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ONNX GraphSurgeon Change Log

Dates are in YYYY-MM-DD format.

v0.5.2 (2024-04-01)

Added

  • Added export_dtype field to gs.Constant to allow numpy-unsupported dtypes such as BFloat16.

v0.5.1 (2024-02-23)

Changed

  • Removed dependency on typing_extensions package.
  • Improved error messages when a function registered with a graph is not registered for the current opset.

v0.5.0 (2024-01-12)

Added

  • Added a GraphPattern API which can be used to find matching subgraphs in a graph.

v0.4.1 (2023-11-30)

Fixed

  • Fixed a bug where toposort would not correctly memoize intermediate values, leading to long runtimes.
  • Fixed a bug where export_value_info_proto would not handle constant tensors correctly.

v0.4.0 (2023-08-16)

Added

  • Added Function class representing a Graph implementing a Custom Op.
  • Added functions field to Graph
  • Added Node.AttributeRef dataclass representing an attribute value in a parent Function.
  • Added subgraph() methods to Node and Graph to iterate over the node's/graph's subgraphs.
  • Added new kwargs to Graph.cleanup(), Graph.fold_constants(), and Graph.toposort() to optionally recurse into the Graph's Functions.
  • Added 'mode' kwarg to Graph.toposort() to control whether nodes, functions, or both get sorted.
  • Added example 11 which demonstrates how to use Functions

Removed

  • Removed do_type_check kwarg from OnnxExporter.export_node()

Fixed

  • Fixed some warnings caused by using deprecated APIs in onnx.mapping.

v0.3.29 (2023-08-11)

Fixed

  • Fixed a bug where doing a copy (e.g. copy.copy) of node/tensor inputs/outputs would retain their synchronization behavior. For example, for a graph like: 
    inp -> node -> out
    Doing: 
    node_outputs = copy.copy(node.outputs)
del node_outputs[0]
    would have previously resulted in out.inputs being modified also.

v0.3.28 (2023-07-11)

Added

  • Added support for various 8-bit floating point types. Like BFLOAT16, these will not be converted to NumPy data types.

Fixed

  • Fixed a bug in fold_constants where nodes with omitted optional inputs would not be folded even if all their other inputs were constant.

v0.3.27 (2023-05-24)

Added

  • Added support for BFLOAT16. Tensors of BFLOAT16 type will not have their data types converted to NumPy. Additionally, attempting to access the values of a BFLOAT16 constant tensor will cause them to be casted to float32.

Changed

  • Updated the Graph.layer API to generate unique names for Tensors and Nodes.
  • Updated the exporter to provide a warning before exporting to ONNX if nodes within a graph have duplicate names.
  • Updated all dtype attributes to accept onnx.TensorProto.DataType types in addition to NumPy types. This is required since some types, like BFLOAT16 are not representable in NumPy.

v0.3.26 (2022-12-09)

Fixed

  • Fixed a bug where node domain was not preserved.

v0.3.25 (2022-10-14)

Added

  • Added a should_exclude_node parameter to fold_constants to allow for excluding nodes from constant folding.

Fixed

  • Fixed a bug where fold_constants would fold quantization nodes, which are intended to be executed at runtime even though they are computable beforehand.

v0.3.24 (2022-08-31)

Fixed

  • Fixed a bug where fold_constants would not work at all when onnxruntime was not installed. Now, fold_constants can still partially fold the graph even when onnxruntime is not available.

v0.3.23 (2022-08-24)

Fixed

  • Fixed a bug in fold_constants where shape tensor cast elision would not work correctly if one input of a binary op was produced by a constant node and had a data type that differed from that of the other input prior to the cast. For example, a pattern like this would have previously failed, but now works as expected: 
    inp (int32)            Constant
    |                     |
Cast (to=float32)   constant_out (float32)
               \       /
                  Sub
                   |
             Cast (to=int32)
  • Fixed a bug where shape-tensor cast elision would invalidate the graph if the original casted inputs were being used as graph outputs or by other nodes.

v0.3.22 (2022-08-22)

Changed

  • Updated fold_constants to issue clearer warnings and avoid evaluating tensors which exceed the size threshold.

v0.3.21 (2022-08-19)

Added

  • Added a size_threshold option in fold_constants which allows for disabling constant folding for nodes which would generate tensors larger than the given size.

v0.3.20 (2022-07-12)

