From 5f3f194ffd459fd5ebe6ea46da5e532820a66060 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期五, 21 七月 2023 11:24:31 +0800
Subject: [PATCH] update
---
funasr/models/encoder/rnn_encoder.py | 8 +++-----
1 files changed, 3 insertions(+), 5 deletions(-)
diff --git a/funasr/models/encoder/rnn_encoder.py b/funasr/models/encoder/rnn_encoder.py
index 6b75574..434af09 100644
--- a/funasr/models/encoder/rnn_encoder.py
+++ b/funasr/models/encoder/rnn_encoder.py
@@ -1,19 +1,19 @@
+
from typing import Optional
from typing import Sequence
from typing import Tuple
import numpy as np
import torch
-from typeguard import check_argument_types
from funasr.modules.nets_utils import make_pad_mask
from funasr.modules.rnn.encoders import RNN
from funasr.modules.rnn.encoders import RNNP
+from funasr.models.encoder.abs_encoder import AbsEncoder
-class RNNEncoder(torch.nn.Module):
+class RNNEncoder(AbsEncoder):
"""RNNEncoder class.
-
Args:
input_size: The number of expected features in the input
output_size: The number of output features
@@ -22,7 +22,6 @@
use_projection: Use projection layer or not
num_layers: Number of recurrent layers
dropout: dropout probability
-
"""
def __init__(
@@ -37,7 +36,6 @@
dropout: float = 0.0,
subsample: Optional[Sequence[int]] = (2, 2, 1, 1),
):
- assert check_argument_types()
super().__init__()
self._output_size = output_size
self.rnn_type = rnn_type
--
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