Documentation

• Installation
  • From Conda
  • From source
    • Use Conda to build SINGA
    • Use native tools to build SINGA on Ubuntu
    • Compile SINGA on Windows
    • More details about the compilation options
    • USE_MODULES
      • USE_PYTHON
      • USE_CUDA
      • USE_OPENCL
      • USE_MKLDNN
      • PACKAGE
  • FAQ
• Software Stack
  • Core
  • Model
  • IO
• Benchmark for Distributed training
• Device
  • Specific devices
  • Python API
  • CPP API
• Tensor
  • Tensor implementation
  • Python API
  • CPP API
• Layer
  • Python API
  • CPP API
• FeedForward Net
• Initializer
  • Python API
  • CPP API
• Loss
• Metric
• Optimizer
• Autograd in Singa
  • Relevant Modules
    • Tensor
    • Operation
    • Layer
  • Examples
    • Operation only
      • Import packages
      • Create weight matrix and bias vector
      • Training
    • Operation + Layer
      • Create the layers
      • Define the forward function
      • Training
• Data
• Image Tool
• Snapshot
• Caffe Converter
• Utils
• Model Zoo
  • Train CNN over Cifar-10
    • Instructions
      • SINGA installation
      • Data preparation
      • Training
      • Prediction
  • Train Char-RNN over plain text
    • Instructions
  • Train AlexNet over ImageNet
    • Instructions
      • Compile SINGA
      • Data download
      • Data preprocessing
      • Training
  • name: GoogleNet on ImageNet SINGA version: 1.0.1 SINGA commit: 8c990f7da2de220e8a012c6a8ecc897dc7532744 parameter_url: https://s3-ap-southeast-1.amazonaws.com/dlfile/bvlc_googlenet.tar.gz parameter_sha1: 0a88e8948b1abca3badfd8d090d6be03f8d7655d license: unrestricted https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet
  • Image Classification using GoogleNet
    • Instructions
    • Details