ONNX v1.6 is now available! We would like to thank everybody who has contributed to this release! You may learn more about the project, who is involved and what tools are available at the onnx.ai site.

Changelog

Major changes and updates since the v1.5.0 release:

Graph representation

• Sequence and map types are now available in ONNX (previously only available in ONNX-ML). (#2249)
• Sparse tensor support has been added. It should significantly reduce the storage size for models with many zero weights. See here for example usage. (#2019)
• ONNX IR version updated to version 6 to reflect support for new types.

Operators

• Opset has been updated to version 11
• New operators:
  • BitShift (#1931)
  • CumSum (#2030)
  • Det (#2233)
  • DynamicQuantizeLinear (#2187)
  • GatherElements (#2143)
  • GatherND (#2106)
  • Range (#2242)
  • Round (#2053)
  • ScatterElements (#2143)
  • ScatterND (#2220)
  • Unique (#2141)
• New sequence-based operators: (#2249)
  • ConcatFromSequence
  • SequenceAt
  • SequenceConstruct
  • SequenceEmpty
  • SequenceErase
  • SequenceInsert
  • SequenceLength
  • SplitToSequence
• Negative axis support added for operators: (#2281)
  • Argmax
  • Argmin
  • Compress
  • Concat
  • Flatten
  • Hardmax
  • LogSoftmax
  • OneHot
  • ReduceL1
  • ReduceL2
  • ReduceLogSum
  • ReduceLogSumExp
  • ReduceMax
  • ReduceMean
  • ReduceMin
  • ReduceProd
  • ReduceSum
  • ReduceSumSquare
  • Scan
  • Slice
  • Softmax
  • Split
  • Squeeze
  • TopK
  • Unsqueeze
• Updated documentation for default stride and dilation attributes for operators: (#2291)
  • AveragePool
  • Conv
  • ConvTranspose
  • LpPool
  • MaxPool
  • MaxUnpool
  • Pad
• Updated operators:
  • Clip - min and max attributes changed to inputs (#2096)
  • Constant - added sparse tensor support (#2019)
  • DepthToSpace - added column-row-depth order mode (#2163)
  • Equal - expanded input tensor type to include all numerical types (#2176)
  • Gemm - marked input bias tensor C as optional (#2330)
  • Loop - allow zero variadic inputs (#1889)
  • Resize - added cubic interpolation mode, sizes input parameter, and coordinate_transformation, cubic_coeff_a and exclude_outside attributes. (#2057)
• Deprecated operators:
  • Scatter has been deprecated in favor for ScatterElements (#2143)
• Many reference implementations have been added to improve clarity of operator behaviour. For example, see here for the reference implementation of Reshape, and here for how to use the reference to generate test data.
• The process of proposing and adding new operator is fully documented in #2172.

Bug Fixes

• Fix resize shape inference issue in opset10 (#2294)
• Fix extra collect_snippets warning (#2307)
• Fix link to community docs in readme (#2261)
• Fix segfault in tile shape inference (#2221)
• Fix errors in RoiAlign shape inference code (#2167)
• Fix globalpool output shape (#2147)
• Fix inconsistency in describing graph's initializer (#2115)
• Fix NN defs file (#2083)
• Fix torchvision installation (#2054)
• Fix torchvision installation (#2054)
• Fix bug that kernel_shape rather than effective_kernel_shape is used in dilated conv (#2043)
• Fix auto_pad shape inference bug (#2028)
• fix macro ONNX_DISALLOW_COPY_AND_ASSIGN bug (#2017)
• Fix shape inference logic for TopK operator (#2005)
• Fix a shapeinference bug in upsample v9/10 (#1969)

Installation

You can simply pip upgrade using the following command or build from source following the instructions on Github.

