(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)
        self.output_views = self.get_partitions(self.outputs, self.slices)
        for l, out_view in zip(self.layers, self.output_views):
            l.allocate(shared_outputs=out_view)
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 ) self . output_views = self . get_partitions ( self . outputs , self . slices ) for l , out_view in zip ( self . layers , self . output_views ) : l . allocate ( shared_outputs = out_view )