Dont convert squeeze/unsqueeze to reshape when fusing mlir

[pfultz2]

Unsqueeze/squeeze/lazy_reshape perserve the layout whereas reshape doesnt. The mlir_op uses this to compute the output shape which could be different after we fuse with mlir. Instead, just convert them to reshape when we are converting to mlir.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 92.17%. Comparing base (ddc4c0c) to head (370c90c).
Report is 8 commits behind head on develop.

Additional details and impacted files

@@           Coverage Diff            @@
##           develop    #3533   +/-   ##
========================================
  Coverage    92.17%   92.17%           
========================================
  Files          512      512           
  Lines        21387    21391    +4     
========================================
+ Hits         19714    19718    +4     
  Misses        1673     1673           

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[shivadbhavsar]

lgtm

[migraphx-bot]

Test	Batch	Rate new 370c90	Rate old 275f85	Diff	Compare
torchvision-resnet50	64	3,261.33	3,260.33	0.03%	✅
torchvision-resnet50_fp16	64	6,987.49	6,996.93	-0.13%	✅
torchvision-densenet121	32	2,435.13	2,436.13	-0.04%	✅
torchvision-densenet121_fp16	32	4,074.51	4,080.65	-0.15%	✅
torchvision-inceptionv3	32	1,638.32	1,639.01	-0.04%	✅
torchvision-inceptionv3_fp16	32	2,762.86	2,759.60	0.12%	✅
cadene-inceptionv4	16	776.86	775.88	0.13%	✅
cadene-resnext64x4	16	811.70	811.11	0.07%	✅
slim-mobilenet	64	7,537.22	7,539.27	-0.03%	✅
slim-nasnetalarge	64	211.56	211.54	0.01%	✅
slim-resnet50v2	64	3,505.47	3,505.47	0.00%	✅
bert-mrpc-onnx	8	1,150.33	1,151.85	-0.13%	✅
bert-mrpc-tf	1	469.67	463.50	1.33%	✅
pytorch-examples-wlang-gru	1	429.74	411.56	4.42%	🔆
pytorch-examples-wlang-lstm	1	381.25	388.27	-1.81%	✅
torchvision-resnet50_1	1	782.26	764.51	2.32%	✅
cadene-dpn92_1	1	401.39	402.09	-0.17%	✅
cadene-resnext101_1	1	382.19	381.69	0.13%	✅
onnx-taau-downsample	1	342.76	342.54	0.06%	✅
dlrm-criteoterabyte	1	33.34	33.35	-0.03%	✅
dlrm-criteoterabyte_fp16	1	52.71	52.74	-0.06%	✅
agentmodel	1	8,304.61	8,186.92	1.44%	✅
unet_fp16	2	58.82	58.82	0.01%	✅
resnet50v1_fp16	1	964.49	953.22	1.18%	✅
resnet50v1_int8	1	1,017.22	1,003.11	1.41%	✅
bert_base_cased_fp16	64	1,170.93	1,170.57	0.03%	✅
bert_large_uncased_fp16	32	363.75	363.63	0.03%	✅
bert_large_fp16	1	198.99	201.70	-1.35%	✅
distilgpt2_fp16	16	2,203.35	2,202.28	0.05%	✅
yolov5s	1	549.54	537.82	2.18%	✅
tinyllama	1	43.42	43.44	-0.04%	✅
vicuna-fastchat	1	173.56	173.47	0.05%	✅
whisper-tiny-encoder	1	418.02	418.26	-0.06%	✅
whisper-tiny-decoder	1	426.43	436.61	-2.33%	✅

Check results before merge 🔆

[migraphx-bot]

     ✅ bert-mrpc-onnx: PASSED: MIGraphX meets tolerance

     ✅ bert-mrpc-tf: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-gru: PASSED: MIGraphX meets tolerance

     ✅ pytorch-examples-wlang-lstm: PASSED: MIGraphX meets tolerance

     ✅ torchvision-resnet50_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-dpn92_1: PASSED: MIGraphX meets tolerance

     ✅ cadene-resnext101_1: PASSED: MIGraphX meets tolerance

     ✅ dlrm-criteoterabyte: PASSED: MIGraphX meets tolerance

     ✅ agentmodel: PASSED: MIGraphX meets tolerance

     ✅ unet: PASSED: MIGraphX meets tolerance

     ✅ resnet50v1: PASSED: MIGraphX meets tolerance

     ✅ bert_base_cased_fp16: PASSED: MIGraphX meets tolerance

🔴bert_large_uncased_fp16: FAILED: MIGraphX is not within tolerance - check verbose output

     ✅ bert_large: PASSED: MIGraphX meets tolerance

     ✅ yolov5s: PASSED: MIGraphX meets tolerance

     ✅ tinyllama: PASSED: MIGraphX meets tolerance

     ✅ vicuna-fastchat: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-encoder: PASSED: MIGraphX meets tolerance

     ✅ whisper-tiny-decoder: PASSED: MIGraphX meets tolerance

     ✅ distilgpt2_fp16: PASSED: MIGraphX meets tolerance