Model Optimizer arguments:
Common parameters:
	- Path to the Input Model: 	/home/openvino/tile/hybrid-tile-aligned-int8-eval/bert-base-squadv1-block-pruning-hybrid-filled-lt-nncf-57.92sparse-qat-lt-tilealigned.onnx
	- Path for generated IR: 	/home/openvino/tile/hybrid-tile-aligned-int8-eval/ir
	- IR output name: 	bert-base-squadv1-block-pruning-hybrid-filled-lt-nncf-57.92sparse-qat-lt-tilealigned
	- Log level: 	ERROR
	- Batch: 	Not specified, inherited from the model
	- Input layers: 	Not specified, inherited from the model
	- Output layers: 	Not specified, inherited from the model
	- Input shapes: 	Not specified, inherited from the model
	- Mean values: 	Not specified
	- Scale values: 	Not specified
	- Scale factor: 	Not specified
	- Precision of IR: 	FP32
	- Enable fusing: 	True
	- Enable grouped convolutions fusing: 	True
	- Move mean values to preprocess section: 	None
	- Reverse input channels: 	False
ONNX specific parameters:
	- Inference Engine found in: 	/opt/intel/openvino/python/python3.6/openvino
Inference Engine version: 	2021.4.2-3974-e2a469a3450-releases/2021/4
Model Optimizer version: 	2021.4.2-3974-e2a469a3450-releases/2021/4
[ WARNING ]  Convert data type of Parameter "input_ids" to int32
[ WARNING ]  Convert data type of Parameter "attention_mask.1" to int32
[ WARNING ]  Convert data type of Parameter "input.1" to int32
[ SUCCESS ] Generated IR version 10 model.
[ SUCCESS ] XML file: /home/openvino/tile/hybrid-tile-aligned-int8-eval/ir/bert-base-squadv1-block-pruning-hybrid-filled-lt-nncf-57.92sparse-qat-lt-tilealigned.xml
[ SUCCESS ] BIN file: /home/openvino/tile/hybrid-tile-aligned-int8-eval/ir/bert-base-squadv1-block-pruning-hybrid-filled-lt-nncf-57.92sparse-qat-lt-tilealigned.bin
[ SUCCESS ] Total execution time: 78.71 seconds. 
[ SUCCESS ] Memory consumed: 1920 MB.