Add support for combined iterator lineage

backend/src/api/api.py

@@ -2,6 +2,7 @@
 
 import importlib
 import os
+import typing
 from dataclasses import asdict, dataclass, field
 from typing import (
     Any,
@@ -149,10 +150,10 @@ def to_list(x: list[S] | S | None) -> list[S]:
         iterator_inputs = to_list(iterator_inputs)
         iterator_outputs = to_list(iterator_outputs)
 
-        if kind == "collector":
-            assert len(iterator_inputs) == 1 and len(iterator_outputs) == 0
-        elif kind == "newIterator":
+        if kind == "generator":  # Generator
             assert len(iterator_inputs) == 0 and len(iterator_outputs) == 1
+        elif kind == "collector":
+            assert len(iterator_inputs) == 1 and len(iterator_outputs) == 0
         else:
             assert len(iterator_inputs) == 0 and len(iterator_outputs) == 0
 
@@ -188,8 +189,8 @@ def inner_wrapper(wrapped_func: T) -> T:
                 inputs=p_inputs,
                 group_layout=group_layout,
                 outputs=p_outputs,
-                iterator_inputs=iterator_inputs,
-                iterator_outputs=iterator_outputs,
+                iterable_inputs=iterator_inputs,
+                iterable_outputs=iterator_outputs,
                 key_info=key_info,
                 suggestions=suggestions or [],
                 side_effects=side_effects,
@@ -511,25 +512,25 @@ def add_package(
 
 
 @dataclass
-class Iterator(Generic[I]):
-    iter_supplier: Callable[[], Iterable[I | Exception]]
+class Generator(Generic[I]):
+    gen_supplier: Callable[[], typing.Generator[I | Exception, None, None]]
     expected_length: int
     fail_fast: bool = True
 
     @staticmethod
     def from_iter(
-        iter_supplier: Callable[[], Iterable[I | Exception]],
+        gen_supplier: Callable[[], typing.Generator[I | Exception, None, None]],
         expected_length: int,
         fail_fast: bool = True,
-    ) -> Iterator[I]:
-        return Iterator(iter_supplier, expected_length, fail_fast=fail_fast)
+    ) -> Generator[I]:
+        return Generator(gen_supplier, expected_length, fail_fast=fail_fast)
 
     @staticmethod
     def from_list(
         l: list[L], map_fn: Callable[[L, int], I], fail_fast: bool = True
-    ) -> Iterator[I]:
+    ) -> Generator[I]:
         """
-        Creates a new iterator from a list that is mapped using the given
+        Creates a new generator from a list that is mapped using the given
         function. The iterable will be equivalent to `map(map_fn, l)`.
         """
 
@@ -540,14 +541,14 @@ def supplier():
                 except Exception as e:
                     yield e
 
-        return Iterator(supplier, len(l), fail_fast=fail_fast)
+        return Generator(supplier, len(l), fail_fast=fail_fast)
 
     @staticmethod
     def from_range(
         count: int, map_fn: Callable[[int], I], fail_fast: bool = True
-    ) -> Iterator[I]:
+    ) -> Generator[I]:
         """
-        Creates a new iterator the given number of items where each item is
+        Creates a new generator the given number of items where each item is
         lazily evaluated. The iterable will be equivalent to `map(map_fn, range(count))`.
         """
         assert count >= 0
@@ -559,7 +560,7 @@ def supplier():
                 except Exception as e:
                     yield e
 
-        return Iterator(supplier, count, fail_fast=fail_fast)
+        return Generator(supplier, count, fail_fast=fail_fast)
 
 
 N = TypeVar("N")

backend/src/api/node_data.py

@@ -136,8 +136,8 @@ class NodeData:
     outputs: list[BaseOutput]
     group_layout: list[InputId | NestedIdGroup]
 
-    iterator_inputs: list[IteratorInputInfo]
-    iterator_outputs: list[IteratorOutputInfo]
+    iterable_inputs: list[IteratorInputInfo]
+    iterable_outputs: list[IteratorOutputInfo]
 
     key_info: KeyInfo | None
     suggestions: list[SpecialSuggestion]
@@ -150,11 +150,11 @@ class NodeData:
     run: RunFn
 
     @property
-    def single_iterator_input(self) -> IteratorInputInfo:
-        assert len(self.iterator_inputs) == 1
-        return self.iterator_inputs[0]
+    def single_iterable_input(self) -> IteratorInputInfo:
+        assert len(self.iterable_inputs) == 1
+        return self.iterable_inputs[0]
 
