From 0e622e694e6cb4459955f1e5942a7c53349ce640 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期二, 19 十二月 2023 21:58:14 +0800
Subject: [PATCH] funasr2
---
funasr/models/transformer/positionwise_feed_forward.py | 22 ----------------------
1 files changed, 0 insertions(+), 22 deletions(-)
diff --git a/funasr/models/transformer/positionwise_feed_forward.py b/funasr/models/transformer/positionwise_feed_forward.py
index ffa0f4e..7ca55cb 100644
--- a/funasr/models/transformer/positionwise_feed_forward.py
+++ b/funasr/models/transformer/positionwise_feed_forward.py
@@ -34,25 +34,3 @@
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)
-
- def forward(self, x):
- """Forward function."""
- return self.w_2(self.norm(self.dropout(self.activation(self.w_1(x)))))
--
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