I'm trying to follow along the Audio Recognition Network tutorial.
I've created an Anaconda environment with python 3.6 and followed the install instruction accordingly for installing the GPU whl.
I can run the 'hello world' TF example.
When I go to run 'train.py' in the Audio Recognition Network tutorial/example, I get:
Traceback (most recent call last):
File "train.py", line 79, in <module>
import input_data
File "/home/philglau/speech_commands/input_data.py", line 35, in <module>
from tensorflow.contrib.framework.python.ops import audio_ops as contrib_audio
ImportError: cannot import name 'audio_ops'
The code in the tutorial that fails is:
from tensorflow.contrib.framework.python.ops import audio_ops as contrib_audio
I then backed up that chain until I could import some part of it:
import tensorflow.contrib.framework as test ==> works
import tensorflow.contrib.framework.python as test --> fail:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: module 'tensorflow.contrib.framework' has no attribute 'python'
Not sure where I'm going wrong on my install.
Details:
Ubuntu 16.04
Anaconda env with python 3.6
Followed the 'anaconda' instruction on the TF install page. (GPU version)
I also tried using a python 2.7 env for anaconda but got the same results.
It looks like they're releasing the audio_ops modules in version 1.4 (https://github.com/tensorflow/tensorflow/issues/11339#issuecomment-327879009).
Until v1.4 is released, an easy way around this is to install the nightly tensorflow build
pip install tf-nightly
or with the docker image linked in the issue comment.
The short answer:
The framework is missing the "audio_ops.py" and the example wont work until the file is released. Or you code the wrappers.
More on this:
If you go to the: tensorflow.contrib.framework.python.ops local folder you can find other *_ops.py files but not the "audio_ops.py".
If you get it from the Master at: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/framework/python/ops
You will find the file is almost empty and with import labels wrong: "audio_ops" vs "gen_audio_ops".
With almost empty I mean that: decode_wav, encode_wav, audio_spectrogram , mfcc are not implemented/wrapped.
So, no working example and no fun.
We need to check again when "audio_ops.py" is released.
Here:
https://github.com/tensorflow/tensorflow/issues/11339
You can find a Developer saying: "we don't actually want to make them public / supported yet. I'm sorry this decision wasn't better documented"
Related
After installing Anaconda on a Virtual Machine I run a script which is working on my local machine but not on my Virtual Machine.
I'm getting the error Message:
C:\Users\...\python>"C:\ProgramData\Anaconda3\python.exe" "C:\Users\...\reporting.py"
C:\ProgramData\Anaconda3\lib\site-packages\numpy\__init__.py:140: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see http://github.com/IntelPython/mkl-service
from . import _distributor_init
Traceback (most recent call last):
File "C:\Users\...\reporting.py", line 1, in <module>
import pandas as pd
File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\__init__.py", line 16, in <module>
raise ImportError(
ImportError: Unable to import required dependencies:
numpy:
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy C-extensions failed. This error can happen for
many reasons, often due to issues with your setup or how NumPy was
installed.
We have compiled some common reasons and troubleshooting tips at:
https://numpy.org/devdocs/user/troubleshooting-importerror.html
Please note and check the following:
* The Python version is: Python3.8 from "C:\ProgramData\Anaconda3\python.exe"
* The NumPy version is: "1.18.5"
and make sure that they are the versions you expect.
Please carefully study the documentation linked above for further help.
Original error was: DLL load failed while importing _multiarray_umath: The specified module could not be found.
The VM has no Internet. Is there any way to install all the required libs and frameworks?
You can package your script and used libraries using something like Pyinstaller. When you use an virtualenv keep in mind that all the packages that you use during pyinstaller execution are stored and may lead to an huge .exe
I've been following this tutorial for recognising an object using machine learning:
https://www.youtube.com/watch?v=Rgpfk6eYxJA
I've followed all the instructions on what to install and how, including those in this related tutorial:
https://www.youtube.com/watch?v=RplXYjxgZbw
I tried both with their version and the newest available versions of the software. With the exception that I create the virtual environment like this:
conda create -n tensorflow1 pip python=3.6
Because the tensorflow module isn't yet compatible with python 3.7.
