From 2a66366be4c2715870e4859fd5a5db6e8a9dc00a Mon Sep 17 00:00:00 2001
From: chenmengzheAAA <123789350+chenmengzheAAA@users.noreply.github.com>
Date: 星期四, 14 九月 2023 19:00:17 +0800
Subject: [PATCH] Merge pull request #956 from alibaba-damo-academy/chenmengzheAAA-patch-4
---
funasr/modules/repeat.py | 21 +++++++++++++++++----
1 files changed, 17 insertions(+), 4 deletions(-)
diff --git a/funasr/modules/repeat.py b/funasr/modules/repeat.py
index ff1e182..7e16066 100644
--- a/funasr/modules/repeat.py
+++ b/funasr/modules/repeat.py
@@ -14,25 +14,38 @@
class MultiSequential(torch.nn.Sequential):
"""Multi-input multi-output torch.nn.Sequential."""
+ def __init__(self, *args, layer_drop_rate=0.0):
+ """Initialize MultiSequential with layer_drop.
+
+ Args:
+ layer_drop_rate (float): Probability of dropping out each fn (layer).
+
+ """
+ super(MultiSequential, self).__init__(*args)
+ self.layer_drop_rate = layer_drop_rate
+
def forward(self, *args):
"""Repeat."""
- for m in self:
- args = m(*args)
+ _probs = torch.empty(len(self)).uniform_()
+ for idx, m in enumerate(self):
+ if not self.training or (_probs[idx] >= self.layer_drop_rate):
+ args = m(*args)
return args
-def repeat(N, fn):
+def repeat(N, fn, layer_drop_rate=0.0):
"""Repeat module N times.
Args:
N (int): Number of repeat time.
fn (Callable): Function to generate module.
+ layer_drop_rate (float): Probability of dropping out each fn (layer).
Returns:
MultiSequential: Repeated model instance.
"""
- return MultiSequential(*[fn(n) for n in range(N)])
+ return MultiSequential(*[fn(n) for n in range(N)], layer_drop_rate=layer_drop_rate)
class MultiBlocks(torch.nn.Module):
--
Gitblit v1.9.1