* Speed affine_channel_op unit testing
* Add check in tensor_py
* Fix ONLY_CPU Compiling

Update the filter generation mechanism that it could generate the negative parameter.
The original calling(np.random.random()) couldn't simulate the conv/relu fusion case.

test=develop

* accelerate test_ir_memory_optimize_nlp, test=develop

* accelerate test_ir_memory_optimize_nlp, test=develop

Rename the testcuda function to has_cuda, it will elimate the unnecessary testing.
test=develop

* speedup gc and inplace softmax_with_cross_entropy_grad
test=develop

* refine models gpu mem
Merge skip vars and warning messages of mem opt
remove relu mem opt
test=develop

* follow comments
test=develop

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* Split test_calibration test to two tests

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* Modify CMakeLists file
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* Support seq len equal to 0 in sequence ops

test=develop

* Add more test cases

* Fix some comments

test=develop

* Fix py3 error

test=develop

* Check some shapes only in runtime

test=develop

* Follow review comments

test=develop

* Update API spec

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test=develop

* fix sampling id op bug, test=develop

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test = develop
resolve #16764

* test=develop
update API.spec with hash, resolve conflict

* remove unused parameter

* optimize lstmp and sample_logits op, test=develop

* update op_use_default_grad_op_maker.spec, test=develop

* delete useless file,test=develop

* append 0 to dim variable to avoid memory reusage, test=develop

* test=develop, fix hsigmoid dereference nullptr

* test=develop, refine condition

* test=develop, refine comments

test=develop

test=develop

test=develop

test=develop

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* enable recurrent op test=develop

* make test_dyn_rnn faster

test = develop
resolve #16764

test=develop

test=develop