How idkhowtocodefr/tensorflow works
TensorFlow is an end-to-end machine-learning platform with Python and C++ APIs, graph and eager execution, automatic differentiation, distributed training, model persistence, and accelerator/compiler integrations. A typical workflow starts with a user building and executing tensor operations, optionally distributing training, then saving or deploying a model. The tree and sampled code support several distinct deployment paths, including TensorRT engine execution and StableHLO-to-TFLite conversion. Some broad subsystems are represented by their enclosing source directories because their implementation was not sampled; edges are limited to documented capabilities and visible calls.
Main entry points: common_runtime Core Runtime · __init__.py Python API · ops Tensor Ops · cc C++ API
Components 19
User APIs
- Python API
tensorflow/__init__.py - C++ API
tensorflow/cc - C API
tensorflow/c/c_api.cc
Execution and Training
- Tensor Ops
tensorflow/cc/ops - Gradients
tensorflow/cc/gradients - Central Storage
tensorflow/python/distribute/central_storage_strategy.py - Core Runtime
tensorflow/core/common_runtime - Device Kernels
tensorflow/c/kernels
Model Lifecycle
- SavedModel
tensorflow/cc/saved_model - Filesystem
tensorflow/c/experimental/filesystem
Compilation and Deployment
- XLA Compiler
tensorflow/compiler/jit - TFRT Pipeline
tensorflow/compiler/mlir/tfrt/transforms - TFLite Conversion
tensorflow/compiler/mlir/lite/python/stablehlo_tfl_pipeline.cc - StableHLO Quantization
tensorflow/compiler/mlir/quantization/stablehlo/cc/pass_pipeline.cc - TensorRT Op
tensorflow/compiler/tf2tensorrt/ops/trt_engine_op.cc - TensorRT Execution
tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc - TPU Engine State
tensorflow/core/tpu/kernels/tpu_embedding_engine_state_interface.h
Other components
- Developer
- TensorRT Engine
Connections 21
- Developer → Python API: calls
- Developer → C++ API: calls
- Developer → C API: calls
- Python API → Tensor Ops: builds operations
- C++ API → Tensor Ops: builds operations
- C API → Core Runtime: accesses runtime
- Tensor Ops → Core Runtime: executes
- Core Runtime → Device Kernels: dispatches
- Tensor Ops → Gradients: differentiates
- Python API → Central Storage: distributes training
- Central Storage → Core Runtime: runs replicas
- Python API → SavedModel: saves or loads
- SavedModel → Filesystem: accesses files
- Core Runtime → XLA Compiler: compiles graphs
- XLA Compiler → TFRT Pipeline: lowers execution
- Python API → TFLite Conversion: converts models
- StableHLO Quantization → TFLite Conversion: supports conversion
- Tensor Ops → TensorRT Op: invokes segment
- TensorRT Op → TensorRT Execution: runs kernel
- TensorRT Execution → TensorRT Engine: builds and executes
- Core Runtime → TPU Engine State: manages state