multi-dimensional arrays. It is built on top of NumPy_. Theano
features:
Theano is a Python library that allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. It is built on top of NumPy_. Theano features:
* **tight integration with NumPy:** a similar interface to NumPy's.
numpy.ndarrays are also used internally in Theano-compiled functions.
* **transparent use of a GPU:** perform data-intensive computations up to
140x faster than on a CPU (support for float32 only).
* **efficient symbolic differentiation:** Theano can compute derivatives
for functions of one or many inputs.
* **speed and stability optimizations:** avoid nasty bugs when computing
expressions such as log(1+ exp(x) ) for large values of x.
* **tight integration with NumPy:** a similar interface to NumPy's. numpy.ndarrays are also used internally in Theano-compiled functions.
* **transparent use of a GPU:** perform data-intensive computations up to 140x faster than on a CPU (support for float32 only).
* **efficient symbolic differentiation:** Theano can compute derivatives for functions of one or many inputs.
* **speed and stability optimizations:** avoid nasty bugs when computing expressions such as log(1+ exp(x) ) for large values of x.
* **dynamic C code generation:** evaluate expressions faster.
* **extensive unit-testing and self-verification:** includes tools for
detecting and diagnosing bugs and/or potential problems.
* **extensive unit-testing and self-verification:** includes tools for detecting and diagnosing bugs and/or potential problems.
Theano has been powering large-scale computationally intensive scientific
research since 2007, but it is also approachable enough to be used in the
