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Imported from GitHub PR https://github.com/openxla/xla/pull/13523
this fixed ROCm build due to https://github.com/openxla/xla/commit/e2a86549996ae6ac57f6eae31c1ed9aee4975bab#diff-1390f748feeae091b1bf42... | {
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`eq(k1, k2) -> hash(k1) == hash(k2)` must be true for hashtable usage to be valid.
Reverts changelist 641225077
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This CL changes `shard_arg_handlers` to be batched, in that it now receives a list of objects and a list of shardings and returns a list of array. This makes it possible to batch backend calls whenever it's beneficial to do so.
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Reverts changelist 641225077
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/13523 from ROCm:ci_hotfit_20240607 931ddf1d5b87c85c3fe1d825665015882d50ef42
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Reverts changelist 641225077
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Updates LLVM usage to match
[5f1adf0433c6](https://github.com/llvm/llvm-project/commit/5f1adf0433c6)
Reverts changelist 641225077
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Make it display the detected compute capability.
Reverts changelist 641225077
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It is currently flaky.
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Imported from GitHub PR https://github.com/openxla/xla/pull/13372
Copybara import of the project:
--
99192a7119725e1b80153f8b29a229acb191c4f7 by Ilia Sergachev <isergachev@nvidia.com>:
[GPU] Fail on conflicting autotuning results.
--
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} | PR #13062: FP8 Windowed Einsums
Imported from GitHub PR https://github.com/openxla/xla/pull/13062
Extends the windowed einsum handler to support collective FP8 GEMMs by shifting the dequantization of dot operands into the body of the while loops of all-gather and reduce-scatter windowed einsums.
Copybara import of th... | {
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} | [XLA:GPU] Experimental: Add --xla_gpu_per_fusion_autotune_cache_dir option
If the option is set, we will use / maintain a per-fusion autotune cache in the given directory.
The directory must exist.
Cache invalidation has to be handled by the user (e.g. please use an empty directory if you want to start with an empty... | {
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Also add an integration test for the input_slices emitter that
verifies this behavior.
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} | [XLA:GPU] Add constraints to `SymbolicTileAnalysis`.
Constraints are constructed from merging the constraints of all the
`SymbolicTile`s encountered while constructing the resulting symbolic tiled HLO
computation. If any of the `SymbolicTile`s is unsatisfiable, the construction
of the `SymbolicTileAnalysis` object doe... | {
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The new logic is simpler, better tested, and produces simpler output:
E.g. before:
```
compare-greater-than.4 {
p.1.lhs.7 = s32[] parameter(2)
p.1.rhs.8 = s32[] parameter(3)
constant.9 = pred[] constant(true)
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} | Integrate LLVM at llvm/llvm-project@5f1adf0433c6
Updates LLVM usage to match
[5f1adf0433c6](https://github.com/llvm/llvm-project/commit/5f1adf0433c6)
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"merged_at": "2024-06-... | Fix float conversions: fp8 and u64.
- fp8 was missing lowerings for cmpf and fptoi
- u64 was using incorrect upper bounds
This fixes unary_ops_test_gpu.
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"Possible workaround. Add these dependecies in the top level `WORKSPACE` file:\r\n\r\n```bazel\r\nhttp_archive(\r\n name = \"llvm_zstd\",\r\n build_file = \"@llvm-raw//utils/bazel/third_party_build:zstd.BUILD\",\r\n sha256 = \"7c42d56fac126929a6a85dbc73ff1db2411d04f104fae9bdea51305663a83fd0\",\r\n strip... | 2024-06-07T10:25:21 | 2024-06-11T14:14:15 | null | NONE | null | null | null | ### Issue type
Build/Install
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
source
### TensorFlow version
dd0c582
### Custom code
No
### OS platform and distribution
Ubuntu 20.04
### Mobile device
_No response_
### Python version
3.11.9
### Bazel v... | {
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See google/jax#21628 and google/jax#21637.
