* [Relay][Frontend][Keras] Fix ReLU in Keras Converter missed the case
* [Relay][Frontend][Keras] Add test case for ReLU in Keras Converter missed the case
* [Relay][Frontend][Keras] Add test case for ReLU in Keras Converter missed the case
* [VTA] Support TLPP in function simulator.
Issue:
currently vta function simulator just doing serialized instruction
execution, the dependency logic of runtime ISA which use for task
level pipe line parallelism can not get verified by function simulator.
Solution:
make the simulator driver to be multiple thread and support TLPP.
Benefit:
TLPP support VTA function simulator would make VTA logic testing/debug
/change more easy.
replace boost lockfree queue
add configure control for simulator tlpp enable or disable.
change code tyle into google style.
Wrap queue read/write and sync logic to make function call more simple.
Add some comments.
Remove MT logic, change into Single thread mode.
address review comments.
code style change to match google code style and add comments.
add cmake macro to enable/disable simulator tlpp logic.
submodule update.
correct file name mentioned in comments.
* remove USE_VTA_FSIM_TLPP.
* Getting closer to having ADT defs
* ADT defs working probly
* Match parsing basipally done
* came to earth in a silver chrome UFO
* match finished?
* All tests but newest are passing
* ADT constructors work
now cleanup?
* Cleanup round 1
* Cleanup round 2
* Cleanup round 3
* Cleanup round 4
* Cleanup round 6
* Cleanup round 7
* Lil grammar fix
* Remove ANTLR Java files
* Lint roller
* Lint roller
* Address feedback
* Test completeness in match test
* Remove unused imports
* Lint roller
* Switch to Rust-style ADT syntax
* Lil fix
* Add dummy `extern type` handler
* Add type arg to test
* Update prelude semantic version
* Repair test
* Fix graph var handling in match
* Revert 's/graph_equal/is_unifiable' change
* [Relay] enable NHWC of `relay.testing.mobilenet`
In this way, we can play around NHWC inside TVM regardless of
the frontends.
* [Test] test for NHWC of relay.testing.mobilenet
* adding support for graphpack over multiply op
* increasing resnet model coverage
* fix indentation
* lint
* moving recursion limit fix into graphpack pass
* moving recursionlimit to relay init
* pooling on NCHWnc format
* adding more models
* deploy_resnet_on_vta.py
* trailing line
* generalizing to vision models
* merge conflicts
* fix, apply quantization to VTA only
* improving comments
* trimming models that have runtime issues for the moment
* lint
* lint
* lint
* [VTA][Chisel] add scalafmt and format existing scala codebase
* change column width to 100
* add scalafmt conf file as a valid file type
* add asf header to scalafmt conf file and rerun formatter
As GraphRuntime does not provide control-flow logics, we have to split
our model to two parts. While we need to share parameters between them
to save memory usage.
Solution:
1) add "lazy_init_input" in graph's attributes
"attrs": {
... ...
"lazy_init_input": [
"list_str",
[
"p0"
]
]
}
2) allow un-allocated NDArray entry in SetupStorage
3) utilize "set_input_zero_copy" function to set parameters
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