Proto commits in HyeonwooNoh/caffe

These commits are when the Protocol Buffers files have changed: (only the last 100 relevant commits are shown)

2015-09-07

seg_ctrl_cls layer is implemented

2015-08-19

seg binary ctrl layer is implemented

2015-06-09

caffe proto is added

The documentation is generated from this commit.

2015-05-28

tile unpooling is added

2015-05-27

average unpooling is added

2015-05-18

cls_label_base param is added

2015-05-07

SELECT_SEG_BINARY caffe.proto is added

2015-05-06

SEG_BINARY_LAYER is added

2015-04-30

window cls data parameter proto is added

WINDOW_CLS_DATA proto is added

2015-04-29

binary accuracy option is added to proto

BIN_ACCURACY proto is added

2015-04-11

window_inst_seg is implemented

instance seg data proto is added

2015-04-10

window_seg_data is added

2015-04-09

proto for IMAGE_SEG_DATA is added

2015-03-16

internal softmax is added to red accuracy layer

red accuracy layer proto define

proto error is fixed

red softmax loss param is added

RED_SOFTMAX_LOSS proto is defined

2015-03-14

BNMode is added[LEARN/INFERENCE]

2015-03-09

proto file for BN layer is added

2015-03-01

unpooling registry in layer_factory.cpp

unpooing layer definition is edited

unpooling proto definition added

2015-02-11

implement ignore label in eltwise_accracy_layer

2015-02-09

eltwise_accuracy proto is added

2015-01-03

Merge pull request #1663 from longjon/accum-grad Decouple the computational batch size and minibatch size by accumulating gradients

Merge pull request #1654 from longjon/softmax-missing-values Add missing value support to SoftmaxLossLayer

2014-12-31

zero-init param diffs and accumulate gradients (With layers whose backwards accumlate gradients), this effectively decouples the computational batch from the SGD minibatch. Each iteration accumulates gradients over iter_size batches, then parameters are updated.

add CropLayer for cropping one blob to another using induced coordinates

add DeconvolutionLayer, using BaseConvolutionLayer

add spatial normalization option to SoftmaxLossLayer With missing values (and batches of varying spatial dimension), normalizing each batch across instances can inappropriately give different instances different weights, so we give the option of simply normalizing by the batch size instead.

add missing value support to SoftmaxLossLayer

2014-10-16

Merge pull request #190 from sguada/new_lr_policies New lr policies, MultiStep and StepEarly

Added cache_images to WindowDataLayer Added root_folder to WindowDataLayer to locate images

Add root_folder to ImageDataLayer

2014-10-15

Added encoded datum to io

2014-10-14

Refactored leveldb and lmdb code.

2014-10-10

Added Multistep, Poly and Sigmoid learning rate decay policies Conflicts: include/caffe/solver.hpp src/caffe/proto/caffe.proto src/caffe/solver.cpp

2014-10-06

correct naming in comment and message about average_loss

2014-10-04

Merge pull request #1070 from sguada/move_data_mean Refactor data_transform to allow datum, cv:Mat and Blob transformation

2014-10-03

Added mean_value to specify mean channel substraction Added example of use to models/bvlc_reference_caffenet/train_val_mean_value.prototxt

Added global_pooling to set the kernel size equal to the bottom size Added check for padding and stride with global_pooling

Initial cv::Mat transformation Added cv::Mat transformation to ImageDataLayer Conflicts: src/caffe/layers/image_data_layer.cpp Added transform Datum to Blob Conflicts: src/caffe/layers/base_data_layer.cpp src/caffe/layers/base_data_layer.cu Added transform cv::Mat to Blob Added transform Vector<Datum> to Blob Conflicts: src/caffe/data_transformer.cpp

2014-10-02

Add ExpLayer to calculate y = base ^ (scale * x + shift)

caffe.proto: do some minor cleanup (fix comments, alphabetization)

2014-10-01

Merge pull request #1096 from qipeng/smoothed-cost Display averaged loss over the last several iterations

2014-09-22

added support for "k" LRN parameter to upgrade_proto

adds a parameter to the LRN layer (denoted as "k" in [Krizhevsky et al., NIPS 2012])

2014-09-19

Merge pull request #959 from nickcarlevaris/contrastive_loss Add contrastive loss layer, tests, and a siamese network example

2014-09-17

Display averaged loss over the last several iterations

2014-09-14

fix spelling error in caffe.proto

fix out-of-date next ID comment for SolverParameter

2014-09-08

Added contrastive loss layer, associated tests, and a siamese network example using shared weights and the contrastive loss.