Fixed

  • Fixed a bug where shape tensor cast elision would sometimes fail when the Cast input had a type of int64.
  • Fixed a bug where opset information would not be propagated down to nested graphs.

v0.3.19 (2022-04-13)

Added

  • Added support for flattening conditional subgraphs into the parent graph in fold_constants().

v0.3.18 (2022-03-31)

Fixed

  • Fixed a bug where {node/tensor}.{inputs/outputs} += <value> would cause the inputs/outputs of the node/tensor to be cleared.

v0.3.17 (2022-03-18)

Added

  • Added producer_name and producer_version to Graph class so that they are preserved during model import/export.

v0.3.16 (2022-02-23)

Fixed

  • Fixed a bug where Graph.fold_constants() was not providing a value for the providers parameter in onnxruntime.InferenceSession.

v0.3.15 (2022-01-18)

Fixed

  • Fixed a bug where Graph.toposort() would not consider implicit inputs of nodes with subgraphs. For example, a graph including an If node whose subgraphs used tensors from the outer graph may previously have been sorted such that it occurred before the nodes producing those tensors.

v0.3.14 (2021-10-14)

Fixed

  • Fixed a bug where numpy.dtype would not be exported correctly when specified as a node attribute.

v0.3.13 (2021-09-21)

Added

  • Graph.tensors() will now display a warning when duplicate tensors are detected in the graph, even if check_duplicates=False. As before, when check_duplicates=True, it will throw an exception in such cases.

v0.3.12 (2021-08-24)

Added

  • Added support for Cast elision in fold_constants().

v0.3.11 (2021-07-14)

Changed

  • Updated fold_constants() so that it no longer fails if a shape folding pass fails when error_ok is True.

Fixed

  • Fixed a bug where fold_constants() would fail if a model contained a Slice node without a starts or ends input.

v0.3.10 (2021-05-20)

Added

  • Added support for folding Shape -> Slice patterns even when the entire shape may not be known.

v0.3.9 (2021-04-20)

Changed

  • fold_constants() will no longer store values for foldable tensors whose outputs are all foldable. For example, while folding a constant subgraph like A (constant) -> B -> C, previously, B values would be computed in addition to C. With these changes, only C values are computed and stored. This can reduce memory usage significantly.

v0.3.8 (2021-04-15)

Fixed

  • Fixed a bug where copy() would not work with subgraphs that included tensors with the same names as outer graph tensors unless a tensor_map was provided.

v0.3.7 (2021-03-31)

Added

  • fold_constants() can now fold Shape -> Gather patterns even when the entire shape may not be known.
  • Added an error_ok parameter in fold_constants() which can be set to False to re-raise errors encountered during inference.

Fixed

  • Fixed a bug where copy() would not correctly copy tensors in nested graphs.
  • Fixed a bug where fold_constants() would attempt to fold nodes including graph attributes even if nodes within the nested graph could not be folded.

v0.3.6 (2021-03-27)

Fixed

  • fold_constants() no longer loads constant values into numpy arrays. This can save a significant amount of memory.
  • cleanup() will no longer remove unused graph inputs by default - this was causing invalid ONNX models to be generated in cases with Loop nodes. Set remove_unused_graph_inputs to True to revert to the old behavior.
  • cleanup() will no longer reorder node inputs in cases where they are also graph outputs.

v0.3.5 (2021-03-24)

Added

  • Added support for models with externally stored data. See the README for details on how to import and export such models.

Fixed

  • Operator domains are now preserved when exporting graphs to ONNX.

v0.3.4 (2021-03-10)

Fixed

  • fold_constants will no longer attempt to run inference if there are no constants to compute.

v0.3.3 (2021-03-04)

Fixed

  • Fixed a bug in fold_constants where it would fail if ONNX-Runtime could not run a node with constant inputs. In such cases, the graph is now partitioned to exclude the node before running another pass of constant folding.
  • Fixed a bug where graph output tensors would still point to consumer nodes that had been removed from the graph.
  • Constant folding is now significantly faster in models with large weights.

v0.3.2 (2021-02-13)

Added

  • Added support for folding Shape nodes in fold_constants. This requires that shape inference has been run on the graph, and that the input to the Shape node has a static shape. This behavior can be disabled by setting fold_shapes=False.

Changed

  • cleanup, toposort, and fold_constants are now recursively applied to subgraphs by default. This behavior can be disabled by setting recurse_subgraphs=False.

v0.3.1 (2021-02-12)

Fixed

  • Fixed a bug where do_type_check would not propagate to subgraphs.
  • Fixed a bug where cleanup() would incorrectly remove outer-level nodes if they were used only by inner-nodes of subgraphs.

Removed

  • Removed __deepcopy__ from Graph as it wasn't deep-copying weights or attributes. The method is now called copy and makes a shallow copy of everything except Nodes and Tensor instances.

v0.3.0 (2021-02-12)

Fixed

  • Fixed a bug where shapes including empty strings for dim_param would be treated as empty tensors. They are now correctly imported as tensors with dynamic shapes.
  • Fixed a bug where variable tensors with unknown shapes would be imported as scalars.

v0.2.9 (2021-02-01)

Changed

  • The values property of Constant tensors is now lazily loaded. This can greatly improve model loading times.

v0.2.8 (2020-10-08)

Fixed

  • Fixed a bug where graph inputs and outputs could be assigned SynchronizedList instances, and would therefore be modified if nodes in the graph were.

v0.2.7 (2020-09-29)

Changed

  • Changed the default value of remove_unused_node_outputs in cleanup() to False, as a value of True can lead to unintuitive behavior, especially with looping constructs like Scan and Loop.

v0.2.6 (2020-09-25)

Fixed

  • Fixed a bug where calling graph.tensors() would cause the inputs or outputs of some tensors to be modified.

Changed

  • SynchronizedList.__add__() no longer modifies the left operand.

v0.2.5 (2020-09-21)

Fixed

  • Fixed a bug where nodes including subgraphs whose inputs/outputs had the same names as the node's inputs/outputs would not be imported correctly.

v0.2.4 (2020-09-14)

Fixed

  • fold_constants() will no longer fail if there is nothing to fold in the graph
  • cleanup() will now properly remove the producer nodes of graph inputs.
  • Fixed a bug where graph input/output tensors not attached to nodes would not be correctly exported.

v0.2.3 (2020-06-17)

Added

  • Graph.register() now accepts an opsets argument so that functions can be registered for specific opsets.

Removed

  • has_metadata has been removed from Tensor, since the function is no longer used.

v0.2.2 (2020-06-17)

Fixed

  • ONNX GraphSurgeon now enforces the constraint that graph inputs/outputs must include type information.
  • Fixed a bug where opset was not being considering when running inference for constant folding.

v0.2.1 (2020-06-10)

Added

  • Added layer() function to Graph to make it easier to generate models from scratch
  • Added i() and o() convenience functions to Tensor, which are similar to the functions for Node, but return Tensors instead of Nodes

v0.2.0 (2020-04-15)

Added

  • Added an examples directory
  • Added has_metadata() to Tensor classes to determine if dtype/shape are known.
  • Added a check_duplicates parameter to Graph.tensors() to make it easy to check for duplicate tensors in the graph.

Changed

  • Various improvements to the logger
  • Updated OnnxImporter so that it can correctly import shapes and types from an ONNX graph after shape inference.
  • Made Tensor an abstract class - all tensors in a graph are now either Variable or Constant
  • Renames generate_tensor_map() to tensors() in Graph
  • Removed Tensor suffix from Tensor classes.

v0.1.3 (2020-02-26)

Fixed

  • The import_onnx and export_onnx functions will now preserve opset information and dim_param values in shapes.

v0.1.2 (2020-02-19)

Added

  • Added i() and o() convenience functions to Node for retrieving input/output nodes.
  • Added fold_constants() to Graph to allow for folding constants in the graph.
  • Added __deepcopy__() to Graph.
  • Added to_constant() and to_variable() functions to Variable and Constant respectively to transmute them in-place.

v0.1.1 (2020-02-11)

Changed

  • Removed some type annotations to allow compatibility with Python 3.5.

v0.1.0 (2020-02-11)

Added

  • Added Node, Tensor and Graph classes.
  • Added BaseImporter and OnnxImporter classes.
  • Added support for importing initializers in the OnnxImporter
  • Added Variable and Constant
  • Consolidates inputs/outputs of Nodes/Tensors. Now, inputs/outputs should generally only be added to Nodes.
  • Added OnnxExporter to export Graph to onnx.GraphProto
  • Added OnnxExporter and OnnxImporter to public imports
  • Added toposort function to Graph, which will topologically sort it.
  • Added cleanup function to Graph, which will remove unused nodes and tensors.
  • Added high-level API for importing/exporting Graphs from/to ONNX models.
  • Graphs are now generated with a default name of onnx_graphsurgeon