Blobs: unified data, 抽象理解為caffe設(shè)計(jì)的標(biāo)準(zhǔn)格式的數(shù)據(jù)
Layers: data process，抽象理解為數(shù)據(jù)的處理
Nets: layer-by-layer schema，bottom-to-top.抽象理解為層之間的鏈接方式，由下至上

Blob storage and communication

blobs is a unified N-Dimensional array, and it can be used in store and process batches of images, model parameters, and derivatives for optimization.
for example:
(1) 4D blobs is the batch of image data, is N*K*W*H, the N is the num of the images and the K is the channels
(2) 2D blobs (shape (N, D)) and call the InnerProductLayer

Implementation Details

two trucks: data and diff原始數(shù)據(jù)與差值數(shù)據(jù)，前向的data和用于后向的diff
two ways: const and mutable常量與變量

Layer computation and connections

A layer takes input through bottom connections and makes output through top connections.

Net definition and operation

caffe model is a end-to-end model
end-to-end: 即輸入是原始數(shù)據(jù)、輸出是最終的loss，通過(guò)loss來(lái)反饋并修正網(wǎng)絡(luò)參數(shù)。沒(méi)有數(shù)據(jù)提取再輸入等過(guò)程。

Model format

The models are defined in plaintext protocol buffer schema (prototxt) while the learned models are serialized as binary protocol buffer (binaryproto) .caffemodel files.

總結(jié)

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