Hi,

I wanted to use the package to perform MCMC for a very simple neural network model, but there is some error which I am not able to figure out (I am not very familiar with the pymc3 and theano). The codes are the following. Appreciate if you can offer any idea!

```
import numpy as np
import scipy.stats as ss
import pymc3 as pm
import theano.tensor as tt
d_i = 2 #number of inputs
d_o = 2 #number of outputs
hidden_units = 2 # number of dimension
sigma = 0.01 # sigma of prior distribution
sigma2_e = 0.000001
nnmodel = pm.Model()
data_x = np.loadtxt('input.txt',dtype='f', delimiter=' ')
data_y = np.loadtxt('output.txt',dtype='f', delimiter=' ')
ns = np.size(data_x,0) # the number of data samples
with nnmodel:
x1 = pm.Normal('x1', mu=0, tau=1, shape=(d_i+1)*hidden_units )
x2 = pm.Normal('x2', mu=0, tau = 1, shape=(1+hidden_units)*d_o )
mu0 = np.zeros((1,d_o*ns))
cove = np.eye(d_o*ns)*sigma2_e
b1 = x1[d_i*hidden_units : ]
b1 = np.tile(b1, (ns,1))
W1 = x1[:d_i*hidden_units] #assign weights associated to connection between input and hidden layer
W1 = W1.reshape((d_i, hidden_units))
W2 = x2[:d_o*hidden_units] #assign weights associated to connection between output and hidden layer
W2 = W2.reshape((hidden_units, d_o))
b2 = x2[d_o*hidden_units : ]
b2 = np.tile(b2, (ns,1))
angle = tt._shared(data_x) # convert format of input np.array data
W1 = tt._shared(W1)
b1 = tt._shared(b1)
W2 = tt._shared(W2)
b2 = tt._shared(b2)
z1 = tt.dot(angle, W1) + b1
a1 = np.tanh(z1)
out = tt.dot(a1, W2) + b2
dif = out - data_y
dif = np.reshape(dif, (1, d_o*ns))
mu0 = tt._shared(mu0)
cove = tt._shared(cove)
y = pm.MvNormal('y', mu = mu0, cov =cove, observed=dif )
trace = pm.sample(5000,core=12)
```

My error is

```
W_1 = tt._shared(W1)
File "/software/Anaconda/5.3.1/lib/python3.7/site-packages/theano/tensor/sharedvar.py", line 45, in tensor_constructor
raise TypeError()
```

TypeError