|
55 | 55 | - After stress test move from stage to prod |
56 | 56 | - Comment on the commit with cml for stress test results |
57 | 57 | - in actions change the workflow comment to PR |
| 58 | +- good one - ecr image May 17, 2025, 00:03:15 (UTC+05.5) - take this and move forward. |
| 59 | + |
| 60 | +Note: If we build a gpu image from github runner then its throwing below error, so i have prebuilt image |
| 61 | + |
| 62 | +``` |
| 63 | +/opt/conda/lib/python3.11/site-packages/torch/cuda/__init__.py:734: UserWarning: Can't initialize NVML |
| 64 | + warnings.warn("Can't initialize NVML") |
| 65 | +``` |
| 66 | +if no thing works then use the model-onnx-server image |
| 67 | +### Pending for Deployment 3 |
| 68 | +- lambda |
58 | 69 |
|
59 | 70 | Docs |
60 | 71 | - Architecture diagram |
61 | 72 | - Screenshots of deployment and video |
62 | 73 |
|
63 | 74 | Explanation: Deployment 01 |
64 | 75 | Architecture diagram |
| 76 | +dvc setup and pull - dataset |
65 | 77 | start from train and store feature |
66 | 78 | then go with optuna taking the lowest loss model and saving it - hyper paramter optimization |
| 79 | +models usage |
| 80 | +onnx model generation |
| 81 | +torch script model for usage |
| 82 | +mar for torch serve usage |
| 83 | +accuracy txt for verification |
67 | 84 | then transfering the outputs to s3-dev |
68 | 85 |
|
69 | 86 | Now kubernetes |
70 | 87 | setting up of kserve, knative, argocd, promethus, grafana |
71 | 88 | show the screenshots on load test |
72 | 89 |
|
73 | 90 | Now deployments workflow |
| 91 | +show the ecr repo and docker files |
74 | 92 | on PR generates a model in dev |
75 | 93 | compare and post comment in PR |
76 | 94 |
|
77 | 95 | Now kubernetes deployment - github actions |
| 96 | +show the ecr repo and docker all 3 files |
78 | 97 | explain secrets setup - github workflow |
79 | 98 | on push to main branch |
80 | 99 | train and push to stage |
|
0 commit comments