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6c3876a30d
- Rename tesla-k80-tests.yml to tesla-k80-single-gpu-tests.yml for clarity - Add new tesla-k80-multi-gpu-tests.yml workflow for large models - Add multi-gpu profile to test/config/models.yaml with gemma3:27b and gpt-oss:20b - Multi-GPU workflow includes GPU count verification and weekly schedule - Profile-specific validation allows multi-GPU splits for large models - Separate workflows optimize CI efficiency: quick tests vs. thorough tests
99 lines
2.5 KiB
YAML
99 lines
2.5 KiB
YAML
# Test configuration for Tesla K80 model testing
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# This file defines test profiles with different model sizes and test scenarios
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profiles:
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# Quick test profile - fast smoke test with medium model
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quick:
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timeout: 5m
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models:
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- name: gemma3:4b
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prompts:
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- "Hello, respond with a brief greeting."
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min_response_tokens: 5
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max_response_tokens: 100
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timeout: 60s
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# Full test profile - test largest model that fits on single K80
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full:
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timeout: 30m
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models:
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- name: gemma3:12b
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prompts:
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- "Hello, respond with a brief greeting."
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min_response_tokens: 5
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max_response_tokens: 100
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timeout: 120s
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# Multi-GPU test profile - test models requiring 2x Tesla K80s
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multi-gpu:
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timeout: 45m
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models:
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- name: gemma3:27b
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prompts:
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- "Hello, respond with a brief greeting."
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min_response_tokens: 5
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max_response_tokens: 100
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timeout: 300s
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- name: gpt-oss:20b
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prompts:
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- "Hello, respond with a brief greeting."
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min_response_tokens: 5
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max_response_tokens: 100
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timeout: 240s
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validation:
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# Override single_gpu_preferred for multi-GPU tests
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gpu_required: true
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single_gpu_preferred: false
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check_patterns:
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success:
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- "loaded model"
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- "offload.*GPU"
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- "CUDA backend"
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- "split.*layer.*GPU" # Expect multi-GPU split
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failure:
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- "CUDA.*error"
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- "out of memory"
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- "OOM"
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- "CPU backend"
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- "failed to load"
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# Validation rules applied to all tests (unless overridden in profile)
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validation:
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# Require GPU acceleration (fail if CPU fallback detected)
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gpu_required: true
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# Require single GPU usage for Tesla K80 (detect unnecessary multi-GPU splits)
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single_gpu_preferred: true
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# Log patterns to check for success/failure
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check_patterns:
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success:
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- "loaded model"
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- "offload.*GPU"
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- "CUDA backend"
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failure:
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- "CUDA.*error"
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- "out of memory"
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- "OOM"
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- "CPU backend"
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- "failed to load"
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warning:
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- "fallback"
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- "using CPU"
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# Server configuration
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server:
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host: "localhost"
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port: 11434
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startup_timeout: 30s
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health_check_interval: 1s
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health_check_endpoint: "/api/tags"
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# Reporting configuration
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reporting:
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formats:
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- json
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- markdown
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include_logs: true
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log_excerpt_lines: 50 # Lines of log to include per failure
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