def test_copy_node_get_partners_with_trace(backend):
node1 = CopyNode(4, 2, backend=backend)
node2 = Node(np.random.rand(2, 2), backend=backend, name="node2")
tn.connect(node1[0], node1[1])
tn.connect(node1[2], node2[0])
tn.connect(node1[3], node2[1])
assert node1.get_partners() == {node2: {0, 1}}
def contract_copy_node(
self,
copy_node: network_components.CopyNode,
name: Optional[Text] = None) -> network_components.BaseNode:
"""Contract all edges incident on given copy node.
Args:
copy_node: Copy tensor node to be contracted.
name: Name of the new node created.
Returns:
New node representing contracted tensor.
Raises:
ValueError: If copy_node has dangling edge(s).
"""
partners = copy_node.get_partners()
new_node = self.add_node(
network_components.contract_copy_node(copy_node, name))
# Remove nodes
for partner in partners:
if partner in self.nodes_set:
self.nodes_set.remove(partner)
for partner in partners:
if not partner.is_disabled:
partner.disable()
self.nodes_set.remove(copy_node)
copy_node.disable()
return new_node
def test_copy_node_load(tmp_path, backend):
node = tn.CopyNode(
rank=4,
dimension=3,
name='copier',
axis_names=[str(n) for n in range(4)],
backend=backend)
with h5py.File(tmp_path / 'node', 'w') as node_file:
node_group = node_file.create_group('node_data')
node_group.create_dataset('signature', data=node.signature)
node_group.create_dataset('backend', data=node.backend.name)
node_group.create_dataset(
'copy_node_dtype', data=np.dtype(node.copy_node_dtype).name)
node_group.create_dataset('name', data=node.name)
node_group.create_dataset('shape', data=node.shape)
node_group.create_dataset(
'axis_names',
data=np.array(node.axis_names, dtype=object),
dtype=string_type)
node_group.create_dataset(
'edges',
data=np.array([edge.name for edge in node.edges], dtype=object),
dtype=string_type)
loaded_node = CopyNode._load_node(node_data=node_file["node_data/"])
assert loaded_node.name == node.name
assert loaded_node.signature == node.signature
assert set(loaded_node.axis_names) == set(node.axis_names)
assert (set(edge.name for edge in loaded_node.edges) == set(
edge.name for edge in node.edges))
assert loaded_node.get_dimension(axis=1) == node.get_dimension(axis=1)
assert loaded_node.get_rank() == node.get_rank()
assert loaded_node.shape == node.shape
assert loaded_node.copy_node_dtype == node.copy_node_dtype
def test_copy_node_load(tmp_path, backend):
net = tensornetwork.TensorNetwork(backend)
node = net.add_copy_node(rank=4, dimension=3, name='copier')
with h5py.File(tmp_path / 'node', 'w') as node_file:
node_group = node_file.create_group('node_data')
node_group.create_dataset('signature', data=node.signature)
node_group.create_dataset('name', data=node.name)
node_group.create_dataset('shape', data=node.shape)
node_group.create_dataset('axis_names',
data=np.array(node.axis_names, dtype=object),
dtype=string_type)
node_group.create_dataset('edges',
data=np.array(
[edge.name for edge in node.edges],
dtype=object),
dtype=string_type)
net = tensornetwork.TensorNetwork(backend=node.network.backend.name)
loaded_node = CopyNode._load_node(net, node_file["node_data/"])
assert loaded_node.name == node.name
assert loaded_node.signature == node.signature
assert set(loaded_node.axis_names) == set(node.axis_names)
assert (set(edge.name for edge in loaded_node.edges) == set(
edge.name for edge in node.edges))
assert loaded_node.get_dimension(axis=1) == node.get_dimension(axis=1)
assert loaded_node.get_rank() == node.get_rank()
assert loaded_node.shape == node.shape
def fixture_copy_node(backend):
net = tensornetwork.TensorNetwork(backend=backend)
return CopyNode(4,
2,
"copier", ["a", "b", "c", "d"],
network=net,
backend=backend)
def contract_copy_node(
self,
copy_node: network_components.CopyNode,
name: Optional[Text] = None) -> network_components.Node:
"""Contract all edges incident on given copy node.
