Update real_time_encoder_transformer.py

Author: ajatshatru01

neural_network/real_time_encoder_transformer.py

@@ -1,12 +1,12 @@
 # imports
-import torch
-import torch.nn as nn
 import math
+import torch
+from torch import nn
 
 
 # Time2Vec layer for positional encoding of real-time data like EEG
 class Time2Vec(nn.Module):
-    # Encodes time steps into a continuous embedding space so to help the transformer learn temporal dependencies.
+    # Encodes time steps into a continuous embedding space 
     def __init__(self, d_model):
         super().__init__()
         self.w0 = nn.Parameter(torch.randn(1, 1))
@@ -174,8 +174,12 @@ def __init__(
 
         # Transformer encoder for sequence modeling
         self.encoder = TransformerEncoder(
-            d_model, n_head, hidden_dim, num_layers, drop_prob
-        )
+    d_model,
+    n_head,
+    hidden_dim,
+    num_layers,
+    drop_prob
+)
 
         # Attention pooling to summarize time dimension
         self.pooling = AttentionPooling(d_model)