Add support for GridSample operator

[gyulaz-htec]

Add support for GridSample onnx operator.
Currently the following feature set is supported:

• inputs: 4-D inputs
• align_corners: both 0 and 1
• mode: linear and nearest
• padding_mode: zeros, border and reflection
  Fixes: Accuracy issue with fuse_pointwise and GridSample #2923

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 91.90%. Comparing base (bceef13) to head (a1cf519).

❗ Current head a1cf519 differs from pull request most recent head 8bb3d24

Please upload reports for the commit 8bb3d24 to get more accurate results.

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #2909      +/-   ##
===========================================
+ Coverage    91.82%   91.90%   +0.08%     
===========================================
  Files          486      487       +1     
  Lines        18991    19192     +201     
===========================================
+ Hits         17438    17639     +201     
  Misses        1553     1553              

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[migraphx-bot]

Test	Batch	Rate new b6172d	Rate old 5fcf86	Diff	Compare
torchvision-resnet50	64	1,751.55	1,751.74	-0.01%	✅
torchvision-resnet50_fp16	64	4,084.47	4,084.34	0.00%	✅
torchvision-densenet121	32	1,467.78	1,467.39	0.03%	✅
torchvision-densenet121_fp16	32	2,529.08	2,525.45	0.14%	✅
torchvision-inceptionv3	32	889.72	889.64	0.01%	✅
torchvision-inceptionv3_fp16	32	1,483.73	1,483.57	0.01%	✅
cadene-inceptionv4	16	412.38	412.40	-0.01%	✅
cadene-resnext64x4	16	419.71	419.50	0.05%	✅
slim-mobilenet	64	4,007.09	4,006.71	0.01%	✅
slim-nasnetalarge	64	101.02	101.01	0.01%	✅
slim-resnet50v2	64	1,680.79	1,680.60	0.01%	✅
bert-mrpc-onnx	8	615.83	618.22	-0.39%	✅
bert-mrpc-tf	1	277.98	279.81	-0.65%	✅
pytorch-examples-wlang-gru	1	320.54	319.57	0.30%	✅
pytorch-examples-wlang-lstm	1	288.76	289.36	-0.21%	✅
torchvision-resnet50_1	1	471.26	471.89	-0.13%	✅
cadene-dpn92_1	1	247.18	247.09	0.04%	✅
cadene-resnext101_1	1	203.92	204.23	-0.15%	✅
onnx-taau-downsample	1	206.48	206.24	0.11%	✅
dlrm-criteoterabyte	1	22.91	22.90	0.04%	✅
dlrm-criteoterabyte_fp16	1	42.72	42.73	-0.02%	✅
agentmodel	1	6,369.83	6,323.67	0.73%	✅
unet_fp16	2	34.18	34.21	-0.07%	✅
resnet50v1_fp16	1	574.81	589.36	-2.47%	✅
resnet50v1_int8	1	578.26	573.50	0.83%	✅
bert_base_cased_fp16	64	646.28	646.33	-0.01%	✅
bert_large_uncased_fp16	32	199.02	198.99	0.02%	✅
bert_large_fp16	1	117.21	117.54	-0.27%	✅
distilgpt2_fp16	16	1,212.43	1,211.40	0.09%	✅
yolov5s	1	301.12	301.25	-0.04%	✅
tinyllama	1	23.33	23.34	-0.03%	✅
vicuna-fastchat	1	133.85	133.65	0.15%	✅
whisper-tiny-encoder	1	244.42	244.39	0.01%	✅
whisper-tiny-decoder	1	256.29	256.66	-0.14%	✅

This build is OK for 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

[gyulaz-htec]

@causten The PR is ready for review
This sould not be marged yet, because I've found an accuracy issue with fuse_pointwise pass with the GPU target when computing GridSample results (with linear inetrploation).
Collected my findings on that issue in #2923

[gyulaz-htec]

I had to exclude logical_and and where operators from pointwise fusion, so the GPU tests are passing now.
#2923 is fixed by that.

[TedThemistokleous]

• Add cubic support + onnx backend coverage - created issue GridSample cubic/bicubic mode is not supported #2960
• Add additional test cases for coverage
  - [ ] Fix loop to pre increment
• Look into alternative to avoid O(n^4) updates and ops.

[gyulaz-htec]

@TedThemistokleous @pfultz2 I've adressed the majority of you commets except the Look into alternative to avoid O(n^4) updates and ops. part.

[gyulaz-htec]

@pfultz2 I've removed the fuse pointwise related changes from the PR in favor of #3054

[codecov-commenter]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 92.05%. Comparing base (5fcf86e) to head (b6172d3).
Report is 1 commits behind head on develop.

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #2909      +/-   ##
===========================================
+ Coverage    91.97%   92.05%   +0.08%     
===========================================
  Files          489      490       +1     
  Lines        19398    19599     +201     
===========================================
+ Hits         17841    18042     +201     
  Misses        1557     1557              

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[causten]

@gyulaz-htec you don't need hit the "update branch" button. Once the review are complete I'll handle it

[kahmed10]

I would like to see additional documentation and possible refactoring since the parse_gridsample.cpp is quite large. Not blocking for merge.