theano/gof/op.py
def perform(self, node, inputs, output_storage, params=None):
        """
        Required: Calculate the function on the inputs and put the variables in
        the output storage. Return None.

        Parameters
        ----------
        node : Apply instance
            Contains the symbolic inputs and outputs.
        inputs : list
            Sequence of inputs (immutable).
        output_storage : list
             List of mutable 1-element lists (do not change the length of
             these lists)

        Notes
        -----
        The `output_storage` list might contain data. If an element of
        output_storage is not None, it has to be of the right type,
        for instance, for a TensorVariable, it has to be a Numpy ndarray,
        with the right number of dimensions, and the correct dtype.
        Its shape and stride pattern, can be arbitrary. It not is
        guaranteed that it was produced by a previous call to impl. It
        could be allocated by another Op impl is free to reuse it as it
        sees fit, or to discard it and allocate new memory.

        Raises
        ------
        MethodNotDefined
            The subclass does not override this method.

        """
        raise utils.MethodNotDefined(
            "perform", type(self), self.__class__.__name__,
            "Did you used Theano flags mode=FAST_COMPILE?"
            " You can use optimizer=fast_compile instead.")

        Required: Calculate the function on the inputs and put the variables in
        the output storage. Return None.

        Parameters
        ----------
        node : Apply instance
            Contains the symbolic inputs and outputs.
        inputs : list
            Sequence of inputs (immutable).
        output_storage : list
             List of mutable 1-element lists (do not change the length of
             these lists)

        Notes
        -----
        The `output_storage` list might contain data. If an element of
        output_storage is not None, it has to be of the right type,
        for instance, for a TensorVariable, it has to be a Numpy ndarray,
        with the right number of dimensions, and the correct dtype.
        Its shape and stride pattern, can be arbitrary. It not is
        guaranteed that it was produced by a previous call to impl. It
        could be allocated by another Op impl is free to reuse it as it
        sees fit, or to discard it and allocate new memory.

        Raises
        ------
        MethodNotDefined
            The subclass does not override this method.

        
Calculate the function on the inputs and put the variables in
the output storage. Return None.

Parameters

node : Apply instance
Contains the symbolic inputs and outputs.
inputs : list
Sequence of inputs (immutable).
output_storage : list
List of mutable 1-element lists (do not change the length of
these lists)

Notes

The `output_storage` list might contain data. If an element of
output_storage is not None, it has to be of the right type,
for instance, for a TensorVariable, it has to be a Numpy ndarray,
with the right number of dimensions, and the correct dtype.
Its shape and stride pattern, can be arbitrary. It not is
guaranteed that it was produced by a previous call to impl. It
could be allocated by another Op impl is free to reuse it as it
sees fit, or to discard it and allocate new memory.

Raises

MethodNotDefined
The subclass does not override this method.
Calculate the function on the inputs and put the variables in the output storage . Return None . Parameters node : Apply instance Contains the symbolic inputs and outputs . inputs : list Sequence of inputs ( immutable ) . output_storage : list List of mutable 1 - element lists ( do not change the length of these lists ) Notes The ` output_storage ` list might contain data . If an element of output_storage is not None it has to be of the right type for instance for a TensorVariable it has to be a Numpy ndarray with the right number of dimensions and the correct dtype . Its shape and stride pattern can be arbitrary . It not is guaranteed that it was produced by a previous call to impl . It could be allocated by another Op impl is free to reuse it as it sees fit or to discard it and allocate new memory . Raises MethodNotDefined The subclass does not override this method .
def perform(self, node, inputs, output_storage, params=None):
        raise utils.MethodNotDefined(
            "perform", type(self), self.__class__.__name__,
            "Did you used Theano flags mode=FAST_COMPILE?"
            " You can use optimizer=fast_compile instead.")
def perform ( self , node , inputs , output_storage , params = None ) : raise utils . MethodNotDefined ( "perform" , type ( self ) , self . __class__ . __name__ , "Did you used Theano flags mode=FAST_COMPILE?" " You can use optimizer=fast_compile instead." )
Required: Calculate the function on the inputs and put the variables in
the output storage.
Required : Calculate the function on the inputs and put the variables in the output storage .
"""
        Required: Calculate the function on the inputs and put the variables in
        the output storage. Return None.

        Parameters
        ----------
        node : Apply instance
            Contains the symbolic inputs and outputs.
        inputs : list
            Sequence of inputs (immutable).
        output_storage : list
             List of mutable 1-element lists (do not change the length of
             these lists)

        Notes
        -----
        The `output_storage` list might contain data. If an element of
        output_storage is not None, it has to be of the right type,
        for instance, for a TensorVariable, it has to be a Numpy ndarray,
        with the right number of dimensions, and the correct dtype.
        Its shape and stride pattern, can be arbitrary. It not is
        guaranteed that it was produced by a previous call to impl. It
        could be allocated by another Op impl is free to reuse it as it
        sees fit, or to discard it and allocate new memory.

        Raises
        ------
        MethodNotDefined
            The subclass does not override this method.

        """
self
node
inputs
output_storage
params