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error #234

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sjm1992st opened this issue Jul 17, 2016 · 2 comments
Closed

error #234

sjm1992st opened this issue Jul 17, 2016 · 2 comments
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@sjm1992st
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when i change the ''int minibatch_size = 10;'' to ''int minibatch_size = 64;'' in main.cpp line of 102,something error happened.
@sjm1992st
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vs2013 prompts a breakpoint in loss_function.h line 117 ( assert(y.size() == t.size());), In debug mode,i see the t.size=32 and y.size=64

@nyanp
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nyanp commented Jul 18, 2016

@sjm1992st
Thanks for your report! It is caused when train_images.size() % minibatch_size != 0. I'll fix it soon :)

@nyanp nyanp added the bug label Jul 18, 2016
@nyanp nyanp closed this as completed in 9322585 Jul 18, 2016
nyanp added a commit that referenced this issue Jul 21, 2016
@nyanp
Merge master into feat/generic-computational-graph (#241)
5cf8629 
* v0.0.1 -> v.0.1.0

- Now we can handle non-sequential model as ```network<graph>``` #108
#153
- Catch up the latest format of caffe's proto #162
- Improve the default behaviour of re-init weight #136
- Add more tests and documents #73
- Remove dependency of OpenCV in MNIST example

* Update layer.h

* Added test case in separate cpp file to force link errors if there are duplicate symbols when including tiny_cnn.h in multiple .cpp files.

* Fix linker error due to duplicate symbols.

* Update README.md

- Update layer catalogue
- Upgrade example codes to v0.1.0

* Removed a repeated include.

* Bug Fix: network::test was broken in multi-thread. closes #185

* fix test_with_stb_image.cpp and typos (tiny_cnn_hrds => tiny_cnn_hdrs) in CMakeLists.txt (#189)

* fix a compile error and warnings when the type float_t is a typedef of float (#191)

* fix README.md (#194)

* Refactor layer to handle minibatch at once (#181)

* get rid of unnecessary compiler warnings (C4018: '>=': signed/unsigned mismatch)

* refactor layer to handle a minibatch at once (previously individual input samples only)

* move new functions apply_cost_if_defined and add_sample_gradient to an anonymous namespace in order to hopefully make AppVeyor happy

* revert the changes to test_network.h

* minor type fixes to get rid of compiler warnings

* make quick changes to deconvolutional_layer so that the examples at least compile

* fix backward_activation to use all samples

* remove unused variables

* update picotest to fix operator precedence

* fix input data ordering

* fix overriding prev_delta

* change gradients to be per-sample as well

* remove unused variables

* fix indexing in convolutional_layer

* also in dropout_layer, have a different mask vector for each sample of a minibatch

* deconvolution_layer: fix allocating space for prev_out_ and cur_out_padded_

* add gradient check for minibatch

* minor: change types to fix some compiler warnings

* Add application links to doc, #158

* Fixed typo (#205)

* Add a contribution document

* fixed typo (#216)

* Add batch normalization #147

* Add batch normalization prototype & remove batch-level parallelsim #147

* add backward pass & formatting

* Add unit test for forward pass

* Add numerical check for batchnorm

* Fix convolutional::brop for pointing correct storage

* Fix bprop in batchnorm

* Change an order of arguments in ctor

to keep consistency to other layers

* add batch normalization layer

* fix compiler error on deconvolutional-layer

* Implement caffe importer

* Revert changes around calc_delta

* Fix backprop of bias factor in conv layer

* Fix compilation error in MSVC2013, close #218 #231

* Add slice layer (#233)

* Bug Fix #234

* Add BSD-3 license file #228

* Fix handling non-square input data in caffemodel #227

* Add power layer #227

* Generalization of loss functions + Correcting MSE (#232)

* generalization of loss function to vectors (solves wrong MSE)

* removed unnecessary function due to loss function generalization

* loss function df operating on vec_t

* correct df of mse

* missin brackets

* fix compile errors in conv-layer

* remove sample_count
edgarriba pushed a commit to edgarriba/tiny-cnn that referenced this issue Aug 8, 2016
@nyanp
Merge master into feat/generic-computational-graph (tiny-dnn#241)
f294033 
* v0.0.1 -> v.0.1.0

- Now we can handle non-sequential model as ```network<graph>``` tiny-dnn#108
tiny-dnn#153
- Catch up the latest format of caffe's proto tiny-dnn#162
- Improve the default behaviour of re-init weight tiny-dnn#136
- Add more tests and documents tiny-dnn#73
- Remove dependency of OpenCV in MNIST example

* Update layer.h

* Added test case in separate cpp file to force link errors if there are duplicate symbols when including tiny_cnn.h in multiple .cpp files.

* Fix linker error due to duplicate symbols.

* Update README.md

- Update layer catalogue
- Upgrade example codes to v0.1.0

* Removed a repeated include.

* Bug Fix: network::test was broken in multi-thread. closes tiny-dnn#185

* fix test_with_stb_image.cpp and typos (tiny_cnn_hrds => tiny_cnn_hdrs) in CMakeLists.txt (tiny-dnn#189)

* fix a compile error and warnings when the type float_t is a typedef of float (tiny-dnn#191)

* fix README.md (tiny-dnn#194)

* Refactor layer to handle minibatch at once (tiny-dnn#181)

* get rid of unnecessary compiler warnings (C4018: '>=': signed/unsigned mismatch)

* refactor layer to handle a minibatch at once (previously individual input samples only)

* move new functions apply_cost_if_defined and add_sample_gradient to an anonymous namespace in order to hopefully make AppVeyor happy

* revert the changes to test_network.h

* minor type fixes to get rid of compiler warnings

* make quick changes to deconvolutional_layer so that the examples at least compile

* fix backward_activation to use all samples

* remove unused variables

* update picotest to fix operator precedence

* fix input data ordering

* fix overriding prev_delta

* change gradients to be per-sample as well

* remove unused variables

* fix indexing in convolutional_layer

* also in dropout_layer, have a different mask vector for each sample of a minibatch

* deconvolution_layer: fix allocating space for prev_out_ and cur_out_padded_

* add gradient check for minibatch

* minor: change types to fix some compiler warnings

* Add application links to doc, tiny-dnn#158

* Fixed typo (tiny-dnn#205)

* Add a contribution document

* fixed typo (tiny-dnn#216)

* Add batch normalization tiny-dnn#147

* Add batch normalization prototype & remove batch-level parallelsim tiny-dnn#147

* add backward pass & formatting

* Add unit test for forward pass

* Add numerical check for batchnorm

* Fix convolutional::brop for pointing correct storage

* Fix bprop in batchnorm

* Change an order of arguments in ctor

to keep consistency to other layers

* add batch normalization layer

* fix compiler error on deconvolutional-layer

* Implement caffe importer

* Revert changes around calc_delta

* Fix backprop of bias factor in conv layer

* Fix compilation error in MSVC2013, close tiny-dnn#218 tiny-dnn#231

* Add slice layer (tiny-dnn#233)

* Bug Fix tiny-dnn#234

* Add BSD-3 license file tiny-dnn#228

* Fix handling non-square input data in caffemodel tiny-dnn#227

* Add power layer tiny-dnn#227

* Generalization of loss functions + Correcting MSE (tiny-dnn#232)

* generalization of loss function to vectors (solves wrong MSE)

* removed unnecessary function due to loss function generalization

* loss function df operating on vec_t

* correct df of mse

* missin brackets

* fix compile errors in conv-layer

* remove sample_count
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