I have this following snippet on Colab:
def getMap7Data():
filename = "/content/maze_7.pkl"
infile = open(filename, "rb")
maze = pickle.load(infile)
infile.close()
return maze
The maze_7.pkl involves an object called maze, and it was produced by the previous person who was working on the file.
I can locally load the pickle and see its attributes. It's a very long list, and I don't know the exact structure. I'm going to use 10-15 attributes for now, but I might need more in the future.
Google Colab gives the following error:
Traceback (most recent call last):
File "/content/loadData.py", line 27, in getMap7Data
maze = pickle.load(infile)
ModuleNotFoundError: No module named 'maze'
Is there a way to load this pickle?
It's similar to the situation given here, and this question remains unanswered, as well.
Related
I was once able to run the below python script on my Ubuntu machine without the memory errors I was getting on windows.
import pandas as pd
import numpy as np
#create a pandas dataframe for each input file
dfs1 = pd.read_csv('s1.csv', encoding='utf-8', names=list(range(0,107)),dtype='string', na_filter=False)
dfs2 = pd.read_csv('s2.csv', encoding='utf-8', names=list(range(0,107)),dtype='string', na_filter=False)
dfr = pd.read_csv('r.csv' , encoding='utf-8', names=list(range(0,107)),dtype='string', na_filter=False)
#combine them into one dataframe
dfs12r = pd.concat([dfs1, dfs2, dfr],ignore_index=True)#withour ignore index the line numbers are not adjusted
# bow is "comming
wordlist=[]
for line in range(8052):
for row in range(106) :
#print(line,row,dfs12r[row][line])
if dfs12r[row][line] not in wordlist :
wordlist.append(dfs12r[row][line])
wordlist.sort()
#print(wordlist)
print(len(wordlist)) #12350
dfBOW = pd.DataFrame(np.zeros((len(dfs12r.index), len(wordlist))),dtype='int')
#create the dictionary
wordDict = dict.fromkeys(wordlist,'default')
counter=0
for word in wordlist :
wordDict[word] = counter
counter+=1
#print(wordDict)
#will start scanning every word from dfS12R and +1 the respective cell in dfBOW
for line in range(8052):
for row in range(107):
dfBOW[wordDict[dfs12r[row][line]]][line]+=1
Unfortunately, probably after some automatic Ubuntu updates I am now getting the simple message "KIlled", after trying to run the process without any further explanation.
Through simple print statements I know that the script is interrupted inside the for loop in the end.
I understand that I should be able to make the script more memory efficient, but I am also hoping for guidance on how to get Ubuntu able to run again the same script like they used to. (Through the TOP command I can see the all of my memory including the swap is being used while inside this loop)
Could paging have been disabled somehow after the updates? Any advice is welcome.
I still have 16GB of RAM, and use Ubuntu 20.04 (Specs are the same before and after the script stopped working). I use dual boot on the same SSD.
Below is the error I am getting from teh same script on windows :
Traceback (most recent call last):
File "D:\sharedfiles\Organised\WorkSpace\ptixiaki\github\ptixiaki\code\makingthedata\2.1 Approach (Same as 2 but turning all words to lowercase)\2.1_CSVtoDataframe\CSVtoBOW.py", line 60, in <module>
dfBOW[wordDict[dfs12r[row][line]]][line]+=1
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\pandas\core\series.py", line 1143, in __setitem__
self._maybe_update_cacher()
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\pandas\core\series.py", line 1279, in _maybe_update_cacher
ref._maybe_cache_changed(cacher[0], self, inplace=inplace)
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\pandas\core\frame.py", line 3950, in _maybe_cache_changed
self._mgr.iset(loc, arraylike, inplace=inplace)
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\pandas\core\internals\managers.py", line 1141, in iset
blk.delete(blk_locs)
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\pandas\core\internals\blocks.py", line 388, in delete
self.values = np.delete(self.values, loc, 0) # type: ignore[arg-type]
File "<__array_function__ internals>", line 5, in delete
File "D:\wandowsoftware\anaconda\envs\ptixiaki\lib\site-packages\numpy\lib\function_base.py", line 4555, in delete
new = arr[tuple(slobj)]
MemoryError: Unable to allocate 501. MiB for an array with shape (12234, 10736) and data type int32
According to the example code mentioned below the library. I have followed the example code but it didn't work.
