From d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99 Mon Sep 17 00:00:00 2001
From: liugz18 <57401541+liugz18@users.noreply.github.com>
Date: 星期四, 18 七月 2024 21:34:55 +0800
Subject: [PATCH] Rename 'res' in line 514 to avoid with naming conflict with line 365
---
funasr/models/transformer/positionwise_feed_forward.py | 30 ++++++++++--------------------
1 files changed, 10 insertions(+), 20 deletions(-)
diff --git a/funasr/models/transformer/positionwise_feed_forward.py b/funasr/models/transformer/positionwise_feed_forward.py
index ffa0f4e..7cfa5f9 100644
--- a/funasr/models/transformer/positionwise_feed_forward.py
+++ b/funasr/models/transformer/positionwise_feed_forward.py
@@ -34,25 +34,15 @@
return self.w_2(self.dropout(self.activation(self.w_1(x))))
-class PositionwiseFeedForwardDecoderSANM(torch.nn.Module):
- """Positionwise feed forward layer.
-
- Args:
- idim (int): Input dimenstion.
- hidden_units (int): The number of hidden units.
- dropout_rate (float): Dropout rate.
-
- """
-
- def __init__(self, idim, hidden_units, dropout_rate, adim=None, activation=torch.nn.ReLU()):
- """Construct an PositionwiseFeedForward object."""
- super(PositionwiseFeedForwardDecoderSANM, self).__init__()
- self.w_1 = torch.nn.Linear(idim, hidden_units)
- self.w_2 = torch.nn.Linear(hidden_units, idim if adim is None else adim, bias=False)
- self.dropout = torch.nn.Dropout(dropout_rate)
- self.activation = activation
- self.norm = LayerNorm(hidden_units)
+class PositionwiseFeedForwardDecoderSANMExport(torch.nn.Module):
+ def __init__(self, model):
+ super().__init__()
+ self.w_1 = model.w_1
+ self.w_2 = model.w_2
+ self.activation = model.activation
+ self.norm = model.norm
def forward(self, x):
- """Forward function."""
- return self.w_2(self.norm(self.dropout(self.activation(self.w_1(x)))))
+ x = self.activation(self.w_1(x))
+ x = self.w_2(self.norm(x))
+ return x
--
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