Llama2 7b model C++ example

[ototh-htec]

Implemented an example for https://huggingface.co/amd/Llama-2-7b-chat-hf-awq-int4-asym-gs128-onnx/tree/main Llama2 7b model with MIGraphX.

Details about the example and description for running is available in README (https://github.com/ROCm/AMDMIGraphX/tree/htec/mgx-llama2-7b-example/examples/transformers/mgx_llama2)

[gyulaz-htec]

We can remove these changes (commits) which are related to exposing this API part. Because we ended up not needing these changes.

[ototh-htec]

Removed them

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 92.23%. Comparing base (2e9104a) to head (b499638).
Report is 2 commits behind head on develop.

Additional details and impacted files

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  Coverage    92.23%   92.23%           
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  Files          514      514           
  Lines        21746    21746           
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  Hits         20057    20057           
  Misses        1689     1689           

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[migraphx-bot]

Test	Batch	Rate new b49963	Rate old 4b15b6	Diff	Compare
torchvision-resnet50	64	3,254.17	3,257.89	-0.11%	✅
torchvision-resnet50_fp16	64	6,988.94	6,918.72	1.01%	✅
torchvision-densenet121	32	2,432.26	2,432.91	-0.03%	✅
torchvision-densenet121_fp16	32	4,085.65	4,086.33	-0.02%	✅
torchvision-inceptionv3	32	1,627.76	1,628.71	-0.06%	✅
torchvision-inceptionv3_fp16	32	2,742.43	2,745.51	-0.11%	✅
cadene-inceptionv4	16	764.96	764.62	0.04%	✅
cadene-resnext64x4	16	810.58	814.13	-0.44%	✅
slim-mobilenet	64	7,461.51	7,458.12	0.05%	✅
slim-nasnetalarge	64	208.46	209.03	-0.27%	✅
slim-resnet50v2	64	3,440.03	3,436.59	0.10%	✅
bert-mrpc-onnx	8	1,150.36	1,150.32	0.00%	✅
bert-mrpc-tf	1	475.69	449.82	5.75%	🔆
pytorch-examples-wlang-gru	1	428.15	437.44	-2.12%	✅
pytorch-examples-wlang-lstm	1	436.50	383.25	13.89%	🔆
torchvision-resnet50_1	1	777.19	741.45	4.82%	🔆
cadene-dpn92_1	1	399.33	400.49	-0.29%	✅
cadene-resnext101_1	1	382.84	382.70	0.04%	✅
onnx-taau-downsample	1	345.53	345.15	0.11%	✅
dlrm-criteoterabyte	1	33.35	33.31	0.11%	✅
dlrm-criteoterabyte_fp16	1	52.51	52.72	-0.40%	✅
agentmodel	1	8,059.84	8,463.32	-4.77%	🔴
unet_fp16	2	58.74	58.77	-0.05%	✅
resnet50v1_fp16	1	935.52	934.37	0.12%	✅
resnet50v1_int8	1	995.64	1,030.33	-3.37%	🔴
bert_base_cased_fp16	64	1,169.76	1,170.28	-0.04%	✅
bert_large_uncased_fp16	32	363.68	363.03	0.18%	✅
bert_large_fp16	1	199.12	199.90	-0.39%	✅
distilgpt2_fp16	16	2,197.04	2,197.64	-0.03%	✅
yolov5s	1	528.96	518.78	1.96%	✅
tinyllama	1	43.34	43.68	-0.79%	✅
vicuna-fastchat	1	165.26	173.15	-4.56%	🔴
whisper-tiny-encoder	1	418.07	417.60	0.11%	✅
whisper-tiny-decoder	1	432.36	429.03	0.78%	✅

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

[turneram]

Is this needed? I don't believe we make any MIOpen calls for this model.

[spolifroni-amd]

readme looks fine from a grammar/spelling angle