Update package namespace to onnx_ir

.github/workflows/lint.yml

@@ -1,7 +1,3 @@
-# Copyright (c) ONNX Project Contributors
-#
-# SPDX-License-Identifier: Apache-2.0
-
 name: Lint
 
 on:
@@ -67,7 +63,7 @@ jobs:
           if ! lintrunner --force-color --all-files --tee-json=lint.json -v; then
               echo ""
               echo -e "\e[1m\e[36mYou can reproduce these results locally by using \`lintrunner\`.\e[0m"
-              echo -e "\e[1m\e[36mSee https://github.com/microsoft/onnxscript#coding-style for setup instructions.\e[0m"
+              echo -e "\e[1m\e[36mSee https://github.com/onnx/onnx_ir/blob/main/CONTRIBUTING.md for setup instructions.\e[0m"
               exit 1
           fi
       - name: Produce SARIF

.github/workflows/scorecard.yml

@@ -1,7 +1,3 @@
-# Copyright (c) ONNX Project Contributors
-#
-# SPDX-License-Identifier: Apache-2.0
-
 # This workflow uses actions that are not certified by GitHub. They are provided
 # by a third-party and are governed by separate terms of service, privacy
 # policy, and support documentation.

MANIFEST.in

@@ -0,0 +1 @@
+global-exclude *_test.py

REUSE.toml

@@ -1,5 +1,4 @@
 # Copyright (c) ONNX Project Contributors
-#
 # SPDX-License-Identifier: Apache-2.0
 
 version = 1

src/onnx_ir/__init__.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """In-memory intermediate representation for ONNX graphs."""
 
 __all__ = [
@@ -81,11 +81,13 @@
     # IO
     "load",
     "save",
+    # Flags
+    "DEBUG",
 ]
 
-from onnxscript.ir import convenience, external_data, passes, serde, tape, traversal
-from onnxscript.ir._convenience._constructors import node, tensor
-from onnxscript.ir._core import (
+from onnx_ir import convenience, external_data, passes, serde, tape, traversal
+from onnx_ir._convenience._constructors import node, tensor
+from onnx_ir._core import (
     Attr,
     AttrFloat32,
     AttrFloat32s,
@@ -121,12 +123,12 @@
     TypeAndShape,
     Value,
 )
-from onnxscript.ir._enums import (
+from onnx_ir._enums import (
     AttributeType,
     DataType,
 )
-from onnxscript.ir._io import load, save
-from onnxscript.ir._protocols import (
+from onnx_ir._io import load, save
+from onnx_ir._protocols import (
     ArrayCompatible,
     AttributeProtocol,
     DLPackCompatible,
@@ -145,14 +147,16 @@
     TypeProtocol,
     ValueProtocol,
 )
-from onnxscript.ir.serde import TensorProtoTensor, from_onnx_text, from_proto, to_proto
+from onnx_ir.serde import TensorProtoTensor, from_onnx_text, from_proto, to_proto
 
+DEBUG = False
 
 def __set_module() -> None:
     """Set the module of all functions in this module to this public module."""
     global_dict = globals()
     for name in __all__:
-        global_dict[name].__module__ = __name__
-
+        if hasattr(global_dict[name], "__module__"):
+            # Set the module of the function to this module
+            global_dict[name].__module__ = __name__
 
 __set_module()

src/onnx_ir/_convenience/__init__.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """Convenience methods for constructing and manipulating the IR.
 
 This is an internal only module. We should choose to expose some of the methods
@@ -20,7 +20,7 @@
 
 import onnx
 
-from onnxscript.ir import _core, _enums, _protocols, serde
+from onnx_ir import _core, _enums, _protocols, serde
 
 SupportedAttrTypes = Union[
     str,
@@ -188,7 +188,7 @@ def convert_attributes(
     types are: int, float, str, Sequence[int], Sequence[float], Sequence[str],
     :class:`_core.Tensor`, and :class:`_core.Attr`::
 
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> import onnx
         >>> import numpy as np
         >>> attrs = {
@@ -269,7 +269,7 @@ def replace_all_uses_with(
 
     We want to replace the node A with a new node D::
 
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> input = ir.Input("input")
         >>> node_a = ir.Node("", "A", [input])
         >>> node_b = ir.Node("", "B", node_a.outputs)
@@ -355,7 +355,6 @@ def replace_nodes_and_values(
         old_values: The values to replace.
         new_values: The values to replace with.
     """
-
     for old_value, new_value in zip(old_values, new_values):
         # Propagate relevant info from old value to new value
         # TODO(Rama): Perhaps this should be a separate utility function. Also, consider

src/onnx_ir/_convenience/_constructors.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """Convenience constructors for IR objects."""
 
 from __future__ import annotations
@@ -15,12 +15,12 @@
 import numpy as np
 import onnx
 
-from onnxscript.ir import _convenience, _core, _enums, _protocols, serde, tensor_adapters
+from onnx_ir import _convenience, _core, _enums, _protocols, serde, tensor_adapters
 
 if typing.TYPE_CHECKING:
     import numpy.typing as npt
 
-    from onnxscript import ir
+    import onnx_ir as ir
 
 
 def tensor(
@@ -39,7 +39,7 @@ def tensor(
 
     Example::
 
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> import numpy as np
         >>> import ml_dtypes
         >>> import onnx
@@ -162,7 +162,7 @@ def node(
 
     Example::
 
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> input_a = ir.Input("A", shape=ir.Shape([1, 2]), type=ir.TensorType(ir.DataType.INT32))
         >>> input_b = ir.Input("B", shape=ir.Shape([1, 2]), type=ir.TensorType(ir.DataType.INT32))
         >>> node = ir.node(

src/onnx_ir/_convenience/_constructors_test.py

@@ -1,13 +1,13 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """Unit tests for the _constructors module."""
 
 import unittest
 
 import numpy as np
 
-from onnxscript import ir
-from onnxscript.ir._convenience import _constructors
+import onnx_ir as ir
+from onnx_ir._convenience import _constructors
 
 
 class ConstructorsTest(unittest.TestCase):

src/onnx_ir/_core.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """data structures for the intermediate representation."""
 
 # NOTES for developers:
@@ -44,8 +44,8 @@
 import numpy as np
 from typing_extensions import TypeIs
 
-import onnxscript
-from onnxscript.ir import (
+import onnx_ir
+from onnx_ir import (
     _display,
     _enums,
     _graph_containers,
@@ -186,7 +186,7 @@ def display(self, *, page: bool = False) -> None:
 
             status_manager = rich.status.Status(f"Computing tensor stats for {self!r}")
 
-        from onnxscript._thirdparty import (  # pylint: disable=import-outside-toplevel
+        from onnx_ir._thirdparty import (  # pylint: disable=import-outside-toplevel
             asciichartpy,
         )
 
@@ -582,7 +582,7 @@ def __init__(
         # NOTE: Do not verify the location by default. This is because the location field
         # in the tensor proto can be anything and we would like deserialization from
         # proto to IR to not fail.
-        if onnxscript.DEBUG:
+        if onnx_ir.DEBUG:
             if os.path.isabs(location):
                 raise ValueError(
                     "The location must be a relative path. Please specify base_dir as well."
@@ -852,7 +852,7 @@ class LazyTensor(TensorBase, _protocols.TensorProtocol):  # pylint: disable=too-
     Example::
 
         >>> import numpy as np
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> weights = np.array([[1, 2, 3]])
         >>> def create_tensor():  # Delay applying transformations to the weights
         ...     weights_t = weights.transpose()
@@ -1039,7 +1039,7 @@ class Shape(_protocols.ShapeProtocol, _display.PrettyPrintable):
 
     Example::
 
-        >>> from onnxscript import ir
+        >>> import onnx_ir as ir
         >>> shape = ir.Shape(["B", None, 3])
         >>> shape.rank()
         3
@@ -1279,7 +1279,7 @@ def _short_tensor_str_for_node(x: Value) -> str:
 
 
 def _normalize_domain(domain: str) -> str:
-    """Normalize 'ai.onnx' to ''"""
+    """Normalize 'ai.onnx' to ''."""
     return "" if domain == "ai.onnx" else domain
 
 
@@ -1709,7 +1709,7 @@ def dtype(self, value: _enums.DataType) -> None:
 
     @property
     def elem_type(self) -> _enums.DataType:
-        """Return the element type of the tensor type"""
+        """Return the element type of the tensor type."""
         return self.dtype
 
     def __hash__(self) -> int:
@@ -2052,7 +2052,7 @@ def const_value(
         self,
         value: _protocols.TensorProtocol | None,
     ) -> None:
-        if onnxscript.DEBUG:
+        if onnx_ir.DEBUG:
             if value is not None and not isinstance(value, _protocols.TensorProtocol):
                 raise TypeError(
                     f"Expected value to be a TensorProtocol or None, got '{type(value)}'"
@@ -2099,7 +2099,6 @@ def Input(
 
     This is equivalent to calling ``Value(name=name, shape=shape, type=type, doc_string=doc_string)``.
     """
-
     # NOTE: The function name is capitalized to maintain API backward compatibility.
 