[Library] https://github.com/notAI-tech/NudeNet/
Code
from nudenet import NudeClassifier
import onnxruntime
classifier = NudeClassifier()
classifier.classify('/home/coremax/Downloads/DETECTOR_AUTO_GENERATED_DATA/IMAGES/3FEF7B75-3823-4153-8490-87483AAC6ABC'
'.jpg')
I have also followed the previous solution on StackOverflow but it didn't work
Error on running Super Resolution Model from ONNX
Traceback (most recent call last):
File "/snap/pycharm-community/276/plugins/python-ce/helpers/pydev/pydevd.py", line 1491, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "/snap/pycharm-community/276/plugins/python-ce/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/coremax/Documents/NudeNet/main.py", line 3, in <module>
classifier = NudeClassifier()
File "/home/coremax/Documents/NudeNet/nudenet/classifier.py", line 37, in __init__
self.nsfw_model = onnxruntime.InferenceSession(model_path)
File "/home/coremax/anaconda3/envs/AdultNET/lib/python3.6/site-packages/onnxruntime/capi/session.py", line 158, in __init__
self._load_model(providers or [])
File "/home/coremax/anaconda3/envs/AdultNET/lib/python3.6/site-packages/onnxruntime/capi/session.py", line 166, in _load_model
True)
RuntimeError: /onnxruntime_src/onnxruntime/core/session/inference_session.cc:238 onnxruntime::InferenceSession::InferenceSession(const onnxruntime::SessionOptions&, const onnxruntime::Environment&, const string&) status.IsOK() was false. Given model could not be parsed while creating inference session. Error message: Protobuf parsing failed.
I know it is too late but hope this helps someone build a very useful software.
why it fails
the error is that for NudeClassifier to work it has to download the onnx model from this link
but github now requires you to be logged in to download any file so the constructor for the NudeClassifier fails as it tries to download this model
Solution
create a folder in your user's home folder with the name .NudeNet/
download the model from this link
save the model in the folder you created in step one
you should now have the model at the following path ~/.NudeNet/classifier_model.onnx
now you're ready to go good luck!
I am using TensorFlow 2.4.1 and have a working script that classifies audio files. It is pretty much copy/paste from the examples and works well. I now want to send an audio file to Model Server for prediction.
I am stuck and how to get the audio into the json message. I am new to TensorFlow and Python so am probably missing something basic.
Full code: https://gitlab.com/-/snippets/2089884
Where I try to use an existing dataset (of wrong type) to be the data:
data = json.dumps({"signature_name": "serving_default", "instances": train_ds.batch(3).tolist()})
In this case the error is:
Saved model:
Traceback (most recent call last):
File "./xmits_train", line 361, in <module>
data = json.dumps({"signature_name": "serving_default", "instances": train_ds.batch(3).tolist()})
AttributeError: 'BatchDataset' object has no attribute 'tolist'
What I don't see he how to get BatchDataset into a structure that will be correct for ".tolist". Of course I may need to use a different starting structure as well.
In the script I have tried all the structures that hold the audio and none can directly be used.
I was able to utilize the test_audio data structure. To encode the first few requests into json:
data = json.dumps({"signature_name": "serving_default", "instances": test_audio[0:3].tolist()})
There may be ways to utilize the other data structures but this addresses the question.
I am trying to download data from Fashion MNIST, but it produces an error. Originally, it was downloading and working properly, but I had to terminate it because I had to turn off my computer. Once I opened the file up again, it gives me an error. I'm not sure what the problem is, but is it because I already downloaded some parts of the data once, and keras doesn't recognize that? I am using Jupyter notebook in a conda environment
Here is the link to the image:
https://i.stack.imgur.com/wLGDm.png
You have missed adding tf. to the line
fashion_mnist = keras.datasets.fashion_mnist
The below code works perfectly for me. Importing the fashion_mnist dataset has been outlined in tensorflow documention here.
Change your code to:
import tensorflow as tf
fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
or, use the better way to do it below. This avoids creating an extra variable fashion_mnist:
import tensorflow as tf
(train_images, train_labels), (test_images, test_labels) = tf.keras.datasets.fashion_mnist.load_data()
I am using tensorflow 1.9.0, keras 2.2.2 and python 3.6.6 on Windows 10 x64 OS.
I know my pc well, I can't download anything larger than 2.7 MB (in terminal), due to WinError 8.
So I manually downloaded all packs from storage.google (since some packs are 25 MB).
Check the packs:
then I paste all packs to \datasets\fashion-mnist
The next time u run your code, it should be fixed.
Note : If u have VScode then just CTRL and click the link, then you can download it easily.
