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[1.7] MXNet Extension PRs (#17623, #17569, #17762) #18063
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This PR adds support for passing the NDArrays from the existing optimize_for API down to the reviewSubgraph function in an external library. It also adds a new API for HybridBlock called optimize_for that can partition the model without running a forward pass.
Feature changes
Adds new API to HybridBlock optimize_for that partitions the model but does not call the cachedOp
Modifies the subgraph library example to optionally require args to be provided
Adds annotation on subgraph inputs for the name of the original param so that inputs can be mapped and passes annotations to input nodes of subgraphs
Adds support for tensors in MKLDNN format, calls Reorder2Default
New tests
Adds a new test to partition operators that directly consume params
add a new model to test where ops to be partitioned have args/params
Bug Fixes
fixes bug in passing ids vector by value instead of by reference
fixes bug in passing copies of attributes instead of by reference
fixes bug where _cached_graph was not updated after partitioning
fixes memory leak where user-specified attributes on subgraph ops were not freed if subgraph was rejected
fixes problem incorrectly indexing into shape/dtype maps when annotating the graph
Docs
Updates the README doc with the latest changes described above
samskalicky
requested review from
aaronmarkham,
anirudh2290,
eric-haibin-lin,
sergeykolychev and
szha
as code owners
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Hey @samskalicky , Thanks for submitting the PR
CI supported jobs: [centos-gpu, unix-gpu, unix-cpu, centos-cpu, windows-gpu, miscellaneous, sanity, windows-cpu, website, edge, clang] Note: |
* Added enum for sparse storage * Add structure for Dense and Sparse * redesign the data structure for MXSparse * pull out aux data from sparse NDArray * Added more sparse arguments to API interface * Passed sparse from c_api to lib_api.h and set in MXTensor * Fix indent * fix segfault * Fix NDArray to MXTensor errors * Add a sample of sparse(CSR) transpose * Make CSR transpose temporarily work by hardcoding * Fixed sparse output size(Refined) * Add tests for symbolic and stateful ops * Added a sample for row sparse transpose * Added real row sparse transpose * Fix output size issue by adding lambda for CheckAndAlloc() * Fix mixed storage formats error * Added infer storage type function * resolve comments * Set inferSType as optional function * Resolve comments * Add error messages * Resolve comments * verify transpose ops results * fix sanity check * update MX_LIBRARY_VERSION to 5
samskalicky
changed the title
Add random number generator support for custom operator libraries. Design: We pass from MXNet the initialized and seeded states, located on CPU and GPU, to custom library. So user could use those seeds to generate deterministic values from a given seed passed to MXNet. Basically this workflow: mx.random.seed(128) r1 = mx.nd.some_custom_random_op(data) mx.random.seed(128) r2 = mx.nd.some_custom_random_op(data) assert (r1 == r2) This PR does not let custom library generate exactly the same sequence of random numbers comparing to MXNet This is a continuation of the custom operator project apache#15921 and apache#17270
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@mxnet-bot run ci [website, unix-gpu] |
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Jenkins CI successfully triggered : [website, unix-gpu] |
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Adding this to 1.7.0 roadmap #16864. |
pengzhao-intel
pushed a commit
that referenced
this pull request
Apr 16, 2020
…18069) * Dynamic subgraph compile support (#17623) This PR adds support for passing the NDArrays from the existing optimize_for API down to the reviewSubgraph function in an external library. It also adds a new API for HybridBlock called optimize_for that can partition the model without running a forward pass. Feature changes Adds new API to HybridBlock optimize_for that partitions the model but does not call the cachedOp Modifies the subgraph library example to optionally require args to be provided Adds annotation on subgraph inputs for the name of the original param so that inputs can be mapped and passes annotations to input nodes of subgraphs Adds support for tensors in MKLDNN format, calls Reorder2Default New tests Adds a new test to partition operators that directly consume params add a new model to test where ops to be partitioned have args/params Bug Fixes fixes bug in passing ids vector by value instead of by reference fixes bug in passing copies of attributes instead of by reference fixes bug where _cached_graph was not updated after partitioning fixes memory leak where user-specified attributes on subgraph ops were not freed if subgraph was rejected fixes problem incorrectly indexing into shape/dtype maps when annotating the graph Docs Updates the README doc with the latest changes described above * Adding sparse support to MXTensor for custom operators (#17569) * Added enum for sparse storage * Add structure for Dense and Sparse * redesign the data structure for MXSparse * pull out aux data from sparse NDArray * Added more sparse arguments to API interface * Passed sparse from c_api to lib_api.h and set in MXTensor * Fix indent * fix segfault * Fix NDArray to MXTensor errors * Add a sample of sparse(CSR) transpose * Make CSR transpose temporarily work by hardcoding * Fixed sparse output size(Refined) * Add tests for symbolic and stateful ops * Added a sample for row sparse transpose * Added real row sparse transpose * Fix output size issue by adding lambda for CheckAndAlloc() * Fix mixed storage formats error * Added infer storage type function * resolve comments * Set inferSType as optional function * Resolve comments * Add error messages * Resolve comments * verify transpose ops results * fix sanity check * update MX_LIBRARY_VERSION to 5 * Custom Operator Random Number Generator Support (#17762) Add random number generator support for custom operator libraries. Design: We pass from MXNet the initialized and seeded states, located on CPU and GPU, to custom library. So user could use those seeds to generate deterministic values from a given seed passed to MXNet. Basically this workflow: mx.random.seed(128) r1 = mx.nd.some_custom_random_op(data) mx.random.seed(128) r2 = mx.nd.some_custom_random_op(data) assert (r1 == r2) This PR does not let custom library generate exactly the same sequence of random numbers comparing to MXNet This is a continuation of the custom operator project #15921 and #17270 Co-authored-by: guanxinq <[email protected]> Co-authored-by: Ziyi Mu <[email protected]>
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@samskalicky I realize that you're committing the patch into v1.7.x instead of v1.x branch, are these patches already in v1.x branch? If not, please help to backport them to v1.x as well, thanks! |
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@samskalicky got it, that's fine, thanks for the update :) |
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Cherry pick MXNet Extension PRs into 1.7.x: