Add ONNX model testing workflow

[danieyan-amd]

Summary

This PR creates and updates the onnx-model.yaml workflow to automate model zoo and onnx model testing.
Changes

Removed explicit gh_token input (no longer required to run this workflow).

Cleaned up permissions section to avoid unnecessary write scope.

Updated results publishing step:

Commented out direct publish to danieyan-amd/migraphx-reports.

Added a placeholder path (danieyan-amd/migraphx-reports for now) to clarify current output destination.

[migraphx-bot]

Test	Batch	Rate new 38fdc6	Rate old 38fdc6	Diff	Compare
torchvision-resnet50	64	3,158.73	3,157.16	0.05%	✅
torchvision-resnet50_fp16	64	6,592.62	6,584.70	0.12%	✅
torchvision-densenet121	32	2,437.74	2,436.81	0.04%	✅
torchvision-densenet121_fp16	32	4,115.73	4,114.72	0.02%	✅
torchvision-inceptionv3	32	1,666.40	1,665.37	0.06%	✅
torchvision-inceptionv3_fp16	32	2,588.05	2,587.64	0.02%	✅
cadene-inceptionv4	16	794.32	794.97	-0.08%	✅
cadene-resnext64x4	16	802.69	802.04	0.08%	✅
slim-mobilenet	64	8,209.14	8,202.93	0.08%	✅
slim-nasnetalarge	64	221.72	221.82	-0.04%	✅
slim-resnet50v2	64	3,295.61	3,285.74	0.30%	✅
bert-mrpc-onnx	8	1,135.13	1,134.61	0.05%	✅
bert-mrpc-tf	1	487.52	487.66	-0.03%	✅
pytorch-examples-wlang-gru	1	315.43	312.89	0.81%	✅
pytorch-examples-wlang-lstm	1	440.33	437.57	0.63%	✅
torchvision-resnet50_1	1	804.97	804.91	0.01%	✅
cadene-dpn92_1	1	428.00	426.34	0.39%	✅
cadene-resnext101_1	1	360.58	368.30	-2.10%	✅
onnx-taau-downsample	1	397.72	397.43	0.07%	✅
dlrm-criteoterabyte	1	31.92	31.91	0.02%	✅
dlrm-criteoterabyte_fp16	1	51.01	51.01	0.00%	✅
agentmodel	1	9,602.92	9,938.09	-3.37%	🔴
unet_fp16	2	59.07	59.02	0.09%	✅
resnet50v1_fp16	1	995.13	1,093.99	-9.04%	🔴
resnet50v1_int8	1	988.17	992.35	-0.42%	✅
bert_base_cased_fp16	64	1,099.24	1,099.78	-0.05%	✅
bert_large_uncased_fp16	32	343.76	343.93	-0.05%	✅
bert_large_fp16	1	198.07	198.07	0.00%	✅
distilgpt2_fp16	16	2,074.98	2,075.97	-0.05%	✅
yolov5s	1	587.98	588.16	-0.03%	✅
tinyllama	1	43.80	43.81	-0.02%	✅
vicuna-fastchat	1	44.89	45.07	-0.40%	✅
whisper-tiny-encoder	1	409.82	409.90	-0.02%	✅
whisper-tiny-decoder	1	413.75	414.63	-0.21%	✅
llama2_7b	1	19.11	19.13	-0.10%	✅
qwen1.5-7b	1	23.42	23.43	-0.04%	✅
phi3-3.8b	1	26.63	26.59	0.13%	✅
mask-rcnn	1	12.16	12.16	-0.02%	✅
llama3-8b	1	21.68	21.65	0.14%	✅
whisper-large-encoder	1	10.17	10.17	-0.03%	✅
whisper-large-decoder	1	99.58	99.72	-0.13%	✅
mistral-7b	1	23.64	23.64	-0.03%	✅
FLUX.1-schnell	1	722.64	728.97	-0.87%	✅
nan	nan	nan	nan	nan%	❌

This build is not recommended to merge 🔴

[migraphx-bot]

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

❌bert-mrpc-tf: ERROR - check error output

2025-09-23 19:50:22.358918: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
File "/src/AMDMIGraphX/tools/accuracy/accuracy_checker.py", line 359, in
main()
File "/src/AMDMIGraphX/tools/accuracy/accuracy_checker.py", line 306, in main
graph = load_tf_graph(model_name)
File "/src/AMDMIGraphX/tools/accuracy/accuracy_checker.py", line 300, in load_tf_graph
graph_def.ParseFromString(f.read())
File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/lib/io/file_io.py", line 116, in read
self._preread_check()
File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/lib/io/file_io.py", line 77, in _preread_check
self._read_buf = _pywrap_file_io.BufferedInputStream(
tensorflow.python.framework.errors_impl.UnimplementedError: File system scheme '[local]' not implemented (file: '/new-saved-models/tf-misc/bert_mrpc1.pb')

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

     ✅ pytorch-examples-wlang-lstm: 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

     ✅ llama2_7b: PASSED: MIGraphX meets tolerance

     ✅ qwen1.5-7b: PASSED: MIGraphX meets tolerance

     ✅ phi3-3.8b: PASSED: MIGraphX meets tolerance

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

     ✅ llama3-8b: PASSED: MIGraphX meets tolerance

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

     ✅ mistral-7b: PASSED: MIGraphX meets tolerance

     ✅ FLUX.1-schnell: PASSED: MIGraphX meets tolerance