     @property
-    def single_iterator_output(self) -> IteratorOutputInfo:
-        assert len(self.iterator_outputs) == 1
-        return self.iterator_outputs[0]
+    def single_iterable_output(self) -> IteratorOutputInfo:
+        assert len(self.iterable_outputs) == 1
+        return self.iterable_outputs[0]

backend/src/api/types.py

@@ -10,4 +10,4 @@
 
 RunFn = Callable[..., Any]
 
-NodeKind = Literal["regularNode", "newIterator", "collector"]
+NodeKind = Literal["regularNode", "generator", "collector"]

backend/src/chain/cache.py

@@ -7,7 +7,7 @@
 
 from api import NodeId
 
-from .chain import Chain, Edge, FunctionNode, NewIteratorNode
+from .chain import Chain, Edge, FunctionNode, GeneratorNode
 
 
 class CacheStrategy:
@@ -54,9 +54,9 @@ def any_are_iterated(out_edges: list[Edge]) -> bool:
         else:
             # the node is NOT implicitly iterated
 
-            if isinstance(node, NewIteratorNode):
+            if isinstance(node, GeneratorNode):
                 # we only care about non-iterator outputs
-                iterator_output = node.data.single_iterator_output
+                iterator_output = node.data.single_iterable_output
                 out_edges = [
                     out_edge
                     for out_edge in out_edges

backend/src/chain/chain.py

@@ -28,12 +28,12 @@ def has_side_effects(self) -> bool:
         return self.data.side_effects
 
 
-class NewIteratorNode:
+class GeneratorNode:
     def __init__(self, node_id: NodeId, schema_id: str):
         self.id: NodeId = node_id
         self.schema_id: str = schema_id
         self.data: NodeData = registry.get_node(schema_id)
-        assert self.data.kind == "newIterator"
+        assert self.data.kind == "generator"
 
     def has_side_effects(self) -> bool:
         return self.data.side_effects
@@ -50,7 +50,7 @@ def has_side_effects(self) -> bool:
         return self.data.side_effects
 
 
-Node = Union[FunctionNode, NewIteratorNode, CollectorNode]
+Node = Union[FunctionNode, GeneratorNode, CollectorNode]
 
 
 @dataclass(frozen=True)
@@ -176,28 +176,28 @@ def visit(node_id: NodeId):
 
         return result
 
-    def get_parent_iterator_map(self) -> dict[FunctionNode, NewIteratorNode | None]:
+    def get_parent_iterator_map(self) -> dict[FunctionNode, GeneratorNode | None]:
         """
         Returns a map of all function nodes to their parent iterator node (if any).
         """
-        iterator_cache: dict[FunctionNode, NewIteratorNode | None] = {}
+        iterator_cache: dict[FunctionNode, GeneratorNode | None] = {}
 
-        def get_iterator(r: FunctionNode) -> NewIteratorNode | None:
+        def get_iterator(r: FunctionNode) -> GeneratorNode | None:
             if r in iterator_cache:
                 return iterator_cache[r]
 
-            iterator: NewIteratorNode | None = None
+            iterator: GeneratorNode | None = None
 
             for in_edge in self.edges_to(r.id):
                 source = self.nodes[in_edge.source.id]
                 if isinstance(source, FunctionNode):
                     iterator = get_iterator(source)
                     if iterator is not None:
                         break
-                elif isinstance(source, NewIteratorNode):
+                elif isinstance(source, GeneratorNode):
                     if (
                         in_edge.source.output_id
-                        in source.data.single_iterator_output.outputs
+                        in source.data.single_iterable_output.outputs
                     ):
                         iterator = source
                         break

backend/src/chain/json.py

@@ -11,7 +11,7 @@
     EdgeSource,
     EdgeTarget,
     FunctionNode,
-    NewIteratorNode,
+    GeneratorNode,
 )
 