Implemented elementwise max layer

2014-09-07

add cuDNN to build

groom proto: sort layer type parameters, put loss_weight after basics

add engine parameter for multiple computational strategies add `engine` switch to layers for selecting a computational backend when there is a choice. Currently the standard Caffe implementation is the only backend.

2014-09-05

Merge pull request #1036 from longjon/test-initialization-param Add test_initialization option to allow skipping initial test

2014-09-04

add SILENCE layer -- takes one or more inputs and produces no output This is useful for suppressing undesired outputs.

add test_initialization option to allow skipping initial test

2014-09-03

Move transform param one level up in the proto to reduce redundancy

Add transformer to the memory data layer

2014-09-01

cleanup caffe.proto

proto conflit, lint, and math_functions (compiler complaint)

Added L1 regularization support for the weights

fixed caffe.proto after a mistaken rebase

fixes after rebase

2014-08-25

Add "stable_prod_grad" option (on by default) to ELTWISE layer to compute the eltwise product gradient using a slower but stabler formula.

2014-08-22

restore old data transformation parameters for compatibility

2014-08-21

Refactor ImageDataLayer to use DataTransformer

2014-08-20

Refactor DataLayer using a new DataTransformer Start the refactoring of the datalayers to avoid data transformation code duplication. So far, only DataLayer has been done.

2014-08-17

cmake build system

2014-08-15

Add "not_stage" to NetStateRule to exclude NetStates with certain stages.

2014-08-14

Added absolute value layer, useful for implementation of siamese networks! This commit also replaces the default caffe_fabs with MKL/non-MKL implementation of Abs.

2014-08-13

Add loss_weight to proto, specifying coefficients for each top blob in the objective function.

2014-08-11

added cross-channel MVN, Mean-only normalization, added to layer factory, moved to common_layers

mean-variance normalization layer

2014-08-07

LICENSE governs the whole project so strip file headers

2014-08-04

Add 'snapshot_after_train' to SolverParameter to override the final snapshot.

2014-07-29

Add NetState message with phase, level, stage; NetStateRule message with filtering rules for Layers.

add h/w kernel size, stride, and pad for non-square filtering while keeping everything working as-is.

2014-07-26

Print blob L1 norms during forward/backward passes and updates if new "debug_info" field in SolverParameter is set.

2014-07-22

SliceLayer: post-rebase fixes, cleanup, etc. (some from changes suggested by @sguada). Test for both num & channels in forward & backward; use GaussianFiller so that tests are non-trivial.

Add split dim layer Differentiate top test blob vector size Rename to SplitLayer Add slicing points

2014-07-21

leaky relu + unit test

2014-07-19

Extend the ArgMaxLayer to output top k results

2014-07-18

cosmetics: add syntax = proto2

2014-07-05

add tests for rectangular pooling regions

2014-07-04

Update caffe.proto Add pad_h, pad_w, kernel_size_h, kernel_size_w, stride_h, stride_w to support pooling on rectangle regions.

2014-06-27

Update name of last added param.

Next LayerParameter proto id

Incorporate top_k param into AccuracyLayer and check it's value.

Add parameter for AccuracyLayer in proto.

2014-06-26

change weight blob field name to param

weight sharing

2014-06-21

Remove C_ mentions, extra spaces and change hinge_norm to norm

Removed L2HingeLoss class now a case within HingeLoss class Conflicts: include/caffe/vision_layers.hpp src/caffe/layers/loss_layer.cpp src/caffe/proto/caffe.proto src/caffe/test/test_l2_hinge_loss_layer.cpp