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PjRt GPU and CPU has recently gotten memory space support with just one memory space per device, so enabling relevant JAX memory tests. Most tests cannot be enabled yet because they rely on `unpinned_host`, so only enabling `ShardingMemoriesTest` for now.
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Registering user-defined types with FFI and passing user data to FFI handlers via execute context coming in followup PRs.
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FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12633 from openxla:fix_multihost_runner_flag_parsing 71083c7d6dfdcaec1a5458b3f1cd04b11e13f8bd
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"Hi @zepouet, can you try with `Clang from xcode 13.6`: https://www.tensorflow.org/install/source#macos ensure your versions are aligned with the compatibility matrix. Thanks.",
"Hello @pkgoogle, can you give me the compatibily matrix please ? Thanks. \r\nI fear to downgrade CLang and have side effect elsewhere.\... | 2024-05-13T19:05:28 | 2024-06-12T01:50:58 | null | 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
No
### OS platform and distribution
Mac Sonoma 14.4.1
### Mobile device
_No response_
### Python version
3.10
### Bazel version
... | {
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Fixes #65865
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"@swoiow,\r\nAfter version 2.10, we will only be providing pip packages for Linux x86_64 and Intel-based Macs. For other systems like Windows, Aarch64, and Apple Macs, TensorFlow relies on [build collaborators](https://blog.tensorflow.org/2022/09/announcing-tensorflow-official-build-collaborators.html), and so we w... | 2024-05-13T18:17:00 | 2024-06-03T21:20:17 | 2024-06-03T21:20:14 | NONE | null | null | null | ### Issue type
Build/Install
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
2.16
### Custom code
No
### OS platform and distribution
windows
### Mobile device
_No response_
### Python version
_No response_
### Bazel v... | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/12049
This helps when testing the compiler on new hardware platforms. The simulator may have nonsensical values for a few fields in the... | {
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Metadata loader was using incorrect warp assignment, which resulted in incorrect addresses with num_warps>4. This was previously missed, as the autotuner rarely selected such configs.
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- Extend PjRt ExecuteContext base class to always include XLA FFI execution context so that end-users can pass data to FFI handlers.
- Add an end-to-end test to SE GPU PjrtClient.
PJRT C API changes will be in the followup PRs.
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Imported from GitHub PR https://github.com/openxla/xla/pull/10803
[CompiledMemoryStats](https://github.com/openxla/xla/blob/01073cf10b57c64615483545bfb34fb9ae0d3c06/xla/pjrt/pjrt_executable.h#L269-L269) is supposed to summarize the amount of memory required to run ... | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/12228
The first time that a NormThunk is executed, it will build a cudnn execution plan. This build step can hang if a NCCL collective is running at the same time. To fix t... | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/12255
Applies the same fix as in https://github.com/openxla/xla/pull/12228 to FMHA.
Copybara import of the project:
--
70a42828f86711a0e83a2eb37ee52833e1768187 by Ilia Sergachev ... | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/10803
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} | [XLA:GPU] Pass the CUDA / ROCm toolkit version explicitly for autotuning and GEMM rewriting.
This allows to remove more `#if GOOGLE_CUDA` preprocessor directives from HLO passes.
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If a pass emits a warning, then the status will be set to `UnknownError` causing pipelines to fail. But we shouldn't if a pass/pattern just emits a warning.
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} | PR #11563: [NVIDIA GPU] Improve GPU collective matmul to support all-gather having multiple users
Imported from GitHub PR https://github.com/openxla/xla/pull/11563
We have identified another optimization opportunity for gpt-3 using collective matmul, in the backward pass, the all-gather has multiple dot users but cur... | {
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} | Integrate LLVM at llvm/llvm-project@331f22af4b4c
Updates LLVM usage to match
[331f22af4b4c](https://github.com/llvm/llvm-project/commit/331f22af4b4c)
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The LLVM lowering doesn't support arbitrary shapes.
