allow pytorch stream model loading #729
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frankfliu
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Mar 5, 2021
onnxruntime/onnxruntime-engine/src/test/java/ai/djl/onnxruntime/engine/OrtTest.java
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goswamig
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Mar 5, 2021
onnxruntime/onnxruntime-engine/src/test/java/ai/djl/onnxruntime/engine/OrtTest.java
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Codecov Report
@@ Coverage Diff @@
## master #729 +/- ##
============================================
+ Coverage 69.15% 69.18% +0.02%
- Complexity 3991 3998 +7
============================================
Files 462 462
Lines 18640 18654 +14
Branches 1999 2004 +5
============================================
+ Hits 12891 12906 +15
+ Misses 4728 4725 -3
- Partials 1021 1023 +2
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stu1130
reviewed
Mar 8, 2021
| @@ -73,6 +73,7 @@ public void testOrt() throws TranslateException, ModelException, IOException { | |||
| public void testStringTensor() | |||
| throws MalformedModelException, ModelNotFoundException, IOException, | |||
| TranslateException { | |||
| System.setProperty("ai.djl.onnx.disable_alternative", "true"); | |||
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How about putting this functionality into Criteria?
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We cannot simply added to criteria, it is usually scoped into a series of operations
frankfliu
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Mar 8, 2021
added 2 commits
March 8, 2021 16:38
frankfliu
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Mar 9, 2021
stu1130
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Mar 9, 2021
zachgk
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Mar 11, 2021
* This creates the component which will populate the Download Tab with Download Buttons. * Making a place for the download buttons. * Adding the Model Download Handler allowing the backend to feed the links into the Model View and making slight changes for readablity. * Getting rid of some of the test code. * Improve Block usability (#712) * Use builder pattern for Parameter (#661) * Make XavierInitializer default value & Improve setInitializer (#664) * Refactor initialize (#675) * Remove NDManager on getOutputShapes (#710) * Removing unnecessary logging messages. * block factory init commit (#697) * [DOCS] Fixing TrainingListener documentation (#718) * Fixing TrainingListener documentation * Fixing PR reviews * Fix DJL serving flaky test for mac (#721) Change-Id: I9eccc84b0c34652e50c5fe5a4fe42f2b82d65a3d * Fixing all of the nits. * Getting rid of unnecessary methods. * update onnxruntime along with String tensor (#724) * Add profiler doc (#722) * Resolving some comments. * Using a better criteria incase multiple models have the same name. * Fixing the java doc. * Configure verbose of mxnet extra libraries (#728) Change-Id: I66d54aa496cccbb9e8c0a89eeaa458605958d9c6 * Added a TODO for using the artifact repo to get the base uri. * paddlepaddle CN notebook (#730) * paddlepaddle CN notebook * install font Change-Id: I2d749e617b0bf78ecbcd168b82c53a1fab49a2c0 * refactor on name Change-Id: I9e379eee51ceae16391850b3ba9782acb04c4021 * Refine the text Co-authored-by: gstu1130 <[email protected]> * add EI documentation (#733) * add EI documentation * fix pmd rules Change-Id: Ieee5577c26f6df2843781f8f9180de35069a5de3 * allow pytorch stream model loading (#729) * allow pytorch stream model loading * updates Change-Id: Ibc26261b90de673712e90de0d640a8f32f23763e * add NDList decode from inputStream (#734) Change-Id: I6a31d8b0b955f2dbb762220b101e3928a34699c1 * Remove memory scope and improve memory management (#695) The MemoryScope reveals a number of shortcomings within the DJL memory management. While the MemoryScope is deleted, many of them are fixed as part of this PR. First, the NDManager.{attach, detach} were renamed to xxxInternal. This is to differentiate them from the attach and detach methods that are intended to be used. There are two new concepts in memory management. An NDResource interface was created to combine the concepts of managed memory that was used in NDArray and NDList. It could also be used in more classes in the future. This includes the getManager, attach, and detach. Within the NDManager, it gains a second "management convention". The first convention of normal resources are added to the manager and then closed when the manager closes. This works for small numbers of things on the NDArray, but not when operations transitively create. So, the second convention is a tempResource. Instead of freeing them when the manager is closed, they are returned to their original manager. This is used to create a temporary scope, do operations within it, and then the inputs and return value are returned to the parent while the intermediate work is cleaned. This also matches the concepts of ownership/borrowing as well. Using these, a few additional helper methods were created. There is `NDManager.from(resource)` to ease creation of managers based on a resource. There is also `scopeManager.ret(returnValue)` to help with returning values outside of the scopeManager. Lastly, there is a `scopeManager.{temp,}AttachAll` to attach a number of resources to a manager within a single call. Using these improvements, the new method were applied to the old locations where MemoryScope was used as well as an additional case in NDManagerEx. Also, the old attach methods were altered to be `void`. Because the return values are no longer used anywhere and are not as necessary in the current scheme, I figured it would simplify things. It also helps for things like `NDList.attach` which does not have a single original NDManager when attaching. Change-Id: I91d109cd14d70fa64fd8fffa0b50d88ab053013e * Remove erroneous random forest application (#726) The application was changed to the more accurate softmax_regression (matching the terminology from the D2L book). Change-Id: I1f69f005bbe38b125f2709c2988d06c14eebb765 * Minor fixes on duplicated code (#736) * remove methods that already defined in the NDArrayAdapter Change-Id: I01cc03a7f5b427bf31c6b3fd8d2136f2a27fe93b * refactor toString Change-Id: Iea22b16e1daa9f759b55c1a8b8b85536482e551a * remove sparse NDArray Change-Id: Icb44096519775f54cb32cc768c14f49e33dc7ea5 * fix test Change-Id: Icef580ed77e7bba22864ce44577de3cba51e3e41 Co-authored-by: Jake Lee <[email protected]> Co-authored-by: Lanking <[email protected]> Co-authored-by: aksrajvanshi <[email protected]> Co-authored-by: Frank Liu <[email protected]> Co-authored-by: Zach Kimberg <[email protected]>
Lokiiiiii
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Oct 10, 2023
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Description
Add a Stream model loading option specifically for PyTorch