def __init__(self, **kwargs):
self.__dict__.update(self._defaults) # set up default values
self.__dict__.update(kwargs) # and update with user overrides
self.class_names = self._get_class()
self.anchors = self._get_anchors()
self.sess = K.get_session()
RuntimeError: get_session is not available when using TensorFlow 2.0.
Tensorflow 2.0 does not expose the backend.get_session directly any more but the code still there and expose for tf1.
https://github.com/tensorflow/tensorflow/blob/r2.0/tensorflow/python/keras/backend.py#L465
You can use it with tf1 compatible interface:
sess = tf.compat.v1.keras.backend.get_session()
Or import tenforflow backend with internal path:
import tensorflow.python.keras.backend as K
sess = K.get_session()
In order to avoid using get_session after tensorflow 2.0 upgrade, Use tf.distribute.Strategy to get model. To load model, use tf.keras.models.load_model
import tensorflow as tf
another_strategy = tf.distribute.MirroredStrategy()
with another_strategy.scope():
model = Service.load_deep_model()
def load_deep_model(self, model):
loaded_model = tf.keras.models.load_model("model.h5")
return loaded_model
Hope this helps. As this worked for me.
I have tried to explain same at this utility article as well. https://www.javacodemonk.com/runtimeerror-get_session-is-not-available-when-using-tensorflow-2-0-f7238546
Probably has something to do with tf 2.0 eager execution that is enabled by default.
Try
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
I had the same error and tried installing and uninstalling. In the end, I found that the library was not actually installed correctly.
I went through each library in my:
C:\Users\MyName\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\
I tracked down the file in within the site-packages in Keras, which was calling from the Tensorflow library, which was calling from another folder. I found the final folder had the get_session(), but this was not being called in. When I checked the directory, I found that get_session wasn't being loaded in. Within the file directory /tensorflow/keras/backend.py it was importing everything, but missed out the get_session.
To fix this I added this line:
from tensorflow.python.keras.backend import get_session
Then saved it. The next time I ran my code it was fine.
I gave the same answer for this page How to fix ' module 'keras.backend.tensorflow_backend' has no attribute '_is_tf_1''
Related
I've been following this tutorial to create a custom NER. However, I keep getting this error:
ValueError: [E143] Labels for component 'tagger' not initialized. This can be fixed by calling add_label, or by providing a representative batch of examples to the component's initialize method.
This is how I defined the spacy model:
import spacy
from spacy.tokens import DocBin
from tqdm import tqdm
nlp = spacy.blank("ro") # load a new spacy model
source_nlp = spacy.load("ro_core_news_lg")
nlp.tokenizer.from_bytes(source_nlp.tokenizer.to_bytes())
nlp.add_pipe("tagger", source=source_nlp)
doc_bin = DocBin() # create a DocBin object
I just meet the same problem. The picture of setting the config file is misleading you.
If you just want to run through the tutrital, you can set the config file like this.
only click the check box on ner
I am currently using jupyter-manim since it is the most efficient way for me to use manim. I'm running my code on Kaggle and every time I use TextMobject in manim, it outputs an error that says Latex error converting to dvi. See log output above or the log file: media/Tex/54dfbfee288272f0.log. I've tried TexMobject and Text function, but only the Text function works. The Text function is limited however, and I'm not sure how to change the font. Is there a way to fix this or is it something that comes with using jupyter-manim? It seems that all the other functions work such as drawing shapes, animating scenes, etc.
%%manim
class Text(Scene):
def construct(self):
first_line = TextMobject('Hi')
second_line = TexMobject('Hi')
#Only one that works
third_line = Text('Hi')
I tried your Manim program and it worked as expected for me. I would try making sure
include from manimlib.imports import * in your first line (importing Manim library)
include self.play(...) so you can see them
I think you already have these, but I'm putting them in case you don't.
You may also be getting the error because you do not have a LaTeX distribution installed on your system (i.e. MikTex or Texlive).
I think part of your problem may be the name of the class you chose. I had problems with your code until I changed the name from Text to TextTest. Here is a minimally working example that works fine in my Jupyter notebook (after running import jupyter_manim of course).
%%manim TextTest -p -ql
from manim import *
class TextTest(Scene):
def construct(self):
first_line = TextMobject('Hi 1')
second_line = TexMobject('Hi 2').shift(DOWN)
third_line = Text('Hi 3').shift(UP)
self.add(first_line)
self.add(second_line)
self.add(third_line)
self.wait(1)
Also, you should be aware that TextMobject and TexMobject have been deprecated.
I'm trying to model evaluate the performance of our deep learning models. And below is my code. However, I still get
No module named 'model_evaluation_utils'
Is there any pip installation or conda that could solve this problem?
from keras.preprocessing.image import load_img, img_to_array, array_to_img
from keras.models import load_model
import model_evaluation_utils as meu # throws error
Implementation of "model_evaluation_utils" can be found in the following github repository:
link
I think it's not a publicly available library, there must be a model_evaluation_utils.py file which is imported in the code and is used.
I am using weka for my project. but get the error info"could not find class weka.core.FastVector" on the line below. I have already added weka.jar from the build path of the project by adding external jar file. How should I solve this problem? Thanks a lot for your time on reviewing my question.
import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;
FastVector atts;
private void setUpARFF(){
atts = new FastVector();}
I know that FastVector was marked as obsolete a while back, perhaps they've finally removed it. Are you using the dev version of weka (or what version are you using)? FastVector can be replaced with ArrayList (in dev version) so use that instead.
I'm following the example here: http://code.google.com/p/modwsgi/wiki/IntegrationWithPylons
however, it doesn't work - I get "ImportError: No module named paste.deploy" in the apache error log. Googling in this case helps not - I see some stuff about permissions, but all my permissions are fine. Where does paste.deploy really come from? It comes from PasteDeploy-1.3.4-py2.6.egg in site-packages, installed in my pylonsdevenv directory, right? Well, then how is apache supposed to know about that directory? Does the actual pylons project have to be in the pylonsdevenv directory?
thanks!
I added:
import site
site.addsitedir('/<yadayada>/pylonsdevenv/lib/python2.6/site-packages')
to the top of my wsgi file, and then set debug = False in my development.ini file (and later, deployment.ini file, I presume), that seemed to work...
If you can import (from paste.deploy import loadapp) manually it has to be a problem with sys.path. Also make sure that apache uses proper python interpreter. I have something like this in my "passanger_wsgi.py" on Dreamhost:
INTERP = "/home/myuser/bin/python"
if sys.executable != INTERP: os.execl(INTERP, INTERP, *sys.argv)
cwd = os.getcwd()
sys.path.append(os.getcwd())
sys.path.append('/home/myuser/blog')
You can try put some debug and check which paths are inside "sys.path".
Hope this helps.