pypi onnx 1.2.1
v1.2.1

ONNX 1.2.1 release.

The following changes have been made since the 1.1.2 release:

IR Changes

  • Adds function and attribute reference (PR #802).
  • Adds dimension denotation (PR #443) and type denotation (PR #879).

Operator Changes

The operator set version of onnx 1.2 is 7 for ONNX domain and 1 for ONNX_ML domain.

  • Type and shape inference function added for all operators.
  • Adds new operators.
    o Upsample (PR #861) – promoted from experimental, attributes and behavior updated to support arbitrary # of dimensions.
    o Identity (PR #892) – promoted from experimental.
    o Acos, Asin, Atan, Cos, Sin, Tan (PR #869).
    o Multinomial (PR #897)
  • Removes FC (experimental) op (PR #977).
  • Moves to numpy broadcasting semantics (PR #907).
  • Clarifies “optional” semantics for input/output and adjust RNN/GRU/LSTM/BatchNormalization/Dropout accordingly (PR #1006, PR #1014).
  • AveragePool – formulas for output shape updated (PR #751), extended to support average count including padding (PR #884)
  • BatchNormalization – clarify outputs can be n-dim (PR #733)
  • Cast – change to attr from string to int (PR #727)
  • ConstantFill (exp) – change value attr from optional to default value of 0 (PR #808)
  • InstanceNormalization – clarify outputs can be n-dim (PR #733)
  • MaxPool – formulas for output shape updated (PR #751)
  • AveragePool, MaxPool, Conv – update to support dimension denotation (PR #443)
  • Reshape – add output shape as an input (PR #608)
  • Size – change output from int to scalar tensor (PR #759)
  • Tile – replace tiles and axis inputs with repeats to match numpy (PR #757)
  • ZipMap – update type constrains from map to seq (PR #818)
  • Affine – add default values for alpha and beta attributes (PR #820)
  • FeatureVectorizer – update behavior (PR #843)
  • LinearClassifier – coefficient attribute is now required (PR #836)
  • RandomNormalLike, RandomUniformLike – change input type constraints and change behavior to copy shape instead of compute it (PR #846)
  • Selu – change default value of attributes to match other frameworks (PR #839)
  • ArgMax, ArgMin – specify default values for axis attribute (PR #847)
  • DepthToSpace, SpaceToDepth – blocksize attribute is now required (PR #847)
  • GRU, LSTM, RNN – specify default value for activation_* attributes (PR #847)
  • Reduce* – specify default behavior for axes attribute (PR #847)
  • Concat, Gather, Squeeze, Unsqueeze – accept any tensor type (PR #957)
  • Add, Div, Mul, Pow, Sub – enhance 1-element broadcast case (PR #902)
  • Pad – clarify pads attribute (PR #962)
  • LRN – specify default values and clarify behavior (PR #965)
  • ConvTranspose – clarify padding behavior and remove restriction on output_padding attribute (PR #1012)
  • All ops – updated type constraints (PR #666)
latest releases: 1.10.1, 1.10.0, 1.9.0...
3 years ago