[MKLDNN] Enable more convolution + activation fusion

[ZhennanQin]

Description

This PR enables below fusion pattern for MKLDNN backend:

FP32:
conv+sigmoid
conv+tanh
conv+softrelu
conv+clip(0, n) #(when n=6, it's mxnet version of relu6)

INT8:
conv+clip(0, n) #(when n=6, it's mxnet version of relu6)

Minor change:

• Fix a bug of partitioning mobilenetV2. The bug is, when loop is detected, build subgraph pass will try to break the loop and try again. During the retry, selector may contain internal state from previous selection, causing unexpected result. The fix is to add reset API for selector to clean up internal state.

@pengzhao-intel @TaoLv @reminisce @anirudh2290

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

• The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant JIRA issue created (except PRs with tiny changes)
• Changes are complete (i.e. I finished coding on this PR)
• All changes have test coverage:
• Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
• Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
• Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
• Code is well-documented:
• For user-facing API changes, API doc string has been updated.
• For new C++ functions in header files, their functionalities and arguments are documented.
• For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
• Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
• To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Changes

• Feature1, tests, (and when applicable, API doc)
• Feature2, tests, (and when applicable, API doc)

Comments

• If this change is a backward incompatible change, why must this change be made.
• Interesting edge cases to note here

[pengzhao-intel]

@TaoLv to review the change inside convolution.

[pengzhao-intel]

@ZhennanQin @xinyu-intel please help rebase the code and the TRT issue is fixed now :)

[ZhennanQin]

@pengzhao-intel CI can pass now.

[pengzhao-intel]

Great, I am taking a review again and will merge soon.

[pengzhao-intel]

LGTM, will merge by the end of today if no further comment.

[pengzhao-intel]

Merging now, thanks for the contribution.