# krishanth7/everyo architecture

> Architecture diagram of the GitHub repository krishanth7/everyo, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-11-10). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/krishanth7/everyo
- Repository: https://github.com/krishanth7/everyo

## Overview

EveryO is a CPU-first neural-computing framework for building and training small neural networks, evaluating them, and exporting supported models. Its documented learning loop runs from data and tensors through differentiable operations and model layers to loss, backpropagation, and optimizer updates. The graph also preserves documented data, inference, serialization, acceleration, interoperability, and experiment capabilities. Sampled trainer and operation references support internal links; several capability branches are represented by their exact tree paths, but their internal calls were not sampled.

Main entry points: [`everyo/training/trainer.py`](https://github.com/krishanth7/everyo/blob/main/everyo/training/trainer.py) (Training Loop), [`everyo/core/operations.py`](https://github.com/krishanth7/everyo/blob/main/everyo/core/operations.py) (Differentiable Operations), [`everyo/nn/layers.py`](https://github.com/krishanth7/everyo/blob/main/everyo/nn/layers.py) (Neural Network Layers), [`everyo/core/tensor.py`](https://github.com/krishanth7/everyo/blob/main/everyo/core/tensor.py) (Tensors and Autograd)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_core["Tensor Core"]
  node_tensor["Tensors and Autograd<br/>[tensor.py]"]
  node_operations["Differentiable Operations<br/>[operations.py]"]
  node_autograd["Gradient Engine<br/>[autograd.py]"]
  node_backend["NumPy Backend<br/>[numpy_backend.py]"]
end

subgraph group_model["Models and Training"]
  node_model_layers["Neural Network Layers<br/>[layers.py]"]
  node_embedding["Embedding Layer<br/>[embedding.py]"]
  node_losses["Loss Functions<br/>[losses.py]"]
  node_optimizer["Optimizers<br/>[optimizer.py]"]
  node_trainer["Training Loop<br/>[trainer.py]"]
  node_inference["Inference<br/>[inference.py]"]
end

subgraph group_data["Data and Evaluation"]
  node_data_prep["Data Preparation"]
  node_datasets["Datasets"]
  node_dataset["Dataset Abstractions<br/>[dataset.py]"]
  node_loader["Batch Loading<br/>[dataloader.py]"]
  node_evaluation["Evaluation<br/>[evaluation.py]"]
end

subgraph group_runtime["Runtime Integrations"]
  node_serialization["Save and Load"]
  node_onnx["ONNX Export<br/>[onnx_export.py]"]
  node_quantization["Dynamic Quantization<br/>[quantization.py]"]
  node_cuda["CUDA Operations<br/>[interface.py]"]
  node_cuda_native["CUDA Bindings<br/>[bindings.cpp]"]
  node_tensorflow["TensorFlow Reference"]
end

subgraph group_tools["Experiments and Assurance"]
  node_experiments["Experiment Tools<br/>[experiments.py]"]
  node_tracking["Experiment Tracking"]
  node_monitoring["Monitoring<br/>[monitoring.py]"]
  node_validation["Validation and Verification<br/>[validation.py]"]
  node_benchmarking["Benchmarking<br/>[benchmarking.py]"]
end

node_developer(("Developer"))

node_developer -->|"prepares data"| node_data_prep
node_data_prep -.->|"builds datasets"| node_dataset
node_developer -.->|"chooses data"| node_datasets
node_dataset -->|"feeds batches"| node_loader
node_developer -->|"creates tensors"| node_tensor
node_tensor -->|"uses operations"| node_operations
node_operations -->|"records gradients"| node_autograd
node_operations -.->|"dispatches computation"| node_backend
node_developer -->|"defines model"| node_model_layers
node_embedding -->|"calls indexing"| node_operations
node_model_layers -->|"computes loss"| node_losses
node_trainer -->|"reads batches"| node_loader
node_trainer -->|"uses gradient control"| node_autograd
node_trainer -->|"updates parameters"| node_optimizer
node_trainer -->|"trains model"| node_model_layers
node_trainer -.->|"evaluates model"| node_evaluation
node_developer -->|"evaluates results"| node_evaluation
node_developer -.->|"requests predictions"| node_inference
node_developer -->|"saves or loads"| node_serialization
node_developer -->|"exports model"| node_onnx
node_developer -->|"quantizes model"| node_quantization
node_operations -->|"dispatches kernels"| node_cuda
node_cuda -->|"calls bindings"| node_cuda_native
node_developer -->|"cross-checks numerics"| node_tensorflow
node_developer -.->|"runs experiments"| node_experiments
node_experiments -.->|"records runs"| node_tracking
node_developer -.->|"observes runtime"| node_monitoring
node_developer -->|"checks behavior"| node_validation
node_developer -->|"measures performance"| node_benchmarking