Args:
copy_node: Copy tensor node to be contracted.
name: Name of the new node created.
Returns:
New node representing contracted tensor.
Raises:
ValueError: If copy_node has dangling edge(s).
"""
new_tensor = copy_node.compute_contracted_tensor()
new_node = self.add_node(new_tensor, name)
partners = copy_node.get_partners()
new_axis = 0
for partner in partners:
for edge in partner.edges:
if edge.node1 is copy_node or edge.node2 is copy_node:
self.edge_order.remove(edge)
continue
old_axis = edge.axis1 if edge.node1 is partner else edge.axis2
edge.update_axis(old_node=partner,
old_axis=old_axis,
new_node=new_node,
new_axis=new_axis)
new_node.add_edge(edge, new_axis)
new_axis += 1
self.nodes_set.remove(partner)
assert len(new_tensor.shape) == new_axis
self.nodes_set.remove(copy_node)
self.nodes_set.add(new_node)
return new_node
def identity(space: Sequence[int],
backend: Optional[Text] = None,
dtype: Type[np.number] = np.float64) -> "QuOperator":
"""Construct a `QuOperator` representing the identity on a given space.
Internally, this is done by constructing `CopyNode`s for each edge, with
dimension according to `space`.
Args:
space: A sequence of integers for the dimensions of the tensor product
factors of the space (the edges in the tensor network).
backend: Optionally specify the backend to use for computations.
dtype: The data type (for conversion to dense).
Returns:
The desired identity operator.
"""
nodes = [CopyNode(2, d, backend=backend, dtype=dtype) for d in space]
out_edges = [n[0] for n in nodes]
in_edges = [n[1] for n in nodes]
return quantum_constructor(out_edges, in_edges)
def fixture_copy_node(backend): return CopyNode(4, 2, "copier", ["a", "b", "c", "d"], backend=backend)
def copy(nodes: Iterable[BaseNode],
conjugate: bool = False) -> Tuple[dict, dict]:
"""Copy the given nodes and their edges.
This will return a dictionary linking original nodes/edges
to their copies. If nodes A and B are connected but only A is passed in to be
copied, the edge between them will become a dangling edge.
Args:
nodes: An `Iterable` (Usually a `List` or `Set`) of `Nodes`.
conjugate: Boolean. Whether to conjugate all of the nodes
(useful for calculating norms and reduced density
matrices).
Returns:
A tuple containing:
node_dict: A dictionary mapping the nodes to their copies.
edge_dict: A dictionary mapping the edges to their copies.
"""
node_dict = {}
for node in nodes:
if isinstance(node, CopyNode):
node_dict[node] = CopyNode(node.rank,
node.dimension,
name=node.name,
axis_names=node.axis_names,
backend=node.backend,
dtype=node.dtype)
else:
if conjugate:
node_dict[node] = Node(node.backend.conj(node.tensor),
name=node.name,
axis_names=node.axis_names,
backend=node.backend)
else:
node_dict[node] = Node(node.tensor,
name=node.name,
axis_names=node.axis_names,
backend=node.backend)
edge_dict = {}
for edge in get_all_edges(nodes):
node1 = edge.node1
axis1 = edge.node1.get_axis_number(edge.axis1)
# edge dangling or node2 does not need to be copied
if edge.is_dangling() or edge.node2 not in node_dict:
new_edge = Edge(node_dict[node1], axis1, edge.name)
node_dict[node1].add_edge(new_edge, axis1)
edge_dict[edge] = new_edge
continue
node2 = edge.node2
axis2 = edge.node2.get_axis_number(edge.axis2)
# copy node2 but not node1
if node1 not in node_dict:
new_edge = Edge(node_dict[node2], axis2, edge.name)
node_dict[node2].add_edge(new_edge, axis2)
edge_dict[edge] = new_edge
continue
# both nodes should be copied
new_edge = Edge(node_dict[node1], axis1, edge.name, node_dict[node2],
axis2)
new_edge.set_signature(edge.signature)
node_dict[node2].add_edge(new_edge, axis2)
node_dict[node1].add_edge(new_edge, axis1)
edge_dict[edge] = new_edge
return node_dict, edge_dict
