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"@zx-lhb \r\nIn order to expedite the trouble-shooting process, please provide a code snippet to reproduce the issue reported here. Thank you!",
"> @zx-lhb In order to expedite the trouble-shooting process, please provide a code snippet to reproduce the issue reported here. Thank you!\r\n\r\n# my dataset definiti... | 2024-05-11T09:45:14 | 2024-05-31T01:49:29 | 2024-05-31T01:49:23 | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
tf2.16
### Custom code
Yes
### OS platform and distribution
windows10
### Mobile device
_No response_
### Python version
3.12
### Bazel version
_No response_
### GCC/compiler version... | {
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"BTW please send XLA PRs via github.com/openxla/xla, it backs the same files, and soon will be the only way to submit such PRs.",
"> BTW please send XLA PRs via github.com/openxla/xla, it backs the same files, and soon will be the only way to submit such PRs.\r\n\r\nXLA PR here: https://github.com/openxla/xla/pul... | 2024-05-11T03:42:48 | 2024-05-28T06:25:02 | null | CONTRIBUTOR | null | false | {
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} | The original code uses the wrong parameter `i` for `cuDeviceCanAccessPeer()`, which can cause undefined behavior when `(*all_ids_)[i] != platform_device_id`, for example, virtual devices are used. Should use `(*all_ids_)[i].value()` to represent the previous pool id.
Also, add a judgment to skip the pool initializat... | {
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} | manual dims must be excluded when computing the new tile assignment, or
num_new_tiles will always be > NumTiles() + 1 and sharding propagation will
infinitely reassign the same partial manual shardings.
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FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12049 from dimvar:detect-nvidia-simulation 1a488e45b3a7d0f7729fde9c28915c40188d17b3
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"Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA).\n\nView this [failed invocation](https://github.com/tensorflow/tensorflow/pull/67370/checks?check_run_... | 2024-05-11T01:11:51 | 2024-06-05T08:11:25 | null | NONE | null | false | {
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} | From profiling slow load times of serialized GPUv2 delegate data, a lot of unnecessary time is spent re-allocating memory as part of the call to std::string::append. By pre-allocating the correct size, we save a lot of time.
This patch was developed in 2022 (pardon the slow turn-around) and I no longer have the exac... | {
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This hopefully should go away when XLA implements it's own memory space propagation pass or JAX adds memory_kind to the type system of jaxpr i.e. on avals.
It's required to treat the follo... | {
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Clients disconnect before the service shuts down. However, there is a short time window where the clients send out heartbeat RPCs right before shutting down, which might reach the server after it shuts down.
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for better generality and not owning the DeviceMgr since that
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Previously, the streamed tensor was being copied to host before the dynamic update slice that is supposed to handle the data transfer. This fixes that.
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FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12228 from trevor-m:tmorris-norm-init f53533087ba1ddcf65ad7cc6268ee89de4690d15
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Reverts 9760d8855f3270d5ff8a42293d26a04a56c42d88
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Reverts 9760d8855f3270d5ff8a42293d26a04a56c42d88
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Reverts 73a3f15becb844358808b7c6686b15fe5d0baecf
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I wanna confirm that the CI really doesn't pick it up.
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Internal tests are failing.
Reverts 73a3f15becb844358808b7c6686b15fe5d0baecf
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"Hi **@karelhorak-gen** ,\r\n- Sorry for the delay, I tried to run your code on colab using TF v2.15, 2.16.1, nightly and in 2.15 it is working fine, remaining versions getting the same issue. please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/63cf5b4bc484ac837ff24245b4c3356d/67334_2-15-2-16-1-... | 2024-05-10T11:59:39 | 2024-05-31T01:49:32 | 2024-05-31T01:49:25 | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
binary
### TensorFlow version
v2.16.1-0-g5bc9d26649c 2.16.1
### Custom code
No
### OS platform and distribution
MacOS 14.4.1 (Arm)
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
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"merged_at": "2024-05-... | Fix GEMM autotuner on Hopper
Triton only generates MMA v3 (sm90+) dots when ENABLE_MMA_V3 env is set, and this env.var is controlled by --xla_gpu_enable_triton_hopper flag in XLA.
The autotuner now correctly uses this flag.
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"@Yummyto,\r\nCould you please try to follow the below steps to resolve the issue. Also try to upgrade the protobuf package.\r\n\r\npip install --upgrade protobuf\r\n\r\n```python\r\n- Use protobuf version 3.19.4 for when using object detection\r\n- Download builder.py from [github repo](https://github.com/protocol... | 2024-05-10T11:04:11 | 2024-06-06T01:49:42 | 2024-06-06T01:49:39 | NONE | null | null | null | ### Issue type
Build/Install
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
2.10.1
### Custom code
Yes
### OS platform and distribution
Windows
### Mobile device
_No response_
### Python version
3.7.3
### Bazel version
_No response_
### GCC/compil... | {
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"Hi @huangrt01 ,\r\n\r\nI have tested the code with tf-nightly and found execution fails.Could you please check the [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/db40b44ba5857492008d9bcc7ab023d1/67330.ipynb) and confirm anything missing in submitted code?",
"> Hi @huangrt01 ,\r\n> \r\n> I have teste... | 2024-05-10T11:02:11 | 2024-05-15T16:51:35 | null | NONE | null | null | null | ### Issue type
Performance
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
2.4
### Custom code
Yes
### OS platform and distribution
_No response_
### Mobile device
_No response_
### Python version
_No response_
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When debugging compile time regressions, it can be helpful to use the flag
--xla_dump_module_metadata. This change adds a tool that can process such a
dump and print the individual pass timings in sorted order, so that it is
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"merged_at": "2024-05-... | PR #11912: [GPU] Support pointwise floor and ceil in GEMM fusions.
Imported from GitHub PR https://github.com/openxla/xla/pull/11912
For this to work with Triton openxla/triton will need to include https://github.com/openai/triton/commit/62706e8c518c8c56e56460a43732d8e375217860.
Copybara import of the project:
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"@Hell576 tf.data.Dataset.choose_from_datasets() isn't designed to merge datasets element-wise. It actually picks elements one at a time, deterministically choosing from the provided datasets based on a separate \"choice\" dataset.\r\nThank you!",
"This issue is stale because it has been open for 7 days with no a... | 2024-05-10T10:53:08 | 2024-06-10T12:52:21 | null | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
tf v2.16.0-rc0-18-g5bc9d26649c 2.16.1
### Custom code
Yes
### OS platform and distribution
Windows 10 Home
### Mobile device
_No response_
### Python version
3.11.8
### Bazel version
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} | Make the CI at least build unsupported GPU test targets
This should allow uncovering build failures for tests that require
hardware that is not available in a presubmit - like H100 GPUs
at the time of writing this.
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} | When using the Arm NN Tensorflow Delegate or Arm NN TfLite parser an abort is caused by the destruction of flatbuffers::ClassicLocale::~ClassicLocale() before the Arm NN ExecuteNetwork process exits.
Setting FLATBUFFERS_LOCALE_INDEPENDENT=0 allows ClassicLocale to be compiled out. however it requires CheckCXXSymbol... | {
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"Hi **@saturn-drm** ,\r\n- Sorry for the delay, I tried to run your code on colab using TF v2.9, 2.16.1 and i am not facing any issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/5a66577867096254c08ee9ab56831d9c/67323_2-9-2-16-1.ipynb) here for reference.\r\n- And it looks like you are u... | 2024-05-10T10:28:34 | 2024-05-16T02:53:42 | 2024-05-16T02:53:40 | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
tf 2.9
### Custom code
Yes
### OS platform and distribution
Linux Ubuntu 22.04
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
_No response_
### GC... | {
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This has to be reverted when/if ENABLE_MMA_V3 env is removed in Triton.
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I thought I could get away with not doing this, but I finally
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Imported from GitHub PR https://github.com/openxla/xla/pull/11762
With https://github.com/openxla/xla/pull/11761 NCCL comm split will be available for multiprocess applications. Using that change, I tested a variety of PAXML and T5X workloads. I found no crashes, han... | {
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>10x difference in performance when compiling tf.cumsum
For a tf.cumsum over 1e6 elements on A6000 GPU:
Without this patch: ~466ms
With the patch: 40us
This is faster than TF native implementation.
The value of splitting is chosen heuris... | {
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Copybara import of the project:
--
0edeabdf23fb01e21c5984b4a8f902a720b5820e by Eugene Kuznetsov <eugene.kuznetsov@amd.com>:
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"@mohammad0081,\r\nCould you please, share colab link or simple standalone code with supporting files to reproduce the issue in our environment. It helps us in localizing the issue faster. Thank you!",
"This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activ... | 2024-05-10T06:46:26 | 2024-05-27T15:23:50 | 2024-05-27T14:54:32 | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
2.16.1
### Custom code
Yes
### OS platform and distribution
colab os platform
### Mobile device
_No response_
### Python version
_No response_
### Bazel... | {
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This op is the IFRT IR equivalent of `xla::ifrt::Client::RemapArrays`.
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