pip install onnx --upgrade

Commits and Pull Requests Since v1.5.0

Fix spec and shape inference for Unsqueeze op (#2347)
Bump NMS version for avoiding regression in existing models (#2348)
Relax IF's shape inference rule (#2345)
Clarify behavior in ConvTranspose (#2343)
Fix node test case model for Gemm scalar bias case (#2342)
Update pybind (#2340)
Update gen_doc script to validate proto3 files (#2122)
Fix some backend tests (#2335)
Gemm optional bias (#2330)
Changes for AIX platform (#1913)
Updated test cases for reshape (#2127)
Replace is by == (#2326)
Updated docs for strides and dilations attributes (#2291)
Revamped test cases for Gemm (#2060)
Add more shape inference tests for Logical operators to improve coverage (#2133)
Change incorrect use of ValueError to TypeError (#2304)
Support dynamic 'pads' and 'value' in Pad operator (#2031)
Update IR doc to clarify initializers are permitted as node inputs (#2320)
Avoid uses of special chars (#2315)
Regenerate ONNX proto and add release date to ver 6 IR (#2316)
Add description of default type about y_zero_point (#2110)
Support make_attribute empty string (#2129)
More unsqueeze tests (#2200)
Fix resize shape inference issue in opset10 (#2294)
Sequence related ops (#2249)
Add helper function update_inputs_outputs_dims to tools (#2148)
Update documentation about required input output types (#2310)
Shape inference for NMS (#2269)
Fix extra collect_snippets warning (#2277) (#2307)
Fix shapeinference function (#2296)
fix the buffer overflow problem in shape inference logic of Squeeze op
Support for negative indices in 'Gather'
Fix collect_snippets warnings (#2277)
Update printable_graph in helper.py to output details of initializers that do not have matching graph inputs. (#2135)
test int64 input type for 'where' op (#2253)
Supporting negative axes for all existing onnx ops (#2281)
Update managingexperimentalops.md (#1981)
Fix link to community docs in readme (#2261)
move map and sequence types to onnx domain
Improve compatiblity with proto3 and enable reading attributes (#2288)
Remove type info for loop variadic input in Loop op used to compose the Range op (#2287)
Add Foundation WG to working-groups.md (#2276)
Fix testdata model for CumSum. Add exclusive attribute. (#2271)
Support GatherND operator in ONNX (#2106)
Support ScatterND operator in ONNX (#2220)
Add Det to ONNX (#2233)
Update the description of nearest_mode of resize op (#2257)
Adding sparse tensor to ONNX (#2019)
Support Range operator in ONNX (#2242)
Update resize op (#2057)
Add function to fuse dynamic quantization graph into 1 node (#2187)
Update logo_request.md (#2231)
Update Clip in opset 11 to support min/max as inputs instead of attributes (#2096)
Fix segfault in tile shape inference (#2221)
update onehot shape inference to reflect the spec for depth input (#2224)
Add GatherElements Op and Rename ScatterElements (#2143)
Unique (#2141)
Clarify dimension variable scoping (#2211)
Liqun/topk sort (#2126)
Update document for NMS (#2193)
Handle negative 'axis' value in Split type and shape inferencing (#2177)
depth to space shuffle order (#2163)
minor updates to fix links in readme (#2189)
Add check to disallow squeezing input axes which are not 1 (#2204)
2019-07-28
Clarify ambiguity in gather spec regarding indices expectation (#2202)
Fix some minor issues in IR.md and Versioning.md (#2108)
Skip install typing package for python >=3.5 (#2199)
Member Company logo guidelines (#2196)
remove link to outdated issue for contributions wanted (#2186)
Create sigs.md (#2103)
mintor format update (#2180)
add more types support for Equal op (#2176)
Update AddNewOP document. (#2172)
Add missing space (#2150)
python api example typo fix (#2155)
Fix errors in RoiAlign shape inference code (#2167)
TensorProto::INT8 & INT16 were missed here (#2164)
Fix LabelEncoder's shape inference (#2170)
Fixing a unit test in Cumsum Operator (#2157)
[New Operator] CumSum (#2030)
Fix globalpool output shape (#2147)
Expose ONNX_ML build option to python (#2138)
Missing newline fix (#2128)
Avoid unnecessary copies of names by checker (#2098)
update qlinear conv test (#2120)
Add shape inference for LinearClassifier (#2077)
Fix inconsistency in describing graph's initializer. The initializer (#2115)
Update codeowners to have community folder changes assigned to steering committee (#2104)
Fix Resize/Upsample Shape inference function (#2085)
Clarify shape inference requirements for new operators (#2088)
Fix NN defs file (#2083)
Fix type s/depracted/deprecated/ (#2092)
Add shape inference for Tile op (#2076)
[New Operator] Round (#2053)
Add dilations support in ConvTranspose shape inference and update docs (#2068)
Fix typo (#2069)
Add a missing step when upgrading an operator (#2071)
Clarify the axis/size in pads
Fix wrong condition and add --user in update_doc.sh (#2050)
Add bit-shift operators for supporting hashing (#1931)
Add shape inference logic for Expand op (#2041)
update qops tests (#2040)
Fix torchvision installation (#2054)
Fix bug that kernel_shape rather than effective_kernel_shape is used in dilated conv (#2043)
Changes done internally at Facebook (#2035)
Explicitly specify type of integers in the input tensor. (#2034)
Version Conversion of Min
Fix auto_pad shape inference bug (#2028)
Version Conversion from opset 8 to 9 (#2007)
fix macro ONNX_DISALLOW_COPY_AND_ASSIGN bug (#2017)
fix array range bug (#2015)
Relax constraint on subgraph input/output type and shape (#2009)
Fix shape inference logic for TopK operator (#2005)
Nullary variadic (#1889)
Removed setting MD/MDd flags manually through cmake. The MTd/MT part is still necessary. Looks like CI fails without it. (#1995)
Move NonMaxSupression to object_detection folder (#2001)
Prevent using invalid iterator
Add shape inference for legacy auto_pad modes (#1988)
Move Quantization working group to completed state (#1980)
Define the IR acronym (#1985)
fix shape inference (#1984)
fixing some of Mod test cases (#1962)
Lint the docs name (#1982)
Fix a shapeinference bug in upsample v9/10 (#1969)
Create managingexperimentalops (#1974)
Create archivefileformat doc based on the wiki equivalent (#1973)
Create NLPinONNXproposal (#1975)
Create ONNXIFIproposal (#1976)
Create onnxreleases (#1977)
Create functionsproposal (#1978)
Create typeannotations.md (#1979)