After I install all the packages needed, also described here:
https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10
Under 2d. Set up new Anaconda virtual environment
and go through the code in the video, I run into a error when I run
python generate_tfrecord.py --csv_input=images\train_labels.csv --image_dir=images\train --output_path=train.record
which is working in the video at 19:35.
The error is
2019-12-11 10:13:43.410540: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'cudart64_100.dll'; dlerror: cudart64_100.dll not found
Traceback (most recent call last):
File "generate_tfrecord.py", line 17, in <module>
import tensorflow as tf
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow\__init__.py", line 98, in <module>
from tensorflow_core import *
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\__init__.py", line 40, in <module>
from tensorflow.python.tools import module_util as _module_util
File "<frozen importlib._bootstrap>", line 971, in _find_and_load
File "<frozen importlib._bootstrap>", line 947, in _find_and_load_unlocked
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow\__init__.py", line 50, in __getattr__
module = self._load()
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow\__init__.py", line 44, in _load
module = _importlib.import_module(self.__name__)
File "C:\Anaconda\envs\tensorflow1\lib\importlib\__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\python\__init__.py", line 52, in <module>
from tensorflow.core.framework.graph_pb2 import *
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\graph_pb2.py", line 16, in <module>
from tensorflow.core.framework import node_def_pb2 as tensorflow_dot_core_dot_framework_dot_node__def__pb2
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\node_def_pb2.py", line 16, in <module>
from tensorflow.core.framework import attr_value_pb2 as tensorflow_dot_core_dot_framework_dot_attr__value__pb2
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\attr_value_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__pb2
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\tensor_pb2.py", line 16, in <module>
from tensorflow.core.framework import resource_handle_pb2 as tensorflow_dot_core_dot_framework_dot_resource__handle__pb2
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\resource_handle_pb2.py", line 16, in <module>
from tensorflow.core.framework import tensor_shape_pb2 as tensorflow_dot_core_dot_framework_dot_tensor__shape__pb2
File "C:\Anaconda\envs\tensorflow1\lib\site-packages\tensorflow_core\core\framework\tensor_shape_pb2.py", line 112, in <module>
'__module__' : 'tensorflow.core.framework.tensor_shape_pb2'
TypeError: expected bytes, Descriptor found
This problem is the same that appears in the jupyter kernel when I run the imports that appear in the video at 14:25
How do I fix the
TypeError: expected bytes, Descriptor found
Error?
And what's with
Could not load dynamic library 'cudart64_100.dll'; dlerror: cudart64_100.dll not found
That also appears?
I can also share this with you, in the second tutorial, the one just about installing tensorflow-gpu library, after I create an account for cuDNN and download it as inscribed, I only get a cudnn64_7.dll file in C:\cuda\bin which is in my system path environment variable, just as are
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\libnvvp and
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\extras\CUPTI\lib64,
as instructed in the tutorial. As you can see, I have version 10.1 of Cuda and cuDNN and the paths are a bit different. The GPU Driver is also updated.
P.S. in the tensorflow installing tutorial, the test code doesn't work either.
This is all the information I think I have to offer.
I've been trying to solve this problem for 4-5 days at this point (and this is not my first video I watch to get a .record file for an image recognition neural network)
and the solutions for this particular problem offered in TypeError: expected bytes, Descriptor found or any other place on stackoverflow are not useful.
What should I do?
P.S. The tensorflow-gpu version I have is 2.0.0, and it might not be compatible with Cuda and cuDNN. It might be why I only have a cudnn64_7.dll file and not a cudart64_100.dll file. If no one has other solutions, I'll just install tensorflow 1.5 and try the software again.
If someone has another solution however, by all means, post it. I'll post a reply if it works. I'll edit this if it doesn't.
I've followed a different tutorial, however came across the same errors.
In case anyone is still wondering, I've fixed it by updating the tensorflow version from 1.5 originally to 1.15
pip install --ignore-installed --upgrade tensorflow-gpu==1.15.0
This is the official issue where I got the idea from.
As for the second part,
Could not load dynamic library 'cudart64_100.dll'; dlerror: cudart64_100.dll not found
This is an issue with the CUDA drivers. In short, there's compatibility issue between the tensorflow and your GPU. In most cases, don't worry too much, since it will default to using your CPU over GPU for training of a model. In case you really want to use the GPU (for better performance etc) check if it's supported. You can check similarly asked question, or from an official source.
