Merge from upstream #53
Merged
Conversation
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
* [relay][vm] Separate VM runtime with executable * Address comments * move ctx back to vm * make only vm related fields and methods protected * integrate seriliaztion/deserialization to executable * create stream
* [Relay][Frontend][TF] Add tensor array ops * rename * delete test * Move utility function * Refactor * fix tensor array ops * fix test * fix rebase * Fix serializer bug * Improve tf convert name lookup to use prelude api * Fix lint * Fix test
* Add LiftIfThenElse pass * Add more comments * Rename and refactor * Add description for internal data structure * Rename a test * Minor change * Address comments * Improve update_for
We think it will reduce the confusion with the meaning. https://discuss.tvm.ai/t/discuss-consider-rename-vm-datatype/4339
…he#4161) * [REFACTOR][NODE][RUNTIME] Move Node to the new Object protocol. This PR removes the original node system, and make node as a subclass of Object. This is a major refactor towards a better unified runtime object system. List of changes in the refactor: - We now hide data_ field, use Downcast explicitly to get a sub-class object. - Removed the node system FFI in python. - Removed the node C API, instead use PackedFunc for list and get attrs. - Change relay::Op::set_attr_type_key(attr_key_name) to relay::Op::set_attr_type<AttrType>(). - This change was necessary because of the new Object registration mechanism. - Subsequent changes to the op registrations - The change revealed a few previous problems that is now fixed. - Patched up a few missing node type registration. - Now we will raise an error if we register object that is not registered. - The original node.h and container.h are kept in the same location. - Calling convention: kObjectHandle now equals the old kNodeHandle, kNodeHandle is removed. - IRFunctor now dispatches on ObjectRef. - Update to the new type checking API: is_type, derived_from are replaced by IsInstance. - Removed .hash member function, instead use C++ convention hasher functors. * Address review comments
This patch adds multiply operator for quantized tensors. The details of the quantized multiplication are outlined in the code. This builds on pull request 3927 and includes the changes Animesh mentions in the comments on that request. Change-Id: I555715b53d0266a91d5c03dc3dfe8fc31e7ce4e1
FIX "After connecting he usb" with "After connecting the usb"
* count MAC for BatchMatMul * update doc
* [bugfix][codegen] fix casting bug in llvm codegen * update example * retrigger ci * check llvm version
* [Relay][Frontend][TF] Fix Size operator * Uncomment tests
* [rpc] use callback func to do send & recv. don't get fd from sock as it is deprecated in java * fix java build * fix min/max macro define in windows * keep the old rpc setup for py * add doc for CallbackChannel
* Start to update TF frontend docs * Add rst * Remove markdown * Update wording * Resolve comments
This reverts commit 6f9d028.
* Support setting path to ANTLR jar * Update comment
apache#4195) * Fix example code in comment of tvm.build_module.build() * Update build_module.py
* add tensor core support * avoid memory bank conflict * fix thread sync & better performance * better performance * add schedule test for conv2d * extend into BatchMatMul * support config fragment shape and layout using intrinsic * add TensorCore tutorial * add int support and fix lint * address comment * add 32*16*8 TensorCore test * fix wmma include logic
* [NODE][REFACTOR] Refactor reflection system in node.
- Removed the old Node, Node is now just an alias of runtime::Object
- Introduce ReflectionVTable, a new columnar dispatcher to support reflection
- This allows us to remove vtable from most node objects
- The VisitAttrs are registered via TVM_RESGITER_NODE_TYPE,
they are no longer virtual.
- Consolidated serialization and reflection features into node.
* Explicit type qualification when calling destructor.
* Fix SPIRV, more comments
…optimization (apache#4146) * add checkpoint annotation for checkpointing memory optimization * add alpha-equivalence checkpoint test and fix gradient type issue * fix build issues * ignore checkpoint annotation when checking missing gradients * refactor, fix checkpoint compute for tuple and add tests
…ndividual functions. (apache#4194) * Add support for attaching params * Fix types * Fix test
* Add support for op Where * Update impl version
* app init push * fix on readme * change name, add bit serial explanantion * rm serialLoadMM, change doc * syntax change for readme * add parallel test functionality * fix readme * add python doc * syntax * init commit * fix empty line * fix typo
…#4206) * :add scale2 for upsample * update unit test for upsampling * support latest upsample op for multiple frontend * fix lint * fix lint * fix lint * fix lint * update scale description and rebase
* Optimize task extraction speed * correct pylint errors * Delete unused function * remove unnecessary argument * resolve code review comments * corrent cpp lint errors * remove one more graph_json return value * fix test bugs
* Add Python type functor and tests * Lint roller
* [QNN] Improving Dense lowering. * - Moving get_shape method to util - Finalizing the test cases and the code structure for optimized dense computation. * - Fixing cpplint. * - Addressing review comments. * - Renaming the variables correctly. * - Renaming the variables correctly.
…che#4197) * Added slice v10 * Added constantofshape operation and small refactor. * Finished one_hot implementation. * Reshape working across all bert layers. * Fixed constantofshape and removed code duplication. * onnx model fully ingested. * Working on improving onnx tests. * Changed onnx testing to use onnxruntime instead of caffe2, also formatted. * Add arbitrary output nodes to onnx frontend. * Added v6 tiling for bert squad 8 support. * Small syntax fixes * Reduced code duplication in split opset versions. * Added batch matmul test * Added unstack split testing. * Adde onehot test, needs a little cleanup probably. * Replaced deprecated constant fill with constantofshape and updated tests accordingly. * Added tests for new opset version of slice and tile. * lint clean up * Lint fixes * Changed onnx dependency * Went back to caffe2 runtime for CI integration. * Rebase and small typo/syntax changes. * Added hard casting of onehot attributes to int.
…4205) * Add support for Any op * Support ONNX frontend * Add doc * Add to relay docs * Dummy change to retrigger CI
yongwww
approved these changes
Oct 31, 2019
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Merge from upstream