     return Value(name=name, shape=shape, type=type, doc_string=doc_string)
@@ -2469,7 +2468,7 @@ def sort(self) -> None:
             ValueError: If the graph contains a cycle, making topological sorting impossible.
         """
         # Obtain all nodes from the graph and its subgraphs for sorting
-        nodes = list(onnxscript.ir.traversal.RecursiveGraphIterator(self))
+        nodes = list(onnx_ir.traversal.RecursiveGraphIterator(self))
         # Store the sorted nodes of each subgraph
         sorted_nodes_by_graph: dict[Graph, list[Node]] = {
             graph: [] for graph in {node.graph for node in nodes if node.graph is not None}
@@ -2858,7 +2857,7 @@ def graphs(self) -> Iterable[Graph]:
         """Get all graphs and subgraphs in the model.
 
         This is a convenience method to traverse the model. Consider using
-        `onnxscript.ir.traversal.RecursiveGraphIterator` for more advanced
+        `onnx_ir.traversal.RecursiveGraphIterator` for more advanced
         traversals on nodes.
         """
         # NOTE(justinchuby): Given
@@ -2868,7 +2867,7 @@ def graphs(self) -> Iterable[Graph]:
         # I created this method as a core method instead of an iterator in
         # `traversal.py`.
         seen_graphs: set[Graph] = set()
-        for node in onnxscript.ir.traversal.RecursiveGraphIterator(self.graph):
+        for node in onnx_ir.traversal.RecursiveGraphIterator(self.graph):
             if node.graph is not None and node.graph not in seen_graphs:
                 seen_graphs.add(node.graph)
                 yield node.graph
@@ -3226,7 +3225,7 @@ def as_strings(self) -> Sequence[str]:
         """Get the attribute value as a sequence of strings."""
         if not isinstance(self.value, Sequence):
             raise TypeError(f"Value of attribute '{self!r}' is not a Sequence.")
-        if onnxscript.DEBUG:
+        if onnx_ir.DEBUG:
             if not all(isinstance(x, str) for x in self.value):
                 raise TypeError(f"Value of attribute '{self!r}' is not a Sequence of strings.")
         # Create a copy of the list to prevent mutation
@@ -3236,7 +3235,7 @@ def as_tensors(self) -> Sequence[_protocols.TensorProtocol]:
         """Get the attribute value as a sequence of tensors."""
         if not isinstance(self.value, Sequence):
             raise TypeError(f"Value of attribute '{self!r}' is not a Sequence.")
-        if onnxscript.DEBUG:
+        if onnx_ir.DEBUG:
             if not all(isinstance(x, _protocols.TensorProtocol) for x in self.value):
                 raise TypeError(f"Value of attribute '{self!r}' is not a Sequence of tensors.")
         # Create a copy of the list to prevent mutation
@@ -3246,7 +3245,7 @@ def as_graphs(self) -> Sequence[Graph]:
         """Get the attribute value as a sequence of graphs."""
         if not isinstance(self.value, Sequence):
             raise TypeError(f"Value of attribute '{self!r}' is not a Sequence.")
-        if onnxscript.DEBUG:
+        if onnx_ir.DEBUG:
             if not all(isinstance(x, Graph) for x in self.value):
                 raise TypeError(f"Value of attribute '{self!r}' is not a Sequence of graphs.")
         # Create a copy of the list to prevent mutation

src/onnx_ir/_core_test.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 from __future__ import annotations
 
 import copy
@@ -15,8 +15,8 @@
 import parameterized
 import torch
 
-from onnxscript import ir
-from onnxscript.ir import _core
+import onnx_ir as ir
+from onnx_ir import _core
 
 
 class TensorTest(unittest.TestCase):

src/onnx_ir/_display.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """Internal utilities for displaying the intermediate representation of a model.
 
 NOTE: All third-party imports should be scoped and imported only when used to avoid

src/onnx_ir/_display_test.py

@@ -1,13 +1,13 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """Test display() methods in various classes."""
 
 import contextlib
 import unittest
 
 import numpy as np
 
-import onnxscript.ir as ir
+import onnx_ir as ir
 
 
 class DisplayTest(unittest.TestCase):

src/onnx_ir/_enums.py

@@ -1,5 +1,5 @@
-# Copyright (c) Microsoft Corporation.
-# Licensed under the MIT License.
+# Copyright (c) ONNX Project Contributors
+# SPDX-License-Identifier: Apache-2.0
 """ONNX IR enums that matches the ONNX spec."""
 
 from __future__ import annotations