volzhenin"
 
 from . import model, commands, esm2_model, dataset, utils, network_utils

senseppi/model.py

@@ -12,9 +12,9 @@ import torch.optim as optim
 import numpy as np
 
 
-class DynamicLSTM(pl.LightningModule):
+class DynamicGRU(pl.LightningModule):
     """
-    Dynamic LSTM module, which can handle variable length input sequence.
+    Dynamic GRU module, which can handle variable length input sequence.
 
     Parameters
     ----------
@@ -33,12 +33,12 @@ class DynamicLSTM(pl.LightningModule):
     -------
     output: tensor, shaped [batch, max_step, num_directions * hidden_size],
          tensor containing the output features (h_t) from the last layer
-         of the LSTM, for each t.
+         of the GRU, for each t.
     """
 
     def __init__(self, input_size, hidden_size=100,
                  num_layers=1, dropout=0., bidirectional=False, return_sequences=False):
-        super(DynamicLSTM, self).__init__()
+        super(DynamicGRU, self).__init__()
 
         self.lstm = torch.nn.GRU(
             input_size, hidden_size, num_layers, bias=True,
@@ -221,7 +221,7 @@ class SensePPIModel(BaselineModel):
         self.encoder_features = self.hparams.encoder_features
         self.hidden_dim = 256
 
-        self.lstm = DynamicLSTM(self.encoder_features, hidden_size=128, num_layers=3, dropout=0.5, bidirectional=True)
+        self.lstm = DynamicGRU(self.encoder_features, hidden_size=128, num_layers=3, dropout=0.5, bidirectional=True)
 
         self.dense_head = torch.nn.Sequential(
             torch.nn.Dropout(p=0.5),