Bump onnx from 1.6.0 to 1.7.0 in /tool/conda/singa

[dependabot]

Bumps onnx from 1.6.0 to 1.7.0.

Release notes

Sourced from onnx's releases.

v1.7.0

ONNX v1.7 is now available with exciting new features! We would like to thank everyone who contributed to this release! You may learn more about the project, who is involved and what tools are available at the onnx.ai site.

Change Log

Major changes and updates since the v1.6.0 release:

Training Support, as a tech preview

• A set of new training features are introduced to represent neural network models in the process of model training.
• A protobuf message TrainingInfoProto is added to store training information, including the algorithm and initializers, as well as new operators Gradient and GraphCall and new functions describing most commonly used Loss functions and Optimizers, all in the domain ai.onnx.preview.training.
• The new spec allows one to create a model training task or a partially trained model in one framework, then export it in ONNX and load into a runtime or another framework where the training can proceed, with the expectation of theoretically similar outcome to the model trained in the original framework.
• Note the converters do not support training yet. The goal of this tech preview is to test the new spec and to enable converters to add full support in future releases.

Operator changes

• Opset has been updated to version 12.

• Preview training opset has been added as version 1.

• New operators:

  • ONNX
    • Celu (onnx/onnx#2575) (onnx/onnx#2573)
    • Einsum (onnx/onnx#2504)
    • GreaterOrEqual (onnx/onnx#2606)
    • LessOrEqual (onnx/onnx#2606)
    • NegativeLogLikelihoodLoss (onnx/onnx#2551) (onnx/onnx#2573) (onnx/onnx#2725)
    • SoftmaxCrossEntropyLoss (onnx/onnx#2573) (onnx/onnx#2667) (onnx/onnx#2680) (onnx/onnx#2690) (onnx/onnx#2696) (onnx/onnx#2700) (onnx/onnx#2703) (onnx/onnx#2725)
    • Pow (onnx/onnx#2666)
  • ONNX preview training
    • Gradient (onnx/onnx#2314)
    • GraphCall (onnx/onnx#2314)
    • Adagrad (onnx/onnx#1955)
    • Adam (onnx/onnx#1970)
    • SG with Momentum (onnx/onnx#1959)

• Updated operators:

  • ONNX
    • ArgMax (onnx/onnx#2461)
    • ArgMin (onnx/onnx#2461)
    • Clip (onnx/onnx#2532)
    • Constant (onnx/onnx#2592)
    • Dropout (onnx/onnx#2568) (onnx/onnx#2725)
    • GatherND (onnx/onnx#2585)
    • Max (onnx/onnx#2608)
    • MaxPool (onnx/onnx#2510)
    • Min (onnx/onnx#2608)
    • ReduceMax (onnx/onnx#2516)
    • ReduceMin (onnx/onnx#2516)

• General Features

  • Operator registration APIs are updated to support dynamic function body (sub-graph) registration. https://github.com/onnx/onnx/blob/master/onnx/defs/schema.h#L674
  • Functions’ body graph are extended to be able to rely on multiple external operator sets.https://github.com/onnx/onnx/blob/master/onnx/onnx-operators.proto#L77
  • Some of the operators (for example, all loss functions) added are actually “functions”, as it’s strongly advocated to add functions instead of (primitive) ops.
  • The model checker is enhanced (onnx/onnx#2367)
    • Call shape-inference to do the extra-checking performed by the type-and-shape-inference methods of ops

Commits

• 0c070ab Change version number for release 1.7.0 (#2768)
• 88ca558 Release 1.7 verification 105 (#2764)
• 673aef0 Avoid experimental word also internally (#2761)
• 1f46786 Move all training operators to a preview domain (#2741)
• 5377fcd Control build paralllelism via --parallel option (#2756)
• 0b5adab Remove Mean Squared Distance expanded tests. (#2754)
• 40cbaad Revert Inverse(12) (#2747)
• f0412f3 Revert MeanSquaredDistance(12) (#2748)
• dce5419 Revert BatchNormalization(12) (#2750)
• a4b8b67 Azure Pipelines - Linux / MacOS CIs (#2730)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #23.