Document changes between versions in docstrings

src/onnx_ir/_convenience/__init__.py

@@ -323,6 +323,9 @@ def create_value_mapping(graph: _core.Graph) -> dict[str, _core.Value]:
     and the first value with that name is returned. Values with empty names
     are excluded from the mapping.
 
+    .. versionchanged:: 0.1.2
+        Values from subgraphs are now included in the mapping.
+
     Args:
         graph: The graph to extract the mapping from.
 
@@ -410,6 +413,8 @@ def get_const_tensor(
     it will propagate the shape and type of the constant tensor to the value
     if `propagate_shape_type` is set to True.
 
+    .. versionadded:: 0.1.2
+
     Args:
         value: The value to get the constant tensor from.
         propagate_shape_type: If True, the shape and type of the value will be

src/onnx_ir/_core.py

@@ -964,7 +964,10 @@ def tobytes(self) -> bytes:
 
 
 class PackedTensor(TensorBase, _protocols.TensorProtocol, Generic[TArrayCompatible]):  # pylint: disable=too-many-ancestors
-    """A tensor that stores 4bit datatypes in packed format."""
+    """A tensor that stores 4bit datatypes in packed format.
+
+    .. versionadded:: 0.1.2
+    """
 
     __slots__ = (
         "_dtype",
@@ -2335,6 +2338,12 @@ class Graph(_protocols.GraphProtocol, Sequence[Node], _display.PrettyPrintable):
     seen as a Sequence of nodes and should be used as such. For example, to obtain
     all nodes as a list, call ``list(graph)``.
 
+    .. versionchanged:: 0.1.1
+        Values with non-none producers will be rejected as graph inputs or initializers.
+
+    .. versionadded:: 0.1.1
+        Added ``add`` method to initializers and attributes.
+
     Attributes:
         name: The name of the graph.
         inputs: The input values of the graph.
@@ -2545,12 +2554,17 @@ def all_nodes(self) -> Iterator[Node]:
         Consider using
         :class:`onnx_ir.traversal.RecursiveGraphIterator` for more advanced
         traversals on nodes.
+
+        .. versionadded:: 0.1.2
         """
         # NOTE: This is a method specific to Graph, not required by the protocol unless proven
         return onnx_ir.traversal.RecursiveGraphIterator(self)
 
     def subgraphs(self) -> Iterator[Graph]:
-        """Get all subgraphs in the graph in O(#nodes + #attributes) time."""
+        """Get all subgraphs in the graph in O(#nodes + #attributes) time.
+
+        .. versionadded:: 0.1.2
+        """
         seen_graphs: set[Graph] = set()
         for node in onnx_ir.traversal.RecursiveGraphIterator(self):
             graph = node.graph
@@ -3216,12 +3230,17 @@ def all_nodes(self) -> Iterator[Node]:
         Consider using
         :class:`onnx_ir.traversal.RecursiveGraphIterator` for more advanced
         traversals on nodes.
+
+        .. versionadded:: 0.1.2
         """
         # NOTE: This is a method specific to Graph, not required by the protocol unless proven
         return onnx_ir.traversal.RecursiveGraphIterator(self)
 
     def subgraphs(self) -> Iterator[Graph]:
-        """Get all subgraphs in the function in O(#nodes + #attributes) time."""
+        """Get all subgraphs in the function in O(#nodes + #attributes) time.
+
+        .. versionadded:: 0.1.2
+        """
         seen_graphs: set[Graph] = set()
         for node in onnx_ir.traversal.RecursiveGraphIterator(self):
             graph = node.graph

src/onnx_ir/_enums.py

@@ -120,6 +120,8 @@ def itemsize(self) -> float:
     def bitwidth(self) -> int:
         """Returns the bit width of the data type.
 
+        .. versionadded:: 0.1.2
+
         Raises:
             TypeError: If the data type is not supported.
         """

src/onnx_ir/passes/common/common_subexpression_elimination.py

@@ -19,6 +19,11 @@
 class CommonSubexpressionEliminationPass(ir.passes.InPlacePass):
     """Eliminate common subexpression in ONNX graphs.
 
+    .. versionadded:: 0.1.1
+
+    .. versionchanged:: 0.1.3
+        Constant nodes with values smaller than ``size_limit`` will be CSE'd.
+
     Attributes:
         size_limit: The maximum size of the tensor to be csed. If the tensor contains
             number of elements larger than size_limit, it will not be cse'd. Default is 10.

src/onnx_ir/passes/common/initializer_deduplication.py

@@ -20,6 +20,8 @@ class DeduplicateInitializersPass(ir.passes.InPlacePass):
 
     To deduplicate initializers from subgraphs, use :class:`~onnx_ir.passes.common.LiftSubgraphInitializersToMainGraphPass`
     to lift the initializers to the main graph first before running pass.
+
+    .. versionadded:: 0.1.3
     """
 
     def __init__(self, size_limit: int = 1024):

src/onnx_ir/serde.py

@@ -200,6 +200,9 @@ def from_onnx_text(
 
     Read more about the textual representation at: https://onnx.ai/onnx/repo-docs/Syntax.html
 
+    .. versionchanged:: 0.1.2
+        Added the ``initializers`` argument.
+
     Args:
         model_text: The ONNX textual representation of the model.
         initializers: Tensors to be added as initializers. If provided, these tensors
@@ -237,6 +240,8 @@ def to_onnx_text(
 ) -> str:
     """Convert the IR model to the ONNX textual representation.
 
+    .. versionadded:: 0.1.2
+
     Args:
         model: The IR model to convert.
         exclude_initializers: If True, the initializers will not be included in the output.