How joeyye-work/tensorflow works
TensorFlow is an end-to-end machine-learning platform with Python and C++ APIs and execution across hardware devices. Its principal workflow is to submit tensor operations through an API, execute them in eager or graph-oriented runtime paths, and return tensor results; training, distribution, model loading, compilation, and accelerator integrations are major branches. The README establishes the broad product scope; source excerpts are partial, so links for unsampled subsystems are limited to relationships supported by the tree and documented capabilities.
Main entry points: kernels.cc Operation Kernels · c_api.cc Eager Runtime · __init__.py Python API · client_session.cc Client Session
Components 17
User Interfaces
- Python API
tensorflow/__init__.py - C API
tensorflow/c/c_api.cc - C++ Operations
tensorflow/cc/framework/ops.cc
Execution Runtime
- Eager Runtime
tensorflow/c/eager/c_api.cc - Client Session
tensorflow/cc/client/client_session.cc - Operation Kernels
tensorflow/c/kernels.cc
Training and Distribution
- Gradient Computation
tensorflow/cc/framework/gradients.cc - Central Distribution
tensorflow/python/distribute/central_storage_strategy.py
Models and Compilation
- SavedModel Load
tensorflow/cc/saved_model/loader.cc - XLA Compilation
tensorflow/compiler/jit/mark_for_compilation_pass.cc - StableHLO Quantization
tensorflow/compiler/mlir/quantization/stablehlo/cc/tf_pass_pipeline.cc
Device Integrations
- TensorRT Operation
tensorflow/compiler/tf2tensorrt/ops/trt_engine_op.cc - TensorRT Execution
tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc - Pluggable Device API
tensorflow/c/experimental/next_pluggable_device/c_api.cc - TPU Embedding State
tensorflow/core/tpu/kernels/tpu_embedding_engine_state_interface.h - Lite Benchmark Storage
tensorflow/lite/experimental/acceleration/mini_benchmark/fb_storage.h
Other components
- Developer
Connections 18
- Developer → Python API: calls
- Developer → C API: calls
- Developer → C++ Operations: calls
- Python API → Eager Runtime: submits operations
- C API → Eager Runtime: creates operations
- C++ Operations → Client Session: builds graph
- Client Session → Operation Kernels: executes operations
- Eager Runtime → Operation Kernels: dispatches operations
- Gradient Computation → Operation Kernels: defines derivatives
- Central Distribution → Python API: distributes training
- SavedModel Load → Client Session: restores graph
- XLA Compilation → Operation Kernels: compiles operations
- StableHLO Quantization → XLA Compilation: transforms graphs
- TensorRT Operation → TensorRT Execution: registers operation
- TensorRT Execution → Operation Kernels: falls back
- Pluggable Device API → Eager Runtime: extends execution
- TPU Embedding State → Operation Kernels: provides TPU state
- Lite Benchmark Storage → Developer: stores benchmark records