Add flag to dump mlir modules to mxrs

[pfultz2]

No description provided.

[codecov]

Codecov Report

Attention: Patch coverage is 0% with 13 lines in your changes missing coverage. Please review.

Project coverage is 92.01%. Comparing base (b57b1e4) to head (f1caeba).

Files with missing lines	Patch %	Lines
src/shape.cpp	0.00%	9 Missing ⚠️
src/program.cpp	0.00%	4 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #3182      +/-   ##
===========================================
- Coverage    92.02%   92.01%   -0.02%     
===========================================
  Files          508      508              
  Lines        20948    20951       +3     
===========================================
  Hits         19278    19278              
- Misses        1670     1673       +3     

Flag	Coverage Δ
	92.01% <0.00%> (-0.02%)	⬇️

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[umangyadav]

add to ENV var document.

Also what's the usefulness of having MXRs for each MLIR module ?

[pfultz2]

Added docs.

[migraphx-bot]

Test	Batch	Rate new 161b7c	Rate old 32a84a	Diff	Compare
torchvision-resnet50	64	3,250.69	3,250.93	-0.01%	✅
torchvision-resnet50_fp16	64	6,998.52	6,986.29	0.18%	✅
torchvision-densenet121	32	2,434.20	2,433.76	0.02%	✅
torchvision-densenet121_fp16	32	4,085.57	4,110.78	-0.61%	✅
torchvision-inceptionv3	32	1,636.43	1,635.58	0.05%	✅
torchvision-inceptionv3_fp16	32	2,736.42	2,737.29	-0.03%	✅
cadene-inceptionv4	16	776.19	775.61	0.07%	✅
cadene-resnext64x4	16	808.55	808.58	-0.00%	✅
slim-mobilenet	64	7,456.88	7,452.87	0.05%	✅
slim-nasnetalarge	64	208.18	208.18	0.00%	✅
slim-resnet50v2	64	3,434.56	3,434.69	-0.00%	✅
bert-mrpc-onnx	8	1,149.49	1,150.44	-0.08%	✅
bert-mrpc-tf	1	312.34	311.37	0.31%	✅
pytorch-examples-wlang-gru	1	420.94	426.16	-1.23%	✅
pytorch-examples-wlang-lstm	1	451.85	386.06	17.04%	🔆
torchvision-resnet50_1	1	765.71	816.95	-6.27%	🔴
cadene-dpn92_1	1	403.90	401.62	0.57%	✅
cadene-resnext101_1	1	381.58	380.63	0.25%	✅
onnx-taau-downsample	1	344.61	345.07	-0.13%	✅
dlrm-criteoterabyte	1	35.07	35.06	0.03%	✅
dlrm-criteoterabyte_fp16	1	58.05	58.01	0.07%	✅
agentmodel	1	7,973.21	7,975.82	-0.03%	✅
unet_fp16	2	58.02	58.07	-0.09%	✅
resnet50v1_fp16	1	924.52	921.74	0.30%	✅
resnet50v1_int8	1	934.33	953.21	-1.98%	✅
bert_base_cased_fp16	64	1,153.07	1,152.80	0.02%	✅
bert_large_uncased_fp16	32	355.90	355.84	0.02%	✅
bert_large_fp16	1	209.91	211.95	-0.96%	✅
distilgpt2_fp16	16	2,161.16	2,157.57	0.17%	✅
yolov5s	1	534.91	528.76	1.16%	✅
tinyllama	1	43.66	43.37	0.65%	✅
vicuna-fastchat	1	168.26	168.85	-0.35%	✅
whisper-tiny-encoder	1	417.96	418.42	-0.11%	✅
whisper-tiny-decoder	1	422.90	425.66	-0.65%	✅

This build is not recommended to 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