odify genome for the official release

tensorneat/common/graph.py

@@ -0,0 +1,123 @@
+"""
+Some graph algorithm implemented in jax.
+Only used in feed-forward networks.
+"""
+
+import jax
+from jax import jit, Array, numpy as jnp
+from typing import Tuple, Set, List, Union
+
+from .tools import fetch_first, I_INF
+
+
+@jit
+def topological_sort(nodes: Array, conns: Array) -> Array:
+    """
+    a jit-able version of topological_sort!
+    conns: Array[N, N]
+    """
+
+    in_degree = jnp.where(jnp.isnan(nodes[:, 0]), jnp.nan, jnp.sum(conns, axis=0))
+    res = jnp.full(in_degree.shape, I_INF)
+
+    def cond_fun(carry):
+        res_, idx_, in_degree_ = carry
+        i = fetch_first(in_degree_ == 0.0)
+        return i != I_INF
+
+    def body_func(carry):
+        res_, idx_, in_degree_ = carry
+        i = fetch_first(in_degree_ == 0.0)
+
+        # add to res and flag it is already in it
+        res_ = res_.at[idx_].set(i)
+        in_degree_ = in_degree_.at[i].set(-1)
+
+        # decrease in_degree of all its children
+        children = conns[i, :]
+        in_degree_ = jnp.where(children, in_degree_ - 1, in_degree_)
+        return res_, idx_ + 1, in_degree_
+
+    res, _, _ = jax.lax.while_loop(cond_fun, body_func, (res, 0, in_degree))
+    return res
+
+
+def topological_sort_python(
+    nodes: Union[Set[int], List[int]],
+    conns: Union[Set[Tuple[int, int]], List[Tuple[int, int]]],
+) -> Tuple[List[int], List[List[int]]]:
+    # a python version of topological_sort, use python set to store nodes and conns
+    # returns the topological order of the nodes and the topological layers
+    # written by gpt4 :)
+
+    # Make a copy of the input nodes and connections
+    nodes = nodes.copy()
+    conns = conns.copy()
+
+    # Initialize the in-degree of each node to 0
+    in_degree = {node: 0 for node in nodes}
+
+    # Compute the in-degree for each node
+    for conn in conns:
+        in_degree[conn[1]] += 1
+
+    topo_order = []
+    topo_layer = []
+
+    # Find all nodes with in-degree 0
+    zero_in_degree_nodes = [node for node in nodes if in_degree[node] == 0]
+
+    while zero_in_degree_nodes:
+
+        for node in zero_in_degree_nodes:
+            nodes.remove(node)
+
+        zero_in_degree_nodes = sorted(
+            zero_in_degree_nodes
+        )  # make sure the topo_order is from small to large
+
+        topo_layer.append(zero_in_degree_nodes.copy())
+
+        for node in zero_in_degree_nodes:
+            topo_order.append(node)
+
+            # Iterate over all connections and reduce the in-degree of connected nodes
+            for conn in list(conns):
+                if conn[0] == node:
+                    in_degree[conn[1]] -= 1
+                    conns.remove(conn)
+
+        zero_in_degree_nodes = [node for node in nodes if in_degree[node] == 0]
+
+    # Check if there are still connections left indicating a cycle
+    if conns or nodes:
+        raise ValueError("Graph has at least one cycle, topological sort not possible")
+
+    return topo_order, topo_layer
+
+
+@jit
+def check_cycles(nodes: Array, conns: Array, from_idx, to_idx) -> Array:
+    """
+    Check whether a new connection (from_idx -> to_idx) will cause a cycle.
+    """
+
+    conns = conns.at[from_idx, to_idx].set(True)
+
+    visited = jnp.full(nodes.shape[0], False)
+    new_visited = visited.at[to_idx].set(True)
+
+    def cond_func(carry):
+        visited_, new_visited_ = carry
+        end_cond1 = jnp.all(visited_ == new_visited_)  # no new nodes been visited
+        end_cond2 = new_visited_[from_idx]  # the starting node has been visited
+        return jnp.logical_not(end_cond1 | end_cond2)
+
+    def body_func(carry):
+        _, visited_ = carry
+        new_visited_ = jnp.dot(visited_, conns)
+        new_visited_ = jnp.logical_or(visited_, new_visited_)
+        return visited_, new_visited_
+
+    _, visited = jax.lax.while_loop(cond_func, body_func, (visited, new_visited))
+    return visited[from_idx]