I had an error regarding the cURL connection, and by looking into the error message I was able to track the file where the URL was declared. In my case it was:
/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/datasets/fashion_mnist.py
At line 44 I have commented out the line:
# base = 'https://storage.googleapis.com/tensorflow/tf-keras-datasets/'
And declared a different base URL, which I had found looking into the documentation of the original dataset:
base = 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/'
The download started immediately and gave no errors. Hope this helps.
This is because for some reason you have an incomplete download for the MNIST dataset.
You will have to manually delete the downloaded folder which usually resides in ~/.keras/datasets or any path specified by you relative to this path, in your case MNIST_data.
Go to : C:\Users\Username.keras\datasets
and then Delete the Dataset that you want to redownload or has the error
You should be good to go!
You can also manually add print for the path from which it is taking dataset ..
Ex: print(paths) in file fashion_mnist.py
with gzip.open(paths[3], 'rb') as imgpath:
print(paths) #debug print in fashion_mnist.py
x_test = np.frombuffer(
imgpath.read(), np.uint8, offset=16).reshape(len(y_test), 28, 28)
& from this path, remove the files & this will start to download fresh data ..
Change The base address with 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/' as described previously. It works for me.
I was getting error of Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
Traceback (most recent call last):
File "C:\Users\AsadA\AppData\Local\Programs\Python\Python38\lib\site-packages\numpy\lib\npyio.py", line 448, in load
return pickle.load(fid, **pickle_kwargs)
EOFError: Ran out of input
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\AsadA\AppData\Local\Programs\Python\Python38\lib\site-packages\numpy\lib\npyio.py", line 450, in load
raise IOError(
OSError: Failed to interpret file 'C:\\Users\\AsadA\\.keras\\datasets\\mnist.npz' as a pickle"**
GO TO FILE C:\Users\AsadA\AppData\Local\Programs\Python\Python38\Lib\site-packages\tensorflow\python\keras\datasets (In my Case) and follow the instructions:
All parts of Python on my computer were recently installed from the Enthought academic package, but use Pyscripter for editing and running code. I'm very early in my learning curve, and so could very well be overlooking some obvious things here.
When I try to create a plot and save it like so:
import matplotlib.pylab as pl
pl.hist(myEst, bins=20, range=(.1,.60))
pl.ylabel("Freq")
pl.xlabel("Success Probability")
pl.title('Histogram of Binomial Estimator')
pl.axis([0, 1, 0, 500])
pl.vlines (.34,0,500)
pl.savefig('TestHist.png')
pl.show()
I get these errors:
Traceback (most recent call last):
File "<editor selection>", line 9, in <module>
File "C:\Python27\lib\site-packages\matplotlib\figure.py", line 1172, in savefig
self.canvas.print_figure(*args, **kwargs)
File "C:\Python27\lib\site-packages\matplotlib\backends\backend_wxagg.py", line 100, in print_figure
FigureCanvasAgg.print_figure(self, filename, *args, **kwargs)
File "C:\Python27\lib\site-packages\matplotlib\backend_bases.py", line 2017, in print_figure
**kwargs)
File "C:\Python27\lib\site-packages\matplotlib\backends\backend_agg.py", line 450, in print_png
filename_or_obj = file(filename_or_obj, 'wb')
IOError: [Errno 13] Permission denied: 'TestHist.png'
If I take out the pl.savefig('TestHist') line everything works fine, and I can see the plot I want, but when that line is in there I get the errors.
I've checked my backend version using pl.get_backend(), it returns 'WXAgg', which according to documentation should be able to use .png format.
I've also tried including an explicit format='png' and format=png within the savefig command, but still get errors.
Can anyone give me advice on how to proceed, or another approach for saving a plot?
There's nothing wrong with your code. I just tested it locally on my machine. The issue is this error:
IOError: [Errno 13] Permission denied: 'TestHist.png'
You are most likely trying to save the file somewhere that the Python process doesn't have permission to access. What OS are you on? Where are you trying to save the file?
If it helps others, I made the silly mistake of not actually designating a file name and as a result had returned the same error message that lead me to this question for review.
Here is the code that was generating the error:
plt.savefig('C:\\Users\\bwarn\\Canopy', format='png')
Here is my correction that resolved (you'll see I designated the actual file and name)
plt.savefig('C:\\Users\\bwarn\\Canopy\\myplot.png', format='png')
The following worked for me when I was running a neural network on my windows machine:
image_path = 'A:/DeepLearning/Padhai/MLFlow/images/%s.png' % (expt_id)
plt.savefig(image_path)
Or otherwise refer:
Using 'r' in front of the path