def get_connections(layers):
connections = []
for layer_name, layer in layers.items():
for con in layer.outgoing:
start = get_normalized_path(con.start_layer, 'outputs',
con.output_name)
end = get_normalized_path(con.end_layer, 'inputs', con.input_name)
connections.append((start, end))
bwd_con = get_backward_connection(start, end, layer)
if bwd_con:
connections.append(bwd_con)
# add connections to implicit 'parameters', and 'gradients'-layer
for layer_name, layer in layers.items():
for param_name in layer.parameter_shapes:
start = get_normalized_path(layer_name, 'parameters', param_name)
end = 'parameters'
connections.append((start, end))
start = get_normalized_path(layer_name, 'gradients', param_name)
end = 'gradients'
connections.append((start, end))
return sorted(connections)
def get_connections(layers):
connections = []
for layer_name, layer in layers.items():
for con in layer.outgoing:
start = get_normalized_path(con.start_layer, 'outputs',
con.output_name)
end = get_normalized_path(con.end_layer, 'inputs', con.input_name)
connections.append((start, end))
bwd_con = get_backward_connection(start, end, layer)
if bwd_con:
connections.append(bwd_con)
# add connections to implicit 'parameters', and 'gradients'-layer
for layer_name, layer in layers.items():
for param_name in layer.parameter_shapes:
start = get_normalized_path(layer_name, 'parameters', param_name)
end = 'parameters'
connections.append((start, end))
start = get_normalized_path(layer_name, 'gradients', param_name)
end = 'gradients'
connections.append((start, end))
return sorted(connections)
def instantiate_layers_from_architecture(architecture):
validate_architecture(architecture)
layers = OrderedDict()
connections = collect_all_connections(architecture)
for layer_name in get_canonical_layer_order(architecture):
layer = architecture[layer_name]
LayerClass = get_layer_class_from_typename(layer['@type'] +
'LayerImpl')
incoming = {c for c in connections if c.end_layer == layer_name}
outgoing = {c for c in connections if c.start_layer == layer_name}
input_names = {c.input_name for c in incoming}
in_shapes = {}
for input_name in input_names:
incoming_out_shapes = [
layers[c.start_layer].get_shape(
get_normalized_path('outputs', c.output_name))
for c in incoming if c.input_name == input_name]
in_shapes[input_name] = combine_buffer_structures(
incoming_out_shapes)
layers[layer_name] = LayerClass(layer_name, in_shapes, incoming,
outgoing, **get_kwargs(layer))
return layers
def get_gradient_order(layer_name, layer):
return tuple([get_normalized_path(layer_name, 'gradients', o)
for o in layer.parameter_shapes])
def get_gradient_order(layer_name, layer):
return tuple([
get_normalized_path(layer_name, 'gradients', o)
for o in layer.parameter_shapes
])
def get_parameter_order(layer_name, layer):
return tuple([get_normalized_path(layer_name, "parameters", o) for o in layer.parameter_shapes])
