/
__init__.py
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/
__init__.py
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# Copyright 2020 D-Wave Systems Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import time
import networkx as nx
import minorminer as mm
from .layout import Layout, dnx_layout, p_norm
from .placement import Placement, closest, intersection
def find_embedding(
S,
T,
layout=(p_norm, None),
placement=closest,
mm_hint_type="initial_chains",
return_layouts=False,
**kwargs
):
"""Tries to embed S in T by computing layout-aware chains and passing
them to :func:`minorminer.find_embedding`. Chains are passed as either
`initial_chains` or `suspend_chains` (see documentation for
:func:`minorminer.find_embedding` to learn more).
Args:
S (NetworkX Graph/edges data structure (dict, list, ...)):
The source graph being embedded or a NetworkX supported data structure
for edges (see :func:`nx.convert.to_networkx_graph` for details).
T (NetworkX Graph/edges data structure (dict, list, ...)):
The target graph being embedded into or a NetworkX supported data
structure for edges (see :func:`nx.convert.to_networkx_graph` for
details).
layout (function/(function/dict/Layout, function/dict/Layout), optional):
A function to compute the :class:`.Layout` for both S and T, or a
2-tuple that either consists of a pair of functions or pre-computed
layouts (in the form of :class:`.Layout` or dicts). The first entry
in the 2-tuple applies to S while the second applies to T.
Note:
If ``layout`` is a single function and T is a dnx_graph, then the
function passed in is only applied to S and the dnx_layout is
applied to T. To run a layout function explicitly on T, pass
it in as a 2-tuple; i.e. (p_norm, p_norm).
placement (function/dict, optional, default=minorminer.placement.closest):
A function that uses the layouts of S and T to map the vertices
of S to subsets of vertices of T (:class:`.Placement`), or a dict
that contains the precomputed mapping/:class:`.Placement`.
By default, :func:`~placement.closest` is called to compute placement.
mm_hint_type (str, optional, default="initial_chains"):
This is the hint type passed to :func:`minorminer.find_embedding`.
Supported types are "initial_chains" and "suspend_chains". See
:func:`minorminer.find_embedding` for more information.
return_layouts (bool, optional, default=False):
If True, layout objects of S and T are also returned.
**kwargs (dict):
Keyword arguments passed to :class:`.Layout`, :class:`.Placement`
or :func:`minorminer.find_embedding`.
Returns:
dict: An embedding of vertices of S (keys) to chains in T (values). This
embedding is dependent on the kwargs being passed in. If ``return_layouts``
is True, a 2-tuple is returned in which the first element is the embedding
dict and the second element is another 2-tuple containing the source and
target :class:`.Layout` objects.
"""
start = time.perf_counter()
# Parse kwargs
layout_kwargs, placement_kwargs = _parse_kwargs(kwargs)
# Compute the layouts
S_layout, T_layout = _parse_layout_parameter(S, T, layout, layout_kwargs)
# Compute the placement (i.e. chains)
S_T_placement = Placement(
S_layout, T_layout, placement, **placement_kwargs)
end = time.perf_counter()
timeout = kwargs.get("timeout")
if timeout is not None:
time_remaining = timeout - (end - start)
if time_remaining <= 0:
raise TimeoutError(
"Layout and placement took {}s, you set timeout at {}.".format(end-start, timeout))
kwargs["timeout"] = time_remaining
# Run minorminer.find_embedding
if mm_hint_type == "initial_chains":
output = mm.find_embedding(
S, T, initial_chains=S_T_placement, **kwargs)
elif mm_hint_type == "suspend_chains":
output = mm.find_embedding(S, T, suspend_chains={
v: [C] for v, C in S_T_placement.items()}, **kwargs)
else:
raise ValueError(
"Only initial_chains and suspend_chains are supported minorminer hint types.")
if return_layouts:
return output, (S_layout, T_layout)
return output
def _parse_kwargs(kwargs):
"""Extract kwargs for layout and placement functions. Leave the remaining
ones for :func:`minorminer.find_embedding`.
"""
layout_kwargs = {}
# For the layout object
if "dim" in kwargs:
layout_kwargs["dim"] = kwargs.pop("dim")
if "center" in kwargs:
layout_kwargs["center"] = kwargs.pop("center")
if "scale" in kwargs:
layout_kwargs["scale"] = kwargs.pop("scale")
placement_kwargs = {}
# For the placement object
if "scale_ratio" in kwargs:
placement_kwargs["scale_ratio"] = kwargs.pop("scale_ratio")
# For closest strategy
if "subset_size" in kwargs:
placement_kwargs["subset_size"] = kwargs.pop("subset_size")
if "num_neighbors" in kwargs:
placement_kwargs["num_neighbors"] = kwargs.pop("num_neighbors")
return layout_kwargs, placement_kwargs
def _parse_layout_parameter(S, T, layout, layout_kwargs):
"""Determine what combination of iterable, dict, and function the layout
parameter is.
"""
if isinstance(layout, (tuple, list)):
if len(layout) == 2:
s_layout, t_layout = layout
else:
raise ValueError(
"layout is expected to be a function or a length-2 iterable")
else:
s_layout = t_layout = layout
# Get a Layout object for S
if isinstance(s_layout, Layout):
S_layout = s_layout
else:
# Assumes s_layout a callable or implements a mapping interface
S_layout = Layout(S, layout=s_layout, **layout_kwargs)
# Get the Layout object for T
if isinstance(t_layout, Layout):
T_layout = t_layout
else:
# Use the dnx_layout if possible
if T.graph.get("family") in ("chimera", "pegasus", "zephyr"):
T_layout = Layout(T, layout=dnx_layout, **layout_kwargs)
# Assumes t_layout a callable or implements a mapping interface
else:
T_layout = Layout(T, layout=t_layout, **layout_kwargs)
return S_layout, T_layout