As of version 1.8, several of the routines in `np.linalg`

can operate on a 'stack' of matrices. That is, the routine can calculate results for multiple matrices if they're stacked together. For example, `A`

here is interpreted as two stacked 3-by-3 matrices:

```
np.random.seed(123)
A = np.random.rand(2,3,3)
b = np.random.rand(2,3)
x = np.linalg.solve(A, b)
print np.dot(A[0,:,:], x[0,:])
# array([ 0.53155137, 0.53182759, 0.63440096])
print b[0,:]
# array([ 0.53155137, 0.53182759, 0.63440096])
```

The official `np`

docs specify this via parameter specifications like `a : (..., M, M) array_like`

.

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