Commit 4b365d4
chore: fix commit messages for conventional compliance
This commit fixes one or more commit messages that didn't follow
conventional commits format. The original commits have been
squashed and their messages updated to comply with the project's
standards.
Original issues fixed:
- Subject line now follows lowercase convention
- Type now uses valid conventional commit types
Co-Authored-By: github-actions[bot] <github-actions[bot]@users.noreply.github.com>1 parent 3f87553 commit 4b365d4
2,283 files changed
Lines changed: 192842 additions & 485963 deletions
File tree
- .github
- ISSUE_TEMPLATE
- codeql
- workflows
- .tools/actionlint
- docs
- man
- AiDotNetBenchmarkTests
- BenchmarkTests
- PhaseATestRunner
- docs
- design
- examples
- reasoning
- examples
- ConcreteExamples
- JitCompiler
- scripts
- src
- ActivationFunctions
- Agents
- AiDotNet.Serving
- Batching
- Configuration
- Controllers
- Models
- Monitoring
- Padding
- Scheduling
- Services
- AiDotNet.Tensors
- Compatibility
- Engines
- Helpers
- Images
- Interfaces
- LinearAlgebra
- NumericOperations
- Operators
- Polyfills
- AutoML
- Autodiff
- Testing
- Configuration
- CrossValidators
- DataProcessor
- Data
- Abstractions
- Graph
- Loaders
- RL
- Structures
- DecompositionMethods
- MatrixDecomposition
- TimeSeriesDecomposition
- Deployment
- Configuration
- Edge
- Export
- Onnx
- Mobile
- Android
- CoreML
- TensorFlowLite
- Optimization/Quantization
- Runtime
- TensorRT
- Diagnostics
- Diffusion
- Schedulers
- DistributedTraining
- Engines
- Enums
- AlgorithmTypes
- Evaluation
- Extensions
- Factories
- FeatureSelectors
- FitDetectors
- FitnessCalculators
- GaussianProcesses
- Genetics
- Helpers
- InferenceOptimization
- Core
- Examples
- IR
- Common
- HighLevel
- LowLevel
- Lowering
- Passes
- Inference
- PagedAttention
- SpeculativeDecoding
- Interfaces
- Interpolation
- Interpretability
- JitCompiler
- CodeGen
- IR
- Operations
- Memory
- Optimizations
- Runtime
- Testing
- Kernels
- KnowledgeDistillation
- Strategies
- Teachers
- LanguageModels
- Models
- LearningRateSchedulers
- LinearAlgebra
- LoRA
- Adapters
- Logging
- LossFunctions
- MetaLearning
- Algorithms
- Config
- Data
- Trainers
- Training
- Metrics
- MixedPrecision
- ModelCompression
- Models
- Inputs
- Options
- Results
- NestedLearning
- NeuralNetworks
- Attention
- Layers
- Tasks/Graph
- Normalizers
- NumericOperations
- Optimizers
- OutlierRemoval
- Polyfills
- PromptEngineering
- Analysis
- Chains
- Compression
- FewShot
- Optimization
- Templates
- Tools
- Prototypes
- Pruning
- RadialBasisFunctions
- Reasoning
- Aggregation
- Benchmarks
- Data
- Models
- Components
- ComputeScaling
- DomainSpecific
- Models
- Search
- Strategies
- Training
- Verification
- Regression
- Regularization
- ReinforcementLearning
- Agents
- Common
- Environments
- Policies
- Exploration
- ReplayBuffers
- RetrievalAugmentedGeneration
- AdvancedPatterns
- ChunkingStrategies
- Configuration
- ContextCompression
- DocumentStores
- Embeddings
- Evaluation
- Generators
- Graph
- Models
- QueryProcessors
- Rerankers
- Retrievers
- VectorSearch
- Indexes
- Metrics
- Serialization
- Serving/ContinuousBatching
- Statistics
- TimeSeries
- AnomalyDetection
- Tokenization
- Algorithms
- CodeTokenization
- Configuration
- Core
- HuggingFace
- Interfaces
- Models
- Specialized
- Vocabulary
- Tools
- TransferLearning
- Algorithms
- DomainAdaptation
- FeatureMapping
- Validation
- WaveletFunctions
- WindowFunctions
- testconsole
- Examples
- tests
- AiDotNet.Serving.Tests
- AiDotNet.Tensors.Benchmarks
- AiDotNet.Tensors.Tests
- Engines
- Operators
- TestHelpers
- AiDotNet.Tests
- Benchmarks
- Concurrency
- EndToEndTests
- Helpers
- InferenceOptimization
- IR
- IntegrationTests
- ActivationFunctions
- Diffusion
- FitnessCalculators
- GaussianProcesses
- Interpolation
- Kernels
- LearningRateSchedulers
- LinearAlgebra
- LossFunctions
- ModelCompression
- Normalizers
- OutlierRemoval
- RadialBasisFunctions
- Regularization
- Statistics
- TimeSeries
- Validation
- WaveletFunctions
- WindowFunctions
- JitCompiler
- PromptEngineering
- Pruning
- Recovery
- StressTests
- Tokenization
- UnitTests
- ActivationFunctions
- Attention
- AutoML
- Autodiff
- Data
- Diagnostics
- Diffusion
- Models
- Schedulers
- Encoding
- FeatureSelectors
- FitDetectors
- FitnessCalculators
- Genetics
- Helpers
- Inference
- Interpretability
- JitCompiler
- KnowledgeDistillation
- LearningRateSchedulers
- Logging
- LossFunctions
- MetaLearning
- Helpers
- MixedPrecision
- ModelCompression
- NestedLearning
- NeuralNetworks
- GANs
- Helpers
- Layers
- Optimizers
- RAG/Embeddings
- Regularization
- ReinforcementLearning
- RetrievalAugmentedGeneration
- ContextCompression
- DocumentStores
- Retrievers
- VectorSearch
- Indexes
- Metrics
- Serving
- TimeSeries
- Tokenization
- TransferLearning
- Reasoning
- Benchmarks
- Search
- Strategies
- Verification
- UnitTests
- Agents
- DistributedTraining
- LanguageModels
- MetaLearning
- Data
- TestHelpers
- Models/Generative/Diffusion
- NeuralNetworks
- Layers
- Normalizers
- Tools
Some content is hidden
Large Commits have some content hidden by default. Use the searchbox below for content that may be hidden.
This file was deleted.
| Original file line number | Diff line number | Diff line change | |
|---|---|---|---|
| |||
| 1 | + | |
| 2 | + | |
| 3 | + | |
| 4 | + | |
| 5 | + | |
| 6 | + | |
| 7 | + | |
| 8 | + | |
| 9 | + | |
| 10 | + | |
| 11 | + | |
| 12 | + | |
| 13 | + | |
| 14 | + | |
| 15 | + | |
| 16 | + | |
| 17 | + | |
| 18 | + | |
| 19 | + | |
| 20 | + | |
| 21 | + | |
0 commit comments