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Split up tensor operators, minor build adjustments #3702
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* 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
* [Engine] Deduplicate Variable Util * [NNVM] NNVM Imperative Invoke * [NNVM] Imperative improve speed * fix * fix
* [CYTHON] Checkin cython enhancement * fix lint * [DOC] Move common doc to base
* [EXEC] Support fcompute * Fix lint * fix lint
* Fix path in setup.py * revert the nnvm version
* [OPERATOR] Refactor Unary Ops * [OPERATOR] Refactor Binary Scalar Ops * Use alias
* [NDARRAY] Cython module for ndarray * More strict tests
* [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
* [IO] Python based ImageIter and Augumenter * fix * fix * fix
* [scala] nnvm op support * [scala] remove unused codes * fix scala native code style
* [R] Fix the R interface. remove man * Fix BN legacy issue
image io fix
* Update legacy op FBackwardInGradIndex * fix test
- gamma - gammaln - log1p - expm1
* move matrix op to nnvm * lint
…rd, fix roi pooling. (#3476)
* 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
deprecate
* fix nnvm scala compile err * scala test on jenkins
* fix nnvm scala compile err * scala test in jenkins * [scala] init NDArray with DType * [scala] dtype support in Executor
* added log10 operator * added log2 operator with test * added rint and fix * remove gradient calculation for rounding tests
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squash and rebase to resolve the conflicts? |
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closed for #4150 |
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