Alternatively, since you've installed CUDA 10.1, as per official documentation, you'll need to upgrade tensorflow 2.1.0 or above to make it work.
Personally, I had to opt to using tensorflow 1.15 over 2.2.0 and installing CUDA 9.0 to make everything run. However, I'm working on a laptop with a mobile 1050 GPU, and no matter what, I couldn't get it to run otherwise.
I am trying to create a custom TFrecords.
When I called a script that uses the tf.python_io.TFRecordWriter(..) as ...:
this error came up
log:
Traceback (most recent call last):
File "createtfrecordsbyother.py", line 105, in <module>
main(args)
File "createtfrecordsbyother.py", line 85, in main
num_shards=num_shards_train)
File "createtfrecordsbyother.py", line 45, in create_tfrecords
with tf.python_io.TFRecordWriter(output_filename) as tfrecord_writer:
AttributeError: module 'tensorflow' has no attribute 'python_io'
Switched to the tensorflow,ver1.15 .
After switching to that version that error is gone and replaced with a warning that states module is depreciated with a new name (io) instead of (python_io)
Note many modules also changed the name.
and downgrading tensorflow may require a updates of CUDA and Cudnn library.
It's not a complete solution to those who wanted to stay in Tensorflow2.0-gpu
But I will post this as a solution for those who are like me fine with downgrade to 1.15.
For uninstall tf,please refer to tf official documentation under install page.
I'm trying to run session_test.py from https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/client/session_test.py, So in my anaconda, tensorflow virtual env, I went to the corresponding directory in tensorflow like ../master/tensorflow/python/client/.. and run
python session_test.py
I got exception info like this:
Traceback (most recent call last):
File "session_test.py", line 32, in
from tensorflow.core.protobuf import cluster_pb2
ImportError: cannot import name 'cluster_pb2'
What package I should install or related documents that I could read about it. Is there anyone trying to do the same thing, run those unit test coming along with each module in tensorflow repo?
Please help me, thanks!
That line was added just a couple of weeks ago (see commit), and relates to a new feature being implemented in TensorFlow. Unless you have compiled and installed a very bleeding-edge version of TensorFlow you won't be able to run it. Instead, try to run the script corresponding to the version of TensorFlow that you have installed (for example, this is for version 1.1.0, the latest stable release at the time of writing).
I'm trying to install tensorflow and now I'm stuck with the following warning:
ranj#ranj-Aspire-V3-772G:~$ python3 -c 'import tensorflow as tf; print(tf.__version__)' # for Python 3Traceback (most recent call last):
...
File "/usr/lib/python3.5/imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libnvidia-fatbinaryloader.so.375.39: cannot open shared object file: No such file or directory
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
...
File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: libnvidia-fatbinaryloader.so.375.39: cannot open shared object file: No such file or directory
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/install_sources#common_installation_problems
for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.
Can someone tell me how I can solve it?
I'm not sure what exactly caused the error you report, but it seems like an issue with CUDA and/or communication with the NVIDIA card in general. Also, I don't know why the installation of the graphics driver failed as you mention in the comments, but if you want to have GPU support, having a working graphics driver is essential obviously. So either the driver you have currently installed works fine already or then you will have to find out why installing a new version of the driver fails.
You could proceed like this:
Make sure your graphics card fulfills the requirements (CUDA compute capability >= 3.0, check the compute capability of your card here).
Make sure your installation of cuDNN and CUDA Toolkit works fine. For this, you could follow the instructions here (point 6.2.2).
If this works fine, it might just be that Tensorflow cannot find the required CUDA libraries. Check this related Stackoverflow post: GPU tensorflow install issue
As a side note: the tutorial you linked in the comments seems to suggest that you have to build Tensorflow from source using bazel, which is in fact not always necessary. I would recommend you take a look at the official installation instructions - those are pretty comprehensive and consider all the details you require for the installation. So if all fails, consider starting from scratch and follow the official tutorial linked above.
I finally fixed it in gnome (ctrl+alt+f3) and logged in with my account and then used:
"sudo init 3"
"sudo -i"
Went to downloads dir and installed the nvidia driver: "sh NVIDIAxxx.run"
"reboot"
In the gnome I can use python3 and import tensorflow
The problem is now that I cannot login to the os in the normal manner. I still can log into the gmome