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I'm trying to run inference using the command ./run.sh VER="mhanet-1.1c" INFER=1 GAIN="mmse-lsa". I just want to use the pretrained model to operate on some noisy .wav files.
However, when I run this command, I get this error:
This workstation is not known.
Finding GPU/s...
1 total GPU/s.
Using GPU 0.
2023-06-15 10:36:40.737557: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-06-15 10:36:41.308076: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Arguments:
gpu 0
ver mhanet-1.1c
test_epoch 200
train False
infer True
test False
spect_dist False
prelim False
verbose False
network_type MHANetV3
inp_tgt_type MagXi
sd_snr_levels [-5, 0, 5, 10, 15]
mbatch_size 8
sample_size 1000
max_epochs 200
resume_epoch 0
save_model True
log_iter False
eval_example True
val_flag True
reset_inp_tgt False
reset_sample False
out_type y
gain mmse-lsa
model_path /home/ericl/deepxi/DeepXi/model
set_path set
log_path log
data_path /home/ericl/deepxi/data/input
test_x_path set/test_noisy_speech
test_s_path set/test_clean_speech
test_d_path set/test_noise
out_path /home/ericl/deepxi/data/output
saved_data_path None
min_snr -10
max_snr 20
snr_inter 1
f_s 16000
T_d 32
T_s 16
n_filters None
d_in None
d_out None
d_model 256
n_blocks 5
n_heads 8
d_b None
d_f None
d_ff None
k None
max_d_rate None
causal True
warmup_steps 40000
length None
m_1 None
centre None
scale None
unit_type None
loss_fnc BinaryCrossentropy
outp_act Sigmoid
max_len 2048
map_type DBNormalCDF
map_params [None, None]
2023-06-15 10:36:42.602692: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:982] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
2023-06-15 10:36:42.710381: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1956] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
Version: mhanet-1.1c.
Traceback (most recent call last):
File "/home/ericl/deepxi/DeepXi/main.py", line 53, in <module>
deepxi = DeepXi(
File "/home/ericl/deepxi/DeepXi/deepxi/model.py", line 87, in __init__
s_sample, d_sample, x_sample, wav_len = self.sample(sample_size, sample_dir)
File "/home/ericl/deepxi/DeepXi/deepxi/model.py", line 464, in sample
raise ValueError('No sample.npz file exists.')
ValueError: No sample.npz file exists.
Am I supposed to train the model from scratch just so I can use it for inference? How do I get the sample.npz file?
This is my config.sh:
#!/bin/bash
PROJ_DIR='deepxi'
NEGATIVE="-"set -o noglob
## Use hostname or whoami to set the paths on your workstation.
... (other code)
*) echo"This workstation is not known."
LOG_PATH='log'
SET_PATH='set'
DATA_PATH='/home/ericl/deepxi/data/input'
TEST_X_PATH='set/test_noisy_speech'
TEST_S_PATH='set/test_clean_speech'
TEST_D_PATH='set/test_noise'
OUT_PATH='/home/ericl/deepxi/data/output'
MODEL_PATH='/home/ericl/deepxi/DeepXi/model';;esac;;esacget_free_gpu () {
echo"Finding GPU/s..."if! [ -x"$(command -v nvidia-smi)" ];thenecho"nvidia-smi does not exist, using CPU instead."
GPU=-1
else
NUM_GPU=$( nvidia-smi --query-gpu=pci.bus_id --format=csv,noheader | wc -l )echo"$NUM_GPU total GPU/s."whiletruedofor(( GPU=0; GPU<$NUM_GPU; GPU++))do
VAR1=$( nvidia-smi -i $GPU --query-gpu=pci.bus_id --format=csv,noheader )
VAR2=$( nvidia-smi -i $GPU --query-compute-apps=gpu_bus_id --format=csv,noheader | head -n 1)if [ "$VAR1"!="$VAR2" ]
thenecho"Using GPU $GPU."returnfidoneecho'Waiting for free GPU.'
sleep 1m
donefi
}
VER=0
TRAIN=0
INFER=0
TEST=0
OUT_TYPE='y'
GAIN='mmse-lsa'forARGUMENTin"$@"do
KEY=$(echo $ARGUMENT| cut -f1 -d=)
VALUE=$(echo $ARGUMENT| cut -f2 -d=)case"$KEY"in
VER) VER=${VALUE} ;;
GPU) GPU=${VALUE} ;;
TRAIN) TRAIN=${VALUE} ;;
INFER) INFER=${VALUE} ;;
TEST) TEST=${VALUE} ;;
OUT_TYPE) OUT_TYPE=${VALUE} ;;
GAIN) GAIN=${VALUE} ;;
*)
esacdone
WAIT=0
if [ -z$GPU ]
then
get_free_gpu $WAIT
GPU=$?fi
The text was updated successfully, but these errors were encountered:
I'm trying to run inference using the command
./run.sh VER="mhanet-1.1c" INFER=1 GAIN="mmse-lsa"
. I just want to use the pretrained model to operate on some noisy .wav files.However, when I run this command, I get this error:
Am I supposed to train the model from scratch just so I can use it for inference? How do I get the sample.npz file?
This is my config.sh:
The text was updated successfully, but these errors were encountered: