This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 6.8k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Browse files
Browse the repository at this point in the history
* 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 <58794120+guanxinq@users.noreply.github.com> Co-authored-by: Ziyi Mu <ziyi.mu@columbia.edu>
- Loading branch information
3 people
committed
Apr 16, 2020
1 parent
13f5ad9
commit bf99f27
Showing
26 changed files
with
1,779 additions
and
220 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,78 @@ | ||
| #!/usr/bin/env python3 | ||
|
|
||
| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
|
|
||
| # coding: utf-8 | ||
| # pylint: disable=arguments-differ | ||
|
|
||
| # This test checks dynamic loading of custom library into MXNet | ||
| # and checks end to end compute of a simple 2D gemm custom op | ||
|
|
||
| import mxnet as mx | ||
| import os | ||
|
|
||
| #load library | ||
| if (os.name=='posix'): | ||
| path = os.path.abspath('libtransposecsr_lib.so') | ||
| mx.library.load(path) | ||
| elif (os.name=='nt'): | ||
| path = os.path.abspath('libtransposecsr_lib.dll') | ||
| mx.library.load(path) | ||
|
|
||
| a = mx.nd.array([[1,3,0,2,1],[0,1,0,0,0],[0,2,4,5,3]]) | ||
| a = a.tostype('csr') | ||
| print("--------Input CSR Array---------") | ||
| print("data:", a.data.asnumpy()) | ||
| print("indices:", a.indices.asnumpy()) | ||
| print("indptr:", a.indptr.asnumpy()) | ||
|
|
||
| print("--------Start NDArray Compute---------") | ||
| b = mx.nd.my_transposecsr(a) | ||
| print("Compute Results:") | ||
| print("data:", b.data.asnumpy()) | ||
| print("indices:", b.indices.asnumpy()) | ||
| print("indptr:", b.indptr.asnumpy()) | ||
|
|
||
| print("Stateful Compute Result:") | ||
| c = mx.nd.my_state_transposecsr(a, test_kw=100) | ||
| print("data:", c.data.asnumpy()) | ||
| print("indices:", c.indices.asnumpy()) | ||
| print("indptr:", c.indptr.asnumpy()) | ||
|
|
||
| print("--------start symbolic compute--------") | ||
| d = mx.sym.Variable('d') | ||
| e = mx.sym.my_transposecsr(d) | ||
| f = mx.sym.my_state_transposecsr(d, test_kw=200) | ||
|
|
||
| exe = e.bind(ctx=mx.cpu(),args={'d':a}) | ||
| exe2 = f.bind(ctx=mx.cpu(),args={'d':a}) | ||
| out = exe.forward() | ||
| print("Compute Results:") | ||
| print("data:", out[0].data.asnumpy()) | ||
| print("indices:", out[0].indices.asnumpy()) | ||
| print("indptr:", out[0].indptr.asnumpy()) | ||
|
|
||
| out2 = exe2.forward() | ||
| out2 = exe2.forward() | ||
| print("Stateful Compute Result:") | ||
| print("data:", out2[0].data.asnumpy()) | ||
| print("indices:", out2[0].indices.asnumpy()) | ||
| print("indptr:", out2[0].indptr.asnumpy()) | ||
|
|
||
| print("--------Baseline(dense)--------") | ||
| print(mx.nd.transpose(a.tostype('default'))) |
Oops, something went wrong.