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"Hi @wzzll123 ,\r\n\r\nI have tested the code with tf-nightly and replicated the precisional differences wrt `float32` and `bfloat16`. Attached [gist](https://colab.sandbox.google.com/gist/SuryanarayanaY/65f24bed8192f64bdcf76bc81c923a93/67440.ipynb#scrollTo=KZg13iGhYGPP) for reference. There seems to be an issue.",... | 2024-05-13T12:05:08 | 2024-05-14T06:16:30 | null | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
binary
### TensorFlow version
tf 2.16.1
### Custom code
Yes
### OS platform and distribution
_No response_
### Mobile device
_No response_
### Python version
3.10.9
### Bazel version
_No response_
### GCC/compil... | {
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Use `--xla_allow_excess_precision` instead.
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We have logic to estimate the impact of certain ops on IR size. This problem is
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The interpreter is very slow for some of these (up to ~45 seconds
in unoptimized builds). With this change, runtime goes down to at
most ~1 second per test case. At this point, sharding is no longer
helpful (since the fixed setup cost dominates), so we can disable
it.
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Before the fix, `tt.splat` was lowered to e.g.
```
%14 = "llvm.mlir.constant"() <{value = 0.000000e+00 : f8E4M3FNUZ}> : () -> f8E4M3FNUZ
```
which LLVM rejected.
Translating the result type through typeConverter is what is done in other similar places. It results in
```
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After this, all legacy fusions are supported by MLIR emitters. Currently, there
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Do not attempt to wrap/rewrap Status, as that loses the attached stack trace, and causes further errors.
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Imported from GitHub PR https://github.com/openxla/xla/pull/12253
Without this change then when `--xla_dump_hlo_as_proto=true --xla_dump_to=/some/real/path` is set, the autotuner dumps PTX to stdout.
Copybara import of the project:
--
91... | {
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index_switch will be used in the reduction group lowering.
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"@Sgzeus23 Could you please provide more context to this issue?\r\nThank you!",
"This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.",
"This issue was closed because it has been inactive for 7 days since being marked as stale. Ple... | 2024-05-13T02:55:53 | 2024-05-29T01:50:48 | 2024-05-29T01:50:45 | NONE | null | null | null | **System information**
- Android Device information (use `adb shell getprop ro.build.fingerprint`
if possible):
- TensorFlow Lite in Play Services SDK version (found in `build.gradle`):
- Google Play Services version
(`Settings` > `Apps` > `Google Play Services` > `App details`):
**Standalone code to reproduce the... | {
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"I realize that I am trying to use on mac a whl file created for linux... I am pretty sure it is the issue, but if someone can confirm that to me I would appreciate...",
"Yes it is. Try linux os with aarch64 type processor. aarch64 architecture not supported mac.",
"hi @huats ,\r\n\r\nLet me know if the provide... | 2024-05-12T21:58:48 | 2024-06-09T01:54:11 | 2024-06-09T01:54:08 | NONE | null | null | null | I have followed the instructions available [here](https://www.tensorflow.org/lite/guide/build_cmake_pip?hl=fr&_gl=1*uh09l8*_up*MQ..*_ga*NDczOTAyOTg5LjE3MTU1Mzg4MTY.*_ga_W0YLR4190T*MTcxNTUzODgxNi4xLjAuMTcxNTUzODgxNi4wLjAuMA.. ) to create some wheel files for aarch64 using the command
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"Hi @samrajput1143 ,\r\n\r\nCould you please test with tf-nightly and let us know whether this is replicable with nightly version as well?\r\n\r\n\r\n",
"I have python version 3.7.5 , can i install tf-nightly?"
] | 2024-05-12T06:17:16 | 2024-05-14T10:10:04 | null | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
binary
### TensorFlow version
2.11.0
### Custom code
Yes
### OS platform and distribution
ubuntu 18.04
### Mobile device
_No response_
### Python version
3.7.5
### Bazel version
_... | {
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