Reverts changelist 641225077
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In principle we could do this, but we need some fixes to
our vector size heuristics first. Right now, we generate
loops of size 4, which is too much (1024 bytes per warp).
But I'm not sure it's actually helpful in any case.
This fixes the `error: 'arith.constant' op requires ... | {
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"Sorry, I was in a wrong Conda env and using TF 2.15.1\r\n\r\nIt seems to have been implemented with keras 3 and TF 2.16.1\r\n"
] | 2024-06-07T09:02:14 | 2024-06-07T12:31:06 | 2024-06-07T10:43:14 | NONE | null | null | null | ### Issue type
Feature Request
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
2.16.1
### Custom code
No
### OS platform and distribution
_No response_
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
_No response_
... | {
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`eq(k1, k2) -> hash(k1) == hash(k2)` must be true for hashtable usage to be valid.
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This fixes bitcast_convert_test_gpu and probably some others.
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Updates LLVM usage to match
[d843c02aba5d](https://github.com/llvm/llvm-project/commit/d843c02aba5d)
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See the added test for an explanation of the problem. This fixes gpu_index_test.
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Reverts changelist 641225077
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/13523 from ROCm:ci_hotfit_20240607 931ddf1d5b87c85c3fe1d825665015882d50ef42
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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/69345/checks?check_run_... | 2024-06-06T22:35:11 | 2024-06-07T22:31:52 | null | NONE | null | false | {
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} | Hello @Venkat6871 , @eggie5
Fixed the #69284 issue.
I believe we just have to make sure to pass the inputs and the be consistent with the datatypes that we are using.
The vital observation that I was able to make is the indices list and the relationship between var and accum parameters, and the relationship ... | {
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Reverts changelist 641225077
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Reverts changelist 641225077
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/13062 from philipphack:u_fp8_windowed_einsum_xla 3ea415d65e47087bb077fa2b13e34c82a4dae87b
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"@ShoumitroC Could you try to use keras.layers.Lambda layer that allows you to define a custom function using a Python lambda expression that can operate on KerasTensors within the model building process?\r\nPlease upgrade to the latest TF version and if the issue still persists then kindly provide the standalone ... | 2024-06-06T21:16:12 | 2024-06-10T09:24:31 | null | NONE | null | null | null | ### Issue type
Build/Install
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
binary
### TensorFlow version
2.13.0
### Custom code
Yes
### OS platform and distribution
Mac OS x86-64
### Mobile device
Macbook
### Python version
3.9
### Bazel version
_No response_
### GCC/compiler... | {
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Updates LLVM usage to match
[79393124ff74](https://github.com/llvm/llvm-project/commit/79393124ff74)
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For example, tree_map(..., None, [2, 3]) did not raise an error, but None is a container and only leaves can be considered tree prefixes in this case.
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The state is not particularly necessary and adds indirection to the tests,
which is not desirable.
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The C++ API also uses a type named "Interpreter", so "Interpreter API" is a bit ambiguous.
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} | Passes kv_store to ifrt::PjRtClient.
This is required for cross-host device transfer. Devices between different hosts need a way to communicate, and we will use kv_store for that.
Update the signature of relevant APIs and pybind to create a ifrt::PjRtClient.
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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/69323/checks?check_run_... | 2024-06-06T14:31:08 | 2024-06-10T10:20:46 | 2024-06-10T10:20:44 | NONE | null | true | {
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FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/13542 from Tixxx:tixxx/dce_control_dep 1de482f5a80f4e9a9b2c8203129111d2aaa63f28
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"isn't this because the tensor is too big for the ram ? if you reduce the size to 20000, 20000 it should output without the resource exhaustion error.",
"> isn't this because the tensor is too big for the ram ? if you reduce the size to 20000, 20000 it should output without the resource exhaustion error.\r\n\r\n\... | 2024-06-06T14:30:10 | 2024-06-11T04:55:47 | null | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
TensorFlow Nightly
### Custom code
Yes
### OS platform and distribution
Linux Ubuntu 22.04.3 LTS (x86_64)
### Mobile device
_No response_
### Python version
_No response_
### Bazel ve... | {
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It loads the kernel made of a pointer to function on host machine.
