OpRegularizerManager could not handle ops

Hello,

I have tried a few examples from tensorflow/model with morphnet (lenet and resnet), a simple mnist model (https://github.com/mengdong/morph-net/blob/master/morph_net/examples/mnist/mnist-tutorial.py) works. However, I ran into problems in some other more complex models under tensorflow estimator interface.

I wonder is there a recommended way to use morphnet in tf estimator inferface? I know there is quite some overhead in the estimator's graph. Detailed infromation below:

Regarding lenet (https://github.com/mengdong/morph-net/blob/master/morph_net/examples/mnist/mnist.py) from https://github.com/tensorflow/models/tree/master/official/mnist, I observe that:
```
I0904 13:14:27.240477 140031449261888 op_regularizer_manager.py:125]
OpRegularizerManager found 63 ops and 4 sources.
......
File "/home/dongm/workspace/laptop_mapping/morph-net/morph_net/framework/op_regularizer_manager.py", line 137, in __init__
['%s (%s)' % (o.name, o.type) for o in self._op_deque])
RuntimeError: OpRegularizerManager could not handle ops: ['sequential/conv2d/BiasAdd (BiasAdd)', 'sequential/max_pooling2d_1/MaxPool (MaxPool)', 'sequential/conv2d_1/BiasAdd (BiasAdd)', 'sequential/max_pooling2d/MaxPool (MaxPool)', 'sequential/conv2d/BiasAdd/ReadVariableOp (ReadVariableOp)']
```

Regarding ResNet (https://github.com/mengdong/morph-net/blob/master/morph_net/examples/resnet/imagenet_main.py), I observe:
```
I0904 11:27:34.397989 139699288442688 op_regularizer_manager.py:125]
OpRegularizerManager found 629 ops and 53 sources.
.....
RuntimeError: OpRegularizerManager could not handle ops:
['resnet_model/batch_normalization_45/FusedBatchNormV3 (FusedBatchNormV3)',
'resnet_model/Pad_6 (Pad)', 'resnet_model/batch_normalization_44/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_49/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_48/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_47/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_52/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_51/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/Squeeze (Squeeze)', 'resnet_model/final_reduce_mean (Identity)', 'resnet_model/Mean (Mean)', 'resnet_model/batch_normalization_50/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_43/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_24/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_11/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_1/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/Pad (Pad)',
'resnet_model/batch_normalization/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_4/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_3/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/max_pooling2d/MaxPool (MaxPool)', 'resnet_model/initial_max_pool (Identity)', 'resnet_model/batch_normalization_2/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_7/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_6/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_5/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_10/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_9/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_8/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_14/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_13/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/Pad_2 (Pad)', 'resnet_model/batch_normalization_12/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_17/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_16/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_15/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_20/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_19/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_18/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_23/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_22/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_21/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_27/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_26/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/Pad_4 (Pad)',
'resnet_model/batch_normalization_25/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_30/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_29/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_28/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_33/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_32/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_31/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_36/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_35/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_34/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_39/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_38/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_37/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_42/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_41/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_40/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_46/FusedBatchNormV3 (FusedBatchNormV3)', 'resnet_model/batch_normalization_45/ReadVariableOp (ReadVariableOp)', 'resnet_model/batch_normalization_45/ReadVariableOp_1 (ReadVariableOp)']
```

Start with morph_net/framework/op_regularizer_manager.py around line 137 and reproduce the failure using the referenced lenet, ResNet, and mnist examples under the TensorFlow estimator interface. Compare the handled operations with the listed BiasAdd, MaxPool, FusedBatchNormV3, Pad, and ReadVariableOp failures; done should establish how these estimator graphs are supported or clearly document the limitation and recommended usage.

Written by the indexing model from the issue text.