click node_data_prep "https://github.com/krishanth7/everyo/tree/main/everyo/data"
click node_datasets "https://github.com/krishanth7/everyo/tree/main/everyo/datasets"
click node_dataset "https://github.com/krishanth7/everyo/blob/main/everyo/data/dataset.py"
click node_loader "https://github.com/krishanth7/everyo/blob/main/everyo/data/dataloader.py"
click node_tensor "https://github.com/krishanth7/everyo/blob/main/everyo/core/tensor.py"
click node_operations "https://github.com/krishanth7/everyo/blob/main/everyo/core/operations.py"
click node_autograd "https://github.com/krishanth7/everyo/blob/main/everyo/core/autograd.py"
click node_backend "https://github.com/krishanth7/everyo/blob/main/everyo/backends/numpy_backend.py"
click node_model_layers "https://github.com/krishanth7/everyo/blob/main/everyo/nn/layers.py"
click node_embedding "https://github.com/krishanth7/everyo/blob/main/everyo/nn/embedding.py"
click node_losses "https://github.com/krishanth7/everyo/blob/main/everyo/nn/losses.py"
click node_optimizer "https://github.com/krishanth7/everyo/blob/main/everyo/optim/optimizer.py"
click node_trainer "https://github.com/krishanth7/everyo/blob/main/everyo/training/trainer.py"
click node_evaluation "https://github.com/krishanth7/everyo/blob/main/everyo/evaluation.py"
click node_inference "https://github.com/krishanth7/everyo/blob/main/everyo/inference.py"
click node_serialization "https://github.com/krishanth7/everyo/tree/main/everyo/serialization"
click node_onnx "https://github.com/krishanth7/everyo/blob/main/everyo/serialization/onnx_export.py"
click node_quantization "https://github.com/krishanth7/everyo/blob/main/everyo/quantization.py"
click node_cuda "https://github.com/krishanth7/everyo/blob/main/everyo/cuda/interface.py"
click node_cuda_native "https://github.com/krishanth7/everyo/blob/main/cuda/bindings/bindings.cpp"
click node_tensorflow "https://github.com/krishanth7/everyo/blob/main/everyo/backends/tensorflow_backend.py"
click node_experiments "https://github.com/krishanth7/everyo/blob/main/everyo/experiments.py"
click node_tracking "https://github.com/krishanth7/everyo/blob/main/everyo/experiment_tracking.py"
click node_monitoring "https://github.com/krishanth7/everyo/blob/main/everyo/monitoring.py"
click node_validation "https://github.com/krishanth7/everyo/blob/main/everyo/validation.py"
click node_benchmarking "https://github.com/krishanth7/everyo/blob/main/everyo/benchmarking.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_tensor,node_operations,node_autograd,node_backend toneBlue
class node_model_layers,node_embedding,node_losses,node_optimizer,node_trainer,node_inference toneAmber
class node_data_prep,node_datasets,node_dataset,node_loader,node_evaluation toneMint
class node_serialization,node_onnx,node_quantization,node_cuda,node_cuda_native,node_tensorflow toneRose
class node_experiments,node_tracking,node_monitoring,node_validation,node_benchmarking,node_developer toneIndigo
```

## Components

### Tensor Core

- [Tensors and Autograd](https://github.com/krishanth7/everyo/blob/main/everyo/core/tensor.py): `everyo/core/tensor.py`
- [Differentiable Operations](https://github.com/krishanth7/everyo/blob/main/everyo/core/operations.py): `everyo/core/operations.py`
- [Gradient Engine](https://github.com/krishanth7/everyo/blob/main/everyo/core/autograd.py): `everyo/core/autograd.py`
- [NumPy Backend](https://github.com/krishanth7/everyo/blob/main/everyo/backends/numpy_backend.py): `everyo/backends/numpy_backend.py`

### Models and Training

- [Neural Network Layers](https://github.com/krishanth7/everyo/blob/main/everyo/nn/layers.py): `everyo/nn/layers.py`
- [Embedding Layer](https://github.com/krishanth7/everyo/blob/main/everyo/nn/embedding.py): `everyo/nn/embedding.py`
- [Loss Functions](https://github.com/krishanth7/everyo/blob/main/everyo/nn/losses.py): `everyo/nn/losses.py`
- [Optimizers](https://github.com/krishanth7/everyo/blob/main/everyo/optim/optimizer.py): `everyo/optim/optimizer.py`
- [Training Loop](https://github.com/krishanth7/everyo/blob/main/everyo/training/trainer.py): `everyo/training/trainer.py`
- [Inference](https://github.com/krishanth7/everyo/blob/main/everyo/inference.py): `everyo/inference.py`

