use lazy-loading in example

performance_testing
Jan Petykiewicz 2 years ago
parent 8ff8a47784
commit c9ffa66f8d

@ -21,8 +21,8 @@ connectivity = [
cells, props = oasis.readfile('connectivity.oas') cells, props = oasis.readfile('connectivity.oas')
topcell = cells['top'] topcell = cells['top']
polys, labels = snarled.interfaces.masque.read_cell(topcell, connectivity) get_layer = snarled.interfaces.masque.prepare_cell(topcell)
nets_info = snarled.trace_connectivity_preloaded(polys, labels, connectivity) nets_info = snarled.trace_connectivity(get_layer, connectivity)
print('\nFinal nets:') print('\nFinal nets:')
print([kk for kk in sorted(nets_info.nets.keys()) if isinstance(kk.name, str)]) print([kk for kk in sorted(nets_info.nets.keys()) if isinstance(kk.name, str)])

@ -1,7 +1,7 @@
""" """
Functionality for extracting geometry and label info from `masque` patterns. Functionality for extracting geometry and label info from `masque` patterns.
""" """
from typing import Sequence, Dict, List, Any, Tuple, Optional, Mapping from typing import Sequence, Dict, List, Any, Tuple, Optional, Mapping, Callable
from collections import defaultdict from collections import defaultdict
import numpy import numpy
@ -14,6 +14,80 @@ from ..types import layer_t
from ..utils import connectivity2layers from ..utils import connectivity2layers
def prepare_cell(
cell: Pattern,
label_mapping: Optional[Mapping[layer_t, layer_t]] = None,
) -> Callable[[layer_t], Tuple[
List[NDArray[numpy.float64]],
List[Tuple[float, float, str]]
]]:
"""
Generate a function for extracting `polys` and `labels` from a `masque.Pattern`.
The returned function can be passed to `snarled.trace_connectivity`.
Args:
cell: A `masque` `Pattern` object. Usually your topcell.
label_mapping: A mapping of `{label_layer: metal_layer}`. This allows labels
to refer to nets on metal layers without the labels themselves being on
that layer.
Default `None` reads labels from the same layer as the geometry.
Returns:
`get_layer` function, to be passed to `snarled.trace_connectivity`.
"""
def get_layer(
layer: layer_t,
) -> Tuple[
List[NDArray[numpy.float64]],
List[Tuple[float, float, str]]
]:
if label_mapping is None:
label_layers = {layer: layer}
else:
label_layers = {label_layer for label_layer, metal_layer in label_mapping.items()
if metal_layer == layer}
subset = cell.deepcopy().subset( # TODO add single-op subset-and-copy, to avoid copying unwanted stuff
shapes_func=lambda ss: ss.layer == layer,
labels_func=lambda ll: ll.layer in label_layers,
subpatterns_func=lambda ss: True,
)
flat = subset.flatten()
# load polygons
polys = []
for ss in flat.shapes:
assert(isinstance(ss, Polygon))
if ss.repetition is None:
displacements = [(0, 0)]
else:
displacements = ss.repetition.displacements
for displacement in displacements:
polys.append(
ss.vertices + ss.offset + displacement
)
# load metal labels
labels = []
for ll in flat.labels:
if ll.repetition is None:
displacements = [(0, 0)]
else:
displacements = ll.repetition.displacements
for displacement in displacements:
offset = ll.offset + displacement
labels.append((*offset, ll.string))
return polys, labels
return get_layer
def read_cell( def read_cell(
cell: Pattern, cell: Pattern,
connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]], connectivity: Sequence[Tuple[layer_t, Optional[layer_t], layer_t]],
@ -41,57 +115,11 @@ def read_cell(
metal_layers, via_layers = connectivity2layers(connectivity) metal_layers, via_layers = connectivity2layers(connectivity)
poly_layers = metal_layers | via_layers poly_layers = metal_layers | via_layers
if label_mapping is None: get_layer = prepare_cell(cell, label_mapping)
label_mapping = {layer: layer for layer in metal_layers}
label_layers = {label_layer for label_layer in label_mapping.keys()}
cell = cell.deepcopy().subset(
shapes_func=lambda ss: ss.layer in poly_layers,
labels_func=lambda ll: ll.layer in label_layers,
subpatterns_func=lambda ss: True,
)
# load polygons
polys = defaultdict(list) polys = defaultdict(list)
labels = defaultdict(list)
for layer in poly_layers: for layer in poly_layers:
shapes_hier = cell.subset( polys[layer], labels[layer] = get_layer(layer)
shapes_func=lambda ss: ss.layer == layer,
subpatterns_func=lambda ss: True,
)
shapes = shapes_hier.flatten().shapes
for ss in shapes: return polys, labels
assert(isinstance(ss, Polygon))
if ss.repetition is None:
displacements = [(0, 0)]
else:
displacements = ss.repetition.displacements
for displacement in displacements:
polys[ss.layer].append(
ss.vertices + ss.offset + displacement
)
# load metal labels
metal_labels = defaultdict(list)
for label_layer, metal_layer in label_mapping.items():
labels_hier = cell.subset(
labels_func=lambda ll: ll.layer == label_layer,
subpatterns_func=lambda ss: True,
)
labels = labels_hier.flatten().labels
for ll in labels:
if ll.repetition is None:
displacements = [(0, 0)]
else:
displacements = ll.repetition.displacements
for displacement in displacements:
offset = ll.offset + displacement
metal_labels[metal_layer].append(
(*offset, ll.string)
)
return polys, metal_labels

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