I am writing this code using numpy 1.9 and the latest version of Theano but I get an error which I can’t fix. I doubt it could be the way I declare variable types but I can’t work it around. I appreciate your suggestions. I want to product a matrix with a vector and sum it with a bias.

```
import theano.tensor as T
from theano import function
import numpy as np
import pprint
def test_theano_matrix():
pp = pprint.PrettyPrinter(indent=3)
W= T.fmatrix()
x=T.fvector()
b= T.fvector()
y = T.dot(W,x) + b
lin_func = function([W,x,b],y)
dt = np.dtype(np.float)
w_inp = np.matrix('1 0;0 1',dtype=dt)
x_inp = np.matrix('2;1',dtype=dt)
b_inp = np.matrix('0;0',dtype=dt)
lin_func(w_inp,x_inp,b_inp)
if __name__ == '__main__':
test_theano_matrix()
```

I get the following error:

```
raise TypeError(err_msg, data)
TypeError: ('Bad input argument to theano function at index 0(0-based)',
'TensorType(float32, matrix) cannot store a value of dtype float64 without risking loss of precision. If you do not mind this loss, you can: 1) explicitly cast your data to float32, or 2) set "allow_input_downcast=True" when calling "function".', matrix([[ 1., 0.],[ 0., 1.]]))
```

Thanks for your time!

Best answer

I had a similar error and was able to resolve it by adding a `.theanorc`

file containing the following two lines:

```
[global]
floatX = float32
```

That seemed to fix everything. However, your problem shows a slightly different error. But I think it’s worth trying.