lhutton1 merged PR #15866:
URL: https://github.com/apache/tvm/pull/15866
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lukhut pushed a change to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
from e89b39e55b Bump pillow from 9.2.0 to 10.0.1 in /apps/microtvm (#15865)
add 6f04fdab5a Bump pillow from 9.3.0 to 10.0.1
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lukhut pushed a change to branch
dependabot/pip/apps/microtvm/cmsisnn/pillow-10.0.1
in repository https://gitbox.apache.org/repos/asf/tvm.git
was 62a873f876 Bump pillow from 9.3.0 to 10.0.1 in /apps/microtvm/cmsisnn
The r
lhutton1 merged PR #15867:
URL: https://github.com/apache/tvm/pull/15867
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lukhut pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
The following commit(s) were added to refs/heads/main by this push:
new ec92ea960d Bump pillow from 9.3.0 to 10.0.1 in /apps/mi
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lukhut pushed a change to branch
dependabot/pip/apps/microtvm/ethosu/pillow-10.0.1
in repository https://gitbox.apache.org/repos/asf/tvm.git
was e623ba5adf Bump pillow from 9.3.0 to 10.0.1 in /apps/microtvm/ethosu
The rev
lhutton1 commented on PR #15836:
URL: https://github.com/apache/tvm/pull/15836#issuecomment-1750182870
closes: #15754
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ashutosh-arm merged PR #15836:
URL: https://github.com/apache/tvm/pull/15836
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ashutoshp pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
The following commit(s) were added to refs/heads/main by this push:
new fa4aeee64e [CI] Update ci-gpu image (#15836)
fa4aeee
lhutton1 commented on issue #15754:
URL: https://github.com/apache/tvm/issues/15754#issuecomment-1750210468
fixed by https://github.com/apache/tvm/pull/15836
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lhutton1 closed issue #15754: [CI Problem] ci_gpu fails to build due to missing
oneflow version
URL: https://github.com/apache/tvm/issues/15754
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lhutton1 commented on PR #15799:
URL: https://github.com/apache/tvm/pull/15799#issuecomment-1750553096
@tvm-bot rerun
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ashutosh-arm commented on PR #15747:
URL: https://github.com/apache/tvm/pull/15747#issuecomment-1750680629
This was dependent on https://github.com/apache/tvm/pull/15836, so re-trying
now to see if CI works this time.
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ekalda commented on PR #104:
URL: https://github.com/apache/tvm-rfcs/pull/104#issuecomment-1750730364
I'm back from holiday and want to get this RFC moving again! Thanks for all
the good discussion so far, I've made some changes to the RFC:
* Use `vscale` directly instead of `vfactor` and
Lunderberg commented on code in PR #15699:
URL: https://github.com/apache/tvm/pull/15699#discussion_r1348897916
##
src/relax/transform/lift_transform_params.cc:
##
@@ -43,26 +43,92 @@ struct LiftTransformParamsInfoPlan {
lifted_bindings; // the bindings of the original f
kparzysz-quic commented on PR #104:
URL: https://github.com/apache/tvm-rfcs/pull/104#issuecomment-1751038124
Sorry for the delay... What I'm aiming at is to be able to lower the TIR to
a generic CPU, that is to an architecture that does not support SVE. The TIR
will need to have some defa
Lunderberg commented on PR #104:
URL: https://github.com/apache/tvm-rfcs/pull/104#issuecomment-1751100613
> What I'm aiming at is to be able to lower the TIR to a generic CPU, that
is to an architecture that does not support SVE. The TIR will need to have some
default lowering in CodeGenLLV
kparzysz-quic commented on PR #104:
URL: https://github.com/apache/tvm-rfcs/pull/104#issuecomment-1751113275
> Could it instead be in a target-dependent lowering pass?
Sure. My idea is to have a single SVE-aware vectorization pass in TVM, and
then be able to utilize it for all target
cyx-6 commented on issue #15805:
URL: https://github.com/apache/tvm/issues/15805#issuecomment-1751243263
I see. Actually, we cannot apply `ExternModule` onto the original model.
`ExternModule` is the new `nn.Module` interface, from `tvm.relax.frontend.nn`.
But original llama model is from `
vinx13 opened a new pull request, #15881:
URL: https://github.com/apache/tvm/pull/15881
This is a follow-up of https://github.com/apache/tvm/pull/15665. It
simplified the special case when `floormod(floordiv(x, lower_factor), ext) ==
x`. This prevent nested `IterMark` being created.
yongwww opened a new pull request, #15882:
URL: https://github.com/apache/tvm/pull/15882
We can unify the `runtime/relax_vm/memory_manager` and
`runtime/memory/memory_manager` by replacing the former with the latter.
DO NOT merge it, this PR should not be merged until PR #15833 is me
Lunderberg opened a new pull request, #15883:
URL: https://github.com/apache/tvm/pull/15883
Prior to this commit, the `relax.transform.FuseTIR` transform required that
the shapes arguments passed into a `PrimFunc` be structurally equivalent to the
shapes of the parameters, and that any repl
masahi commented on PR #15883:
URL: https://github.com/apache/tvm/pull/15883#issuecomment-1751490974
cc @Hzfengsy
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guoyaol opened a new pull request, #15884:
URL: https://github.com/apache/tvm/pull/15884
Add support: allow one dynamic tensor as torch.tensor's index
In Stable Diffusion XL:
e.g. `output = input1 [input2.argmax(dim = -1), ]`
**Before:** we can only support int, slice, elips
Cydia2018 closed issue #15805: [Bug][Unity] nn.Module external modules usage
URL: https://github.com/apache/tvm/issues/15805
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Cydia2018 commented on issue #15805:
URL: https://github.com/apache/tvm/issues/15805#issuecomment-1751565834
@cyx-6 I get it, really thanks.
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Hzfengsy commented on PR #15884:
URL: https://github.com/apache/tvm/pull/15884#issuecomment-1751601521
Thanks for the fix!
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github-bot pushed a change to branch nightly
in repository https://gitbox.apache.org/repos/asf/tvm.git
from e89b39e55b Bump pillow from 9.2.0 to 10.0.1 in /apps/microtvm (#15865)
add 6f04fdab5a Bump pillow from 9.3.0 to
Hzfengsy commented on code in PR #15883:
URL: https://github.com/apache/tvm/pull/15883#discussion_r1349462821
##
src/relax/transform/fuse_tir.cc:
##
@@ -39,31 +39,41 @@ namespace tir {
*/
class SymbolicMatcher : ExprFunctor {
public:
- explicit SymbolicMatcher(Map* var_rem
Hzfengsy merged PR #15813:
URL: https://github.com/apache/tvm/pull/15813
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Hzfengsy opened a new pull request, #15885:
URL: https://github.com/apache/tvm/pull/15885
This PR adds support for ReLU in NN module and op, also adds support for
GELU in the NN modules.
cc @jwfromm @junrushao
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