brainstorm/structure/network.py
def backward_pass(self):
        """
        Perform a backward pass on all provided data and targets.

        Note:
            All the targets to be used during this backward pass have to be
            passed to the network beforehand using provide_external_data.
            Also this backward pass depends on the internal state produced by
            a forward pass. So you have to always run a forward_pass first.
        """
        self._buffer_manager.clear_backward_buffers()
        for layer_name, layer in reversed(list(self.layers.items())[1:]):
            layer.backward_pass(self.buffer[layer_name])
        self.apply_gradient_modifiers()

        Perform a backward pass on all provided data and targets.

        Note:
            All the targets to be used during this backward pass have to be
            passed to the network beforehand using provide_external_data.
            Also this backward pass depends on the internal state produced by
            a forward pass. So you have to always run a forward_pass first.
        
Perform a backward pass on all provided data and targets.
Note:
All the targets to be used during this backward pass have to be
passed to the network beforehand using provide_external_data.
Also this backward pass depends on the internal state produced by
a forward pass. So you have to always run a forward_pass first.
Perform a backward pass on all provided data and targets . Note : All the targets to be used during this backward pass have to be passed to the network beforehand using provide_external_data . Also this backward pass depends on the internal state produced by a forward pass . So you have to always run a forward_pass first .
def backward_pass(self):
        self._buffer_manager.clear_backward_buffers()
        for layer_name, layer in reversed(list(self.layers.items())[1:]):
            layer.backward_pass(self.buffer[layer_name])
        self.apply_gradient_modifiers()
def backward_pass ( self ) : self . _buffer_manager . clear_backward_buffers ( ) for layer_name , layer in reversed ( list ( self . layers . items ( ) ) [ 1 : ] ) : layer . backward_pass ( self . buffer [ layer_name ] ) self . apply_gradient_modifiers ( )
Perform a backward pass on all provided data and targets.
Perform a backward pass on all provided data and targets .
"""
        Perform a backward pass on all provided data and targets.

        Note:
            All the targets to be used during this backward pass have to be
            passed to the network beforehand using provide_external_data.
            Also this backward pass depends on the internal state produced by
            a forward pass. So you have to always run a forward_pass first.
        """
self