From 4ace5a95b052d338947fc88809a440ccd55cf6b4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 16 十一月 2023 16:39:52 +0800
Subject: [PATCH] funasr pages
---
funasr/models/encoder/rnn_encoder.py | 12 +++++-------
1 files changed, 5 insertions(+), 7 deletions(-)
diff --git a/funasr/models/encoder/rnn_encoder.py b/funasr/models/encoder/rnn_encoder.py
index 6b75574..353beaf 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
@@ -48,12 +46,12 @@
raise ValueError(f"Not supported rnn_type={rnn_type}")
if subsample is None:
- subsample = np.ones(num_layers + 1, dtype=np.int)
+ subsample = np.ones(num_layers + 1, dtype=np.int32)
else:
subsample = subsample[:num_layers]
# Append 1 at the beginning because the second or later is used
subsample = np.pad(
- np.array(subsample, dtype=np.int),
+ np.array(subsample, dtype=np.int32),
[1, num_layers - len(subsample)],
mode="constant",
constant_values=1,
--
Gitblit v1.9.1