ckrapu

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from theano import shared
import scipy.stats as stats
from scipy.stats import gamma, norm
import pymc3 as pm
import theano.tensor as tt
import arviz as az

ckrapu

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from theano import shared
import scipy.stats as stats
from scipy.stats import gamma, norm
import pymc3 as pm
import theano.tensor as tt
import arviz as az

ckrapu

import numpy as np
import pymc3 as pm

n = 4

X_2D_train = np.random.randn(n,2)
X_2D_star  = np.random.randn(n-1, 2)
y          = np.random.randn(n,1)

with pm.Model() as model:

ckrapu

import pymc3 as pm
import numpy as np

def sigmoid(x):
    return np.exp(x) / (1. + np.exp(x))

# Create toy dataset
n = 100
n_components = 2
p = 2

ckrapu

import theano
import theano.tensor as tt
import numpy as np
import pymc3 as pm

print(theano.__version__)

x = np.asarray([0,1])
print(x.dtype)