This is useful for loading kernel compiled together with xla by regular cpp compiler.
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`(a mod b) * x` worked, but `(a * x) mod b` didn't.
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FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/13461 from knightXun:transpose-typo e7c6c23be44648237a31d17bf2574c4f26510889
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Imported from GitHub PR https://github.com/openxla/xla/pull/11425
It is a sub PR of https://github.com/openxla/xla/pull/9042 to add sycl platform
Copybara import of the project:
--
7d0c37057c673f784089ce961d24276a496d43bd by Sheng, Yang <yang.sheng@intel.com>:
Add sycl platfor... | {
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Whether SPMD is used is inferrable from number of partitions, having both
num_partitions and use_spmd specified is redundant.
An extra flag to skip hlo passes is also redundant, since
--xla_disbale_hlo_passes could be just used.
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Imported from GitHub PR https://github.com/openxla/xla/pull/13461
Copybara import of the project:
--
e7c6c23be44648237a31d17bf2574c4f26510889 by knightXun <1004815462@qq.com>:
typo: fix transpse
Merging this change closes #13461
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"You might want to look into Quantization-Aware Training",
"I think no, because I train Pytorch models and then convert them to onnx and tflite",
"Hi @DaraOrange , this issue may be resolved by following a different work flow.\r\n\r\nHave you tried using [AI-Edge-Torch](https://github.com/google-ai-edge/ai-edge... | 2024-06-06T11:18:18 | 2024-06-11T09:42:32 | null | NONE | null | null | null | Hi! I'm trying to quantize MobileNetV3 with tflite, but int8-model performs very poor. I think, it is because of linear quantization, which is too simple method not appropriate for any weights distributions. What else can I try? Are you going to support logarithmic scale for quantization in the future? | {
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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/69310/checks?check_run_... | 2024-06-06T11:00:56 | 2024-06-06T11:49:58 | 2024-06-06T11:49:57 | NONE | null | true | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/13408
This PR aims to fix the mlir_hlo tests which are designed to test the implementation of the HLO (High-Level Optimizer) for MLIR (Multi-Level Intermediate Representation).
**Error**
mlir_hlo tests were failing o... | {
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- Add a comment
- Verify that the rewrite is actually happening and CUB sort is indeed used. I got bitten by a passing test with a temporary change that didn't actually use CUB.
- Make the test size medium. Otherwise it timed out quite a lot for me.
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I just coincidentally noticed this is missing.
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"@ian-huu One workaround could be to specify the input names during saving using the tf.saved_model.save API with the input argument. This ensures that all your model's inputs are included in the serving_default signature.\r\nThank you!",
"> @ian-huu One workaround could be to specify the input names during savin... | 2024-06-06T09:43:20 | 2024-06-11T06:55:53 | null | NONE | null | null | null | ### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
binary
### TensorFlow version
2.16.1
### Custom code
Yes
### OS platform and distribution
Linux Ubuntu 22.04.1
### Mobile device
_No response_
### Python version
3.10.13
### Bazel version
_No response_
### GCC/c... | {
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Imported from GitHub PR https://github.com/openxla/xla/pull/13258
Copybara import of the project:
--
735291df0028b9d3a1a73a7db8fe5104910b4ca5 by Ilia Sergachev <isergachev@nvidia.com>:
Give GPU compiler class access to PJRT key-value store.
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[55d2fffdae55](https://github.com/llvm/llvm-project/commit/55d2fffdae55)
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Before, if an HLO snapshot was passed, it would use the HLO module from the snapshot but not the inputs, if --input_format was omitted
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