Here are some of the things I tried to make it work
I've tried searching for any file named random.py that I created (except for library files) and searched online for solutions like updating numpy but still can't find any decent solution. Here is my code:
from numpy import random
import random
#from random import uniform
#inputs- i.e population
equation_inputs = [4,-2,3.5,5,-11,-4.7]
#number of weights
num_weights = 6
sol_per_pop = 9
pop_size = (sol_per_pop,num_weights)
#tuple of pop_size
new_population = numpy.random.uniform(low=-4.0,high=4.0,size=pop_size)
The error message goes as follows
AttributeError: module 'numpy.random' has no attribute 'uniform'
I tried importing random and also
from numpy import random
The numpy.random.uniform should actually return 9 lists each with 6 solutions
Just use random.uniform while importing the related class with an alias (using 'as') or else just use import numpy while importing
An example for using alias is :
from numpy import random as np_random
Then utilize np_random.uniform()
Related
I am working on a small library and I need to know can I import modules like numpy, sklearn and etc. Using functions. For example:
def ml():
import numpy as np
import pandas as pd
x = np.array([1,2,647,345,3,7,3,8,36,64])
Is this possible ?
Simply can I import a module using a function and then use that later outside the function
The main idea is when the user calls the function ml he has all the modules related to machine learning imported and then he can use them. X = np.array was just kind of an example.
UPDATED
This should work
import importlib
def importmd(modulex):
return importlib.import_module(modulex) #Returning the module
np = importmd("numpy") #Same as import numpy as np
In the following code I'm getting errors when trying to call librosa.grifflim, telling me the attribute does not exist.
import os
from matplotlib import pyplot as plt
import librosa
import librosa.display
import IPython.display as ipd
import numpy as np
import cv2
S = cv2.imread('spectrograms/CantinaBand60.wav10.jpg')
D = librosa.amplitude_to_db(np.abs(S), ref=np.max)
signal = librosa.griffinlim(D)
sf.write('test.wav', signal, 352000)
I've upgraded librosa, and I still encounter the error. The documentation page for this function no longer seems to exist either. I've also tried import just that module using librosa.griffinlim but it continues to tell me this module doesn't exist. Was this function removed during a recent version? If so, is there another function I can use to apply the griffin lim algorithm?
librosa.griffinlim was introduced in librosa 0.7.0. So you need to have that version or later. You can check this using the following code.
import librosa; print(librosa.__version__)
I have this code
import scipy.sparse as sparse
import numpy as np
id = np.eye(13)
vals, vecs = sparse.linalg.eigsh(id, k=6)
vals
which is just the example code from the documentation here.
I am running it in a Python 2.7 console and I get the following error message:
AttributeError: 'module' object has no attribute 'linalg'
Does anyone know why this happens?
Try this code
import scipy.sparse.linalg as sp
import numpy as np
id = np.eye(13)
vals, vecs = sp.eigsh(id, k=6)
vals
This happens because linalg is a directory and not source code i.e it is a sub-package. And I guess this causes the issue because some of the Scipy sub modules do not have __init__.py, Maybe the devs did this to reduce loading times of top-level packages. You can find this information in Scipy Organization section in this link
I'm writing code in a Jupyter Notebook that involves cleaning and analyzing a large amount of consumer data. I'm trying to use dill to save the dataframes with thousands of rows so I don't have to run the code every time I want to make an adjustment, so dill seems like the perfect package to do so... Except I'm getting this error when attempting to pickle the notebook:
AttributeError: module 'dill' has no attribute 'dump_session'
Let me know if the program code is necessary - I don't think it should make a difference. The imports are:
import numpy as np
import pandas as pd
import dill
import scipy
from matplotlib import pyplot as plt
from __future__ import division
from collections import OrderedDict
from sklearn.cluster import KMeans
pd.options.display.max_columns = None
and when I run this code I get the error from above:
dill.dump_session('recengine.db')
Is there another package that's interfering with dill's use of pickle vs. cpickle?
When attempting to pass my RNN call, I call tf.nn.rnn_cell and I receive the following error:
AttributeError: module 'tensorflow.python.ops.nn' has no attribute 'rnn_cell'
Which is odd, because I'm sure I imported everything correctly:
from __future__ import print_function, division
from tensorflow.contrib import rnn
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
But looking at the docs, things have moved around between tensorflow versions.
what would you all recommend to fix this??
Line, I'm getting the error against:
state_per_layer_list = tf.unstack(init_state, axis=0)
rnn_tuple_state = tuple(
[tf.nn.rnn_cell.LSTMStateTuple(state_per_layer_list[idx][0], state_per_layer_list[idx][1])
for idx in range(num_layers)]
)
Specifically:
tf.nn.rnn_cell
I'm using anaconda 3 to manage all of this so, the dependancies should all be taken care of. I have already tried working around a damn rank/shape error with Tensor shapes which took ages to resolve.
Cheers in advance.
Replace tf.nn.rnn_cell with tf.contrib.rnn
Since version 1.0, rnn implemented as part of the contrib module.
More information can be found here
https://www.tensorflow.org/api_guides/python/contrib.rnn