### Data and Evaluation

- [Data Preparation](https://github.com/krishanth7/everyo/tree/main/everyo/data): `everyo/data`
- [Datasets](https://github.com/krishanth7/everyo/tree/main/everyo/datasets): `everyo/datasets`
- [Dataset Abstractions](https://github.com/krishanth7/everyo/blob/main/everyo/data/dataset.py): `everyo/data/dataset.py`
- [Batch Loading](https://github.com/krishanth7/everyo/blob/main/everyo/data/dataloader.py): `everyo/data/dataloader.py`
- [Evaluation](https://github.com/krishanth7/everyo/blob/main/everyo/evaluation.py): `everyo/evaluation.py`

### Runtime Integrations

- [Save and Load](https://github.com/krishanth7/everyo/tree/main/everyo/serialization): `everyo/serialization`
- [ONNX Export](https://github.com/krishanth7/everyo/blob/main/everyo/serialization/onnx_export.py): `everyo/serialization/onnx_export.py`
- [Dynamic Quantization](https://github.com/krishanth7/everyo/blob/main/everyo/quantization.py): `everyo/quantization.py`
- [CUDA Operations](https://github.com/krishanth7/everyo/blob/main/everyo/cuda/interface.py): `everyo/cuda/interface.py`
- [CUDA Bindings](https://github.com/krishanth7/everyo/blob/main/cuda/bindings/bindings.cpp): `cuda/bindings/bindings.cpp`
- [TensorFlow Reference](https://github.com/krishanth7/everyo/blob/main/everyo/backends/tensorflow_backend.py): `everyo/backends/tensorflow_backend.py`

### Experiments and Assurance

- [Experiment Tools](https://github.com/krishanth7/everyo/blob/main/everyo/experiments.py): `everyo/experiments.py`
- [Experiment Tracking](https://github.com/krishanth7/everyo/blob/main/everyo/experiment_tracking.py): `everyo/experiment_tracking.py`
- [Monitoring](https://github.com/krishanth7/everyo/blob/main/everyo/monitoring.py): `everyo/monitoring.py`
- [Validation and Verification](https://github.com/krishanth7/everyo/blob/main/everyo/validation.py): `everyo/validation.py`
- [Benchmarking](https://github.com/krishanth7/everyo/blob/main/everyo/benchmarking.py): `everyo/benchmarking.py`

### Other components

- **Developer**

## Connections

- Developer → Data Preparation: prepares data (evidence: `README.md`)
- Data Preparation → Dataset Abstractions: builds datasets
- Developer → Datasets: chooses data
- Dataset Abstractions → Batch Loading: feeds batches (evidence: `everyo/data/dataset.py`)
- Developer → Tensors and Autograd: creates tensors (evidence: `README.md`)
- Tensors and Autograd → Differentiable Operations: uses operations (evidence: `README.md`)
- Differentiable Operations → Gradient Engine: records gradients (evidence: `everyo/core/operations.py`)
- Differentiable Operations → NumPy Backend: dispatches computation
- Developer → Neural Network Layers: defines model (evidence: `README.md`)
- Embedding Layer → Differentiable Operations: calls indexing (evidence: `everyo/nn/embedding.py`)
- Neural Network Layers → Loss Functions: computes loss (evidence: `README.md`)
- Training Loop → Batch Loading: reads batches (evidence: `everyo/training/trainer.py`)
- Training Loop → Gradient Engine: uses gradient control (evidence: `everyo/training/trainer.py`)
- Training Loop → Optimizers: updates parameters (evidence: `README.md`)
- Training Loop → Neural Network Layers: trains model (evidence: `everyo/training/trainer.py`)
- Training Loop → Evaluation: evaluates model
- Developer → Evaluation: evaluates results (evidence: `README.md`)
- Developer → Inference: requests predictions
- Developer → Save and Load: saves or loads (evidence: `README.md`)
- Developer → ONNX Export: exports model (evidence: `README.md`)
- Developer → Dynamic Quantization: quantizes model (evidence: `README.md`)
- Differentiable Operations → CUDA Operations: dispatches kernels (evidence: `everyo/core/operations.py`)
- CUDA Operations → CUDA Bindings: calls bindings (evidence: `everyo/cuda/interface.py`)
- Developer → TensorFlow Reference: cross-checks numerics (evidence: `README.md`)
- Developer → Experiment Tools: runs experiments
- Experiment Tools → Experiment Tracking: records runs
- Developer → Monitoring: observes runtime
- Developer → Validation and Verification: checks behavior (evidence: `README.md`)
- Developer → Benchmarking: measures performance (evidence: `README.md`)