merrymercy opened a new pull request #6683:
URL: https://github.com/apache/incubator-tvm/pull/6683
Fix for this bug
https://discuss.tvm.apache.org/t/auto-scheduling-for-lstm-operator/8158
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merrymercy commented on pull request #6683:
URL: https://github.com/apache/incubator-tvm/pull/6683#issuecomment-708220388
cc @jcf94 @comaniac
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merrymercy merged pull request #6683:
URL: https://github.com/apache/incubator-tvm/pull/6683
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lmzheng pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/main by this push:
new 78bba3c [AutoScheduler] Fix a bug in thread
tqchen merged pull request #6667:
URL: https://github.com/apache/incubator-tvm/pull/6667
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tqchen commented on pull request #6682:
URL: https://github.com/apache/incubator-tvm/pull/6682#issuecomment-708370603
We already have vulkan build as part of the CI process.
However, vulkan running itself is not enabled because my previous tests of
nvidia docker does not seems to suppor
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tqchen pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/main by this push:
new 60ed926 [ARITH] Introduce iterator (quasi)af
tqchen opened a new pull request #6684:
URL: https://github.com/apache/incubator-tvm/pull/6684
https://discuss.tvm.apache.org/t/naming-consistency-util-vs-utils/6434
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ANSHUMAN87 opened a new pull request #6685:
URL: https://github.com/apache/incubator-tvm/pull/6685
SparseTensorDenseMatMul support added for Tensorflow frontend.
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ANSHUMAN87 commented on pull request #6685:
URL: https://github.com/apache/incubator-tvm/pull/6685#issuecomment-708582002
@FrozenGene , @siju-samuel , @kevinthesun : please help review. Thanks!
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jroesch pushed a change to branch ci-docker-staging
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git.
discard 074dbef Bump Jenkinsfile
discard 0704756 Setup Rust path
discard 7858503 Add deps needed for
areusch commented on a change in pull request #6603:
URL: https://github.com/apache/incubator-tvm/pull/6603#discussion_r504941656
##
File path: src/runtime/crt/utvm_rpc_server/rpc_server.cc
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@@ -126,25 +125,33 @@ class MicroRPCServer {
/*! \brief Process one message from
areusch commented on a change in pull request #6603:
URL: https://github.com/apache/incubator-tvm/pull/6603#discussion_r504941832
##
File path: tests/micro/qemu/zephyr-runtime/crt/crt_config.h
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@@ -0,0 +1,62 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under on
areusch commented on pull request #6603:
URL: https://github.com/apache/incubator-tvm/pull/6603#issuecomment-708632486
thanks @liangfu, please take another look when you have a minute
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jroesch pushed a commit to branch ci-docker-staging
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/ci-docker-staging by this push:
new ecf8b65 Format
ec
tkonolige commented on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708649133
The problem with using fork is that it is unsafe on macOS or when using the
CUDA api. The pytorch developers recommend not using fork with CUDA:
https://pytorch.org/docs
comaniac opened a new pull request #6686:
URL: https://github.com/apache/incubator-tvm/pull/6686
This PR improves the cache read sketch generation rule in auto-scheduler to
support multiple cache reads. Previously, cache read sketch generation rule
will simply give up if a tensor has multi
mbrookhart opened a new pull request #6687:
URL: https://github.com/apache/incubator-tvm/pull/6687
We found some quantized models that were performing Int32 average pooling
with input tensors that had Int64 shapes. This cause an error in te where the
resulting computations were implicitly
mbrookhart commented on a change in pull request #6681:
URL: https://github.com/apache/incubator-tvm/pull/6681#discussion_r505024398
##
File path: python/tvm/relay/frontend/onnx.py
##
@@ -532,10 +534,18 @@ def flatten_to_3d(x, x_shape):
b = _op.transpose(b, [0, 2,
jwfromm commented on a change in pull request #6681:
URL: https://github.com/apache/incubator-tvm/pull/6681#discussion_r505043967
##
File path: python/tvm/relay/frontend/onnx.py
##
@@ -532,10 +534,18 @@ def flatten_to_3d(x, x_shape):
b = _op.transpose(b, [0, 2, 1])
tqchen merged pull request #6684:
URL: https://github.com/apache/incubator-tvm/pull/6684
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tqchen pushed a change to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git.
from 60ed926 [ARITH] Introduce iterator (quasi)affine map detection.
(#6667)
add 8439f3e [REFACTOR] util => u
mbrookhart commented on a change in pull request #6681:
URL: https://github.com/apache/incubator-tvm/pull/6681#discussion_r505048637
##
File path: python/tvm/relay/frontend/onnx.py
##
@@ -532,10 +534,18 @@ def flatten_to_3d(x, x_shape):
b = _op.transpose(b, [0, 2,
merrymercy commented on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it needs to
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
merrymercy edited a comment on pull request #6671:
URL: https://github.com/apache/incubator-tvm/pull/6671#issuecomment-708845921
Autotvm uses a lot of python multiprocessing and I expect it will be much
slower when using spawn. AutoTVM uses multiprocessing for feature extraction.
So it ne
masahi commented on pull request #6681:
URL: https://github.com/apache/incubator-tvm/pull/6681#issuecomment-708878955
Thanks @jwfromm @mbrookhart
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masahi merged pull request #6681:
URL: https://github.com/apache/incubator-tvm/pull/6681
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masahi pushed a change to branch main
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git.
from 8439f3e [REFACTOR] util => utils for consistency in the project.
(#6684)
add 9564925 [Relay][Frontend][O
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jroesch pushed a commit to branch ci-docker-staging
in repository https://gitbox.apache.org/repos/asf/incubator-tvm.git
The following commit(s) were added to refs/heads/ci-docker-staging by this push:
new d4e3f4d Disable R
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