nnc
a deep learning framework from ccv
  • Overview
    • What’s NNC?
    • 1. Tensors, Commands and Streams
    • 2. Computation Graph
    • 3. Symbolic Graph
    • 4. Dynamic Graph
    • 5. Common Neural Network Primitives
    • Supplementary Materials
      • Toll-Free Bridging
      • Automatic Differentiation
      • while Type Sub-Graph
      • case..of Type Sub-Graph
      • Limits and Constraints
  • Technicals
    • The NNC Tensor Allocation Algorithm
      • Tensor Representation
      • Loop Representation
      • The Problem Definition
      • The Core Algorithm
      • Basic Structure
      • Candidate Selection
      • Insertion
      • Intuition
      • Loop
      • Multi-view Tensor
      • Loop with Efficient Tensor Allocation
      • Sub-Computation Graph
      • Conclusion
    • NNC Static Schedule A Graph
      • Stream
      • Static Schedule
      • while and case..of
    • NNC Dynamic Graph Execution
      • Naming The Variable
      • Tracing The Operation
      • Optimizations
      • Interoperability
      • Future Optimizations
      • Some Maybes
    • NNC Common Neural Network Primitives
      • Model
      • Model IO
      • Fit, Evaluate, Backward, Apply Gradients
    • NNC Dataframe
      • Operations on the Data
      • Iteration
      • Map
      • Reduce
      • Others
      • Use Dataframe with Addons
    • NNC Micro Ops
      • Describe Micro Ops
      • Parameters
      • Simplification
      • Loop-Fusion
      • Variable Substitution
      • Automatic Differentiation
  • API Reference
    • Level 0 API
      • Essentials
    • Level 1 API
      • The concept of meta-ops in Jittor is amazing
      • Tensors
      • Commands
      • Streams
      • Micro Ops
    • Level 2 API
      • Essentials
      • Others
    • Level 3 API
      • Essentials
      • Others
    • Level 3.5 API
      • Construct “switch” control structure in symbolic graph
      • Symbolic graph simplification
      • Construct a “while” loop in a symbolic graph
      • Automatic Differentiation
      • While Loop Essentials
      • Branching
      • Gradient-based Optimization
      • Graph Simplification
      • Automatic Graph Parallelization
      • Memory Compression
      • While Loop Others
    • Level 4 API
      • Essentials
    • Level 5 API
      • What is “dataframe” in ML?
      • Why to support comma-separated-values files in dataframe?
      • Models, layers, and Keras
      • Dataframe API
      • Dataframe Add-ons
      • Dataframe CSV Support
      • Model API
      • Model Add-ons
    • Convenience API
    • Available Commands
      • Backends
      • Commands
      • Command Identifiers
  • Swift for NNC
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