From 429ea5d3786fb77d1b53728307a59fe3d204d4ce Mon Sep 17 00:00:00 2001
From: speech_asr <wangjiaming.wjm@alibaba-inc.com>
Date: 星期三, 15 三月 2023 15:48:35 +0800
Subject: [PATCH] update
---
funasr/bin/eend_ola_inference.py | 10 ++--------
1 files changed, 2 insertions(+), 8 deletions(-)
diff --git a/funasr/bin/eend_ola_inference.py b/funasr/bin/eend_ola_inference.py
index 96e7516..1a47c92 100755
--- a/funasr/bin/eend_ola_inference.py
+++ b/funasr/bin/eend_ola_inference.py
@@ -27,9 +27,6 @@
from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
-from modelscope.utils.logger import get_logger
-logger = get_logger()
-
class Speech2Diarization:
"""Speech2Diarlization class
@@ -148,7 +145,7 @@
output_dir: Optional[str] = None,
batch_size: int = 1,
dtype: str = "float32",
- ngpu: int = 0,
+ ngpu: int = 1,
num_workers: int = 0,
log_level: Union[int, str] = "INFO",
key_file: Optional[str] = None,
@@ -210,8 +207,7 @@
if data_path_and_name_and_type is None and raw_inputs is not None:
if isinstance(raw_inputs, torch.Tensor):
raw_inputs = raw_inputs.numpy()
- data_path_and_name_and_type = [raw_inputs, "speech", "waveform"]
- logger.info(data_path_and_name_and_type)
+ data_path_and_name_and_type = [raw_inputs[0], "speech", "bytes"]
loader = EENDOLADiarTask.build_streaming_iterator(
data_path_and_name_and_type,
dtype=dtype,
@@ -231,8 +227,6 @@
output_writer = open("{}/result.txt".format(output_path), "w")
result_list = []
for keys, batch in loader:
- logger.info("keys: {}".format(keys))
- logger.info("batch: {}".format(batch))
assert isinstance(batch, dict), type(batch)
assert all(isinstance(s, str) for s in keys), keys
_bs = len(next(iter(batch.values())))
--
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