(self, shared_outputs=None)
Allocate output buffer to store activations from fprop.

        Arguments:
            shared_outputs (Tensor, optional): pre-allocated tensor for activations to be
                                               computed into
Allocate output buffer to store activations from fprop.
Allocate output buffer to store activations from fprop .
def allocate(self, shared_outputs=None):
        """
        Allocate output buffer to store activations from fprop.

        Arguments:
            shared_outputs (Tensor, optional): pre-allocated tensor for activations to be
                                               computed into
        """
        if self.outputs is None:
            self.outputs = self.be.iobuf(self.out_shape, shared=shared_outputs,
                                         parallelism=self.parallelism)
        for l in self.layers:
            self.be.allocate_new_outputs(l, self.outputs)
def allocate ( self , shared_outputs = None ) : if self . outputs is None : self . outputs = self . be . iobuf ( self . out_shape , shared = shared_outputs , parallelism = self . parallelism ) for l in self . layers : self . be . allocate_new_outputs ( l , self . outputs )