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[IO] Python based ImageIter and Augumenter #3227
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@piiswrong i just saw it. i'll check it next week. (3 holiday days and i have no computer at home:) ) |
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need rebase against master |
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Sep 20, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Sep 23, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Sep 27, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Oct 8, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Oct 9, 2016
* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
piiswrong
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Oct 19, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Oct 19, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
piiswrong
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Oct 19, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
piiswrong
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Oct 19, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
tqchen
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Oct 31, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
tqchen
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Oct 31, 2016
* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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Nov 17, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Nov 17, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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Nov 18, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Nov 18, 2016
* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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Nov 30, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Nov 30, 2016
* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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Dec 11, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Dec 11, 2016
* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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Dec 24, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Dec 24, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
piiswrong
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Dec 29, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Dec 29, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
piiswrong
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Dec 29, 2016
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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Dec 29, 2016
* NNVM Refactor (apache#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (apache#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (apache#3214) * [PYTHON] Optional Cython Module for Symbols (apache#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (apache#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (apache#3261) * Fix path in setup.py (apache#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (apache#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (apache#3290) * Fix breaking changes after pull master (apache#3291) * [CYTHON] Cython module for NDArray (apache#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (apache#3303) * Update run_test.sh * add nnvm cmake with windows (apache#3255) * [WIP] binary broadcast wip (apache#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (apache#3308) * [IO] Python based ImageIter and Augumenter (apache#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (apache#3314) * fix cpython in windows (apache#3309) * Add Mathematical functions (apache#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (apache#3335) * add recent examples, collect some missing tutorials (apache#3340) * Improving docs & utilities for distributed training example. (apache#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (apache#3346) * Add channel_ to Shape2D calculation (apache#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (apache#3186) * RNN cell demo with ptb LSTM language model (apache#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (apache#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (apache#3238) * Fix little bug on context (apache#3202) * add PennTreeBank Language Model using lstm model in R (apache#2659) * Add function 'print_summary' and some revise (apache#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (apache#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (apache#3217) [scala] auto-generate Symbol functions * fix spelling errors (apache#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (apache#3260) * Copy slice along arbitrary axis (apache#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (apache#3264) * fix PReLU backward computing (apache#3277) * Add `reverse` option in Reshape (apache#3280) * add scala example, end2end neural-style (apache#3267) add scala example, end2end neural-style * Improve multi-GPU performance (apache#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (apache#3293) * Fix newer version of gtest and cpptest (apache#3294) * when set use_global_stats then do not use cudnn (apache#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (apache#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (apache#3270) * add support for building on power (apache#3302) * add recent examples, collect some missing tutorials (apache#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (apache#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (apache#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (apache#3369) * Fix metric & im2rec.py (apache#3375) image io fix * Update legacy op FBackwardInGradIndex (apache#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (apache#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (apache#3337) - gamma - gammaln - log1p - expm1 * fix kv build (apache#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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* [IO] Python based ImageIter and Augumenter * fix * fix * fix