 
@@ -53,8 +53,8 @@ def parse_json(json: list[JsonNode]) -> Chain:
     index_edges: list[IndexEdge] = []
 
     for json_node in json:
-        if json_node["nodeType"] == "newIterator":
-            node = NewIteratorNode(json_node["id"], json_node["schemaId"])
+        if json_node["nodeType"] == "generator":
+            node = GeneratorNode(json_node["id"], json_node["schemaId"])
         elif json_node["nodeType"] == "collector":
             node = CollectorNode(json_node["id"], json_node["schemaId"])
         else:

backend/src/packages/chaiNNer_ncnn/ncnn/batch_processing/load_models.py

@@ -5,7 +5,7 @@
 
 from sanic.log import logger
 
-from api import Iterator, IteratorOutputInfo
+from api import Generator, IteratorOutputInfo
 from nodes.impl.ncnn.model import NcnnModelWrapper
 from nodes.properties.inputs import BoolInput, DirectoryInput
 from nodes.properties.outputs import (
@@ -46,12 +46,12 @@
         ),
     ],
     iterator_outputs=IteratorOutputInfo(outputs=[0, 2, 3, 4]),
-    kind="newIterator",
+    kind="generator",
 )
 def load_models_node(
     directory: Path,
     fail_fast: bool,
-) -> tuple[Iterator[tuple[NcnnModelWrapper, str, str, int]], Path]:
+) -> tuple[Generator[tuple[NcnnModelWrapper, str, str, int]], Path]:
     logger.debug(f"Iterating over models in directory: {directory}")
 
     def load_model(filepath_pairs: tuple[Path, Path], index: int):
@@ -82,4 +82,4 @@ def load_model(filepath_pairs: tuple[Path, Path], index: int):
 
     model_files = list(zip(param_files, bin_files))
 
-    return Iterator.from_list(model_files, load_model, fail_fast), directory
+    return Generator.from_list(model_files, load_model, fail_fast), directory

backend/src/packages/chaiNNer_onnx/onnx/batch_processing/load_models.py

@@ -5,7 +5,7 @@
 
 from sanic.log import logger
 
-from api import Iterator, IteratorOutputInfo
+from api import Generator, IteratorOutputInfo
 from nodes.impl.onnx.model import OnnxModel
 from nodes.properties.inputs import BoolInput, DirectoryInput
 from nodes.properties.outputs import (
@@ -46,12 +46,12 @@
         ),
     ],
     iterator_outputs=IteratorOutputInfo(outputs=[0, 2, 3, 4]),
-    kind="newIterator",
+    kind="generator",
 )
 def load_models_node(
     directory: Path,
     fail_fast: bool,
-) -> tuple[Iterator[tuple[OnnxModel, str, str, int]], Path]:
+) -> tuple[Generator[tuple[OnnxModel, str, str, int]], Path]:
     logger.debug(f"Iterating over models in directory: {directory}")
 
     def load_model(path: Path, index: int):
@@ -63,4 +63,4 @@ def load_model(path: Path, index: int):
     supported_filetypes = [".onnx"]
     model_files = list_all_files_sorted(directory, supported_filetypes)
 
-    return Iterator.from_list(model_files, load_model, fail_fast), directory
+    return Generator.from_list(model_files, load_model, fail_fast), directory

backend/src/packages/chaiNNer_pytorch/pytorch/iteration/load_models.py

@@ -6,7 +6,7 @@
 from sanic.log import logger
 from spandrel import ModelDescriptor
 
-from api import Iterator, IteratorOutputInfo, NodeContext
+from api import Generator, IteratorOutputInfo, NodeContext
 from nodes.properties.inputs import DirectoryInput
 from nodes.properties.inputs.generic_inputs import BoolInput
 from nodes.properties.outputs import DirectoryOutput, NumberOutput, TextOutput
@@ -43,14 +43,14 @@
         ),
     ],
     iterator_outputs=IteratorOutputInfo(outputs=[0, 2, 3, 4]),
-    kind="newIterator",
+    kind="generator",
     node_context=True,
 )
 def load_models_node(
     context: NodeContext,
     directory: Path,
     fail_fast: bool,
-) -> tuple[Iterator[tuple[ModelDescriptor, str, str, int]], Path]:
+) -> tuple[Generator[tuple[ModelDescriptor, str, str, int]], Path]:
     logger.debug(f"Iterating over models in directory: {directory}")
 
     def load_model(path: Path, index: int):
@@ -62,4 +62,4 @@ def load_model(path: Path, index: int):
     supported_filetypes = [".pt", ".pth", ".ckpt", ".safetensors"]
     model_files: list[Path] = list_all_files_sorted(directory, supported_filetypes)
 
-    return Iterator.from_list(model_files, load_model, fail_fast), directory
+    return Generator.from_list(model_files, load_model, fail_fast), directory