* Finished ChannelWiseQuantDequantAbsMaxOp and Passed unittests.

* Finished channel-wise quantize strategy in imperative quantization.

* Added Cuda code of ChannelWiseQuantDequantMaxAbsOP
Add Cuda code of ChannelWiseQuantDequantMaxAbsOp

* Add quant_axis for channel_wise quant.

* fixed a bug in unnitests, which will not trigger axis = 1 case and cannot meet the coverage rate requirement.

* Added some assert infomation and fixed some coding style mistakes.

* Conv2d_transpose and mul support channnelwise quantization, test=develop
* Skip collecting out threshold for output tensor of which the type is not fp32 or fp64, test=develop
* Fix error in test_user_defined_quantization, test=develop
* Add depthwise_conv_bn_fuse, test=develop
* Add conv_transpose_bn_fuse_pass for post_training_quant, test=develop

* Remove the output for moving_average_abs_max_scale op, test=develop

* fix div zero test=develop

* fix div zero test=develop

* add hostdevice function test=develop

* add eps when is zero test=develop

TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.

We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.

Also added data_feed_proto to operator to fix CI in CPU compilation

* add quant_dequant_moving_avg_max_abs op
test=develop

* add more note for quantdequant op
test=develop

* Add MovingAverageAbsMaxScale operator which is only used for calculating the quantization scale.

* test=develop

* change the output into inplace. test=develop

* Revert "test=develop"

This reverts commit 696cf626.

* Revert "change the output into inplace. test=develop"

This reverts commit a19acd20.

* test=develop.

* update the MovingAverageAbsMaxScaleOp test. test=develop

* Add moving average absmax op in quantilize-aware training.

* Improve and fix fake_quantize_op.

* Add a fake_quantize_op, which quantize an input tensor to a tensor with lower bits.