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* NNVM Refactor (#3194) * Init nnvm change * temp checkin * Move TShape to NNVM * Redirect Symbolic API to NNVM * Add Op Prop Adapter * Finish migrate in shape infer * Pass all symbolic test * temp commit * enable aux data * [EXEC] Basic version of exec for forward only * [EXEC] Enable most optimizations, still wait grad and context * fix legacy op with latest one * Update NNVM NodeRef * Adapt to newer interface * ALl registry of backop is complete * temp commit * Hack finish backward pass * [EXEC] One day pass * [EXEC] Pass all operator unittest * [EXEC] enable model parallel * Fully pass all legacy tests * Remove legacy symbolic code * update news * Make travis compile * Fix python3 * Update viz module to new json format * [NNVM] Imperative Invoke (#3208) * [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix * [scala] link libnnvm.a (#3214) * [PYTHON] Optional Cython Module for Symbols (#3242) * [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base * [EXEC] Support fcompute (#3249) * [EXEC] Support fcompute * Fix lint * fix lint * [OP] Add alias support (#3261) * Fix path in setup.py (#3276) * Fix path in setup.py * revert the nnvm version * [WIP] Element wise op refactor (#3245) * [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias * update nnvm version (#3290) * Fix breaking changes after pull master (#3291) * [CYTHON] Cython module for NDArray (#3292) * [NDARRAY] Cython module for ndarray * More strict tests * [NNVM] change of attr to set_attr (#3303) * Update run_test.sh * add nnvm cmake with windows (#3255) * [WIP] binary broadcast wip (#3301) * [WIP] binary broadcast wip [OPERATOR] Binary Broadcast ops fix lint lint fix max and min update submodule before removing reduce axis broad cast reduce ops * update * fix * fix warning * fix * x (#3308) * [IO] Python based ImageIter and Augumenter (#3227) * [IO] Python based ImageIter and Augumenter * fix * fix * fix * [OPT] NNVM Optimizer (#3314) * fix cpython in windows (#3309) * Add Mathematical functions (#3317) * fix image io * add hypot degrees radians cosh sinh tanh arcsinh arccosh arctanh (#3335) * add recent examples, collect some missing tutorials (#3340) * Improving docs & utilities for distributed training example. (#3341) * add init dict * disable SSE for arm hardware e.g. Raspberry Pi (#3346) * Add channel_ to Shape2D calculation (#3181) * Add channel_ to Shape2D calculation * scalapkg, add example multitask (#3186) * RNN cell demo with ptb LSTM language model (#3197) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * Bulk lint fix (#3211) * [TENSOR] Add FlatTo1D for all elementwise ops (#3238) * Fix little bug on context (#3202) * add PennTreeBank Language Model using lstm model in R (#2659) * Add function 'print_summary' and some revise (#3161) * Add function 'print_summary' and some revise Add function 'print_summary' for print detail information of network, and format argument was add in 'plot_network'. You can use 'print_summary' like: """ net = get_symbol(1000) shape = {'softmax_label': (64, 12), 'data': (64, 3, 224, 224)} mx.viz.print_summary(net, shape=shape) """ If without shape, the number of arguments would be nonsense currently. * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Update visualization.py * Added my CmakeLists.txt for caffe plugin, etc. * Revert "fix travis scala test config" (#3246) This reverts parts of commit 3e15f62. Reenables testing the Julia bindings * [Scala] Code generation for Symbol (#3217) [scala] auto-generate Symbol functions * fix spelling errors (#3258) Also align grammar and punctuation in short descriptions of features * fix typo in run_test.sh (#3260) * Copy slice along arbitrary axis (#3259) * rnn-cell demo (push to server for testing) * a running example with cuDNN RNN cell * add copyslice along arbitrary axis for NDArray * copy_slice_to as an ndarray operator * Python interface to the _copy_slice_to operator * fix lint error * Enable concatenation for dim-1 vectors (#3264) * fix PReLU backward computing (#3277) * Add `reverse` option in Reshape (#3280) * add scala example, end2end neural-style (#3267) add scala example, end2end neural-style * Improve multi-GPU performance (#3241) * update kvstore * update model.py * bandwith tool * update readme * tiny * fix lint * fix batch size of dist_device_sync * fix * fix perf problem of kvstore when only using a single device * roll back to previous strategy how to choose update_on_kvsotre * add an optionl MXNET_ENABLE_GPU_P2P to control whether or not use p2p * update dmlccore (#3293) * Fix newer version of gtest and cpptest (#3294) * when set use_global_stats then do not use cudnn (#3289) * when set use_global_stats then do not use cudnn * fix batch norm with use_global_stats * Fix req+reserve_space in cudnn_rnn (#3274) Fix req Fix reserve_space Allocate reserve_space using Storage * add cudnn off option in Convolution (#3270) * add support for building on power (#3302) * add recent examples, collect some missing tutorials (#3340) * CMake for caffe plugin * Fix metric & im2rec.py * [Scala] Nnvm ops for NDArray & Symbol (#3361) * [scala] nnvm op support * [scala] remove unused codes * fix scala native code style * [R] Fix the R interface (#3334) * [R] Fix the R interface. remove man * Fix BN legacy issue * Locate compiled library on Windows (#3369) * Fix metric & im2rec.py (#3375) image io fix * Update legacy op FBackwardInGradIndex (#3376) * Update legacy op FBackwardInGradIndex * fix test * Fix for LRN Layer (#3366) * fixed cpu forward bug * added out_data[lrn_enum::kOut] as backward req. * removed lint * removed duplicate out_data[lrn_enum::kTmpNorm], * removed inplace option * add backward index * include some special functions (#3337) - gamma - gammaln - log1p - expm1 * fix kv build (#3385) * initial profiler branch based on dmlc/mxnet:nnvm * [profiler] add profiler & modify engine API * [profiler] add USE_PROFILER compile flag & modify code for changed engine api * [profiler] add c_api interface & modify graph_executor * [profiler] add python api * [profiler] typo & lint error * [profiler] reduce overhead & add PROFIELR_MESSAGE_FUNCNAME macro * [profiler] remove profiling argument from PushSync/PushAsync * [profiler] refactor profiler.h/.cc * [profiler] improve readability * [profiler] typo && add TODO comment * [profiler] fix ndarray op name & add WaitForVar back * [profiler] add example/profiler/profiler_ndarray.py * [profiler] fix memleak by using op->name * [profiler] fix lint * [profiler] fix lint
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@tornadomeet @mli