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PR #12538: [GPU] Fix OSS compilation of previously disabled tests.
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PR #12538: [GPU] Fix OSS compilation of previously disabled tests.
Imported from GitHub PR https://github.com/openxla/xla/pull/12538
Copybara import of the project:
--
78d74154a1693426014eef2940e759d1e36902ed by Ilia Sergachev <[email protected]>:
[GPU] Fix OSS compilation of previously disabled tests.
Merging this change closes #12538
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12538 from openxla:fix_test_compilation 78d74154a1693426014eef2940e759d1e36902ed
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Update TFRT dependency to use revision
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Update TFRT dependency to use revision
http://github.com/tensorflow/runtime/commit/76dfd9f8757c12739429c8178d1b0c5167862ae7.
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[IFRT] Wrap RemapPlan::mappings with shared_ptr
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[IFRT] Wrap RemapPlan::mappings with shared_ptr
`xla::ifrt::RemapPlan`'s `mappings` is frequently reused across different
`xla::ifrt::RemapPlan`. It can be costly to keep a copy of `mappings` for each
plan if the mappings is not trivially small.
This change wraps `mappings` with `std::shared_ptr` so that it can be shared
more cheaply across multiple plans.
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In PjRtStreamExecutorBuffer::Delete, fix some bugs causing memory corruption.
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In PjRtStreamExecutorBuffer::Delete, fix some bugs causing memory corruption.
The bug is that we don't wait for events using the buffer on the Compute stream, and also the definition events. This can cause a race condition where the buffer is deleted before it is read/written, which can lead to memory corruptions.
For events on the compute stream, the fix is to schedule the deallocation on the compute stream.
For the definition events, the fix is to wait for them on a borrowed stream if they are not defined on the compute stream.
This change probably wouldn't be needed if all writes are scheduled on the compute stream, but that is not the case today. We have a lot of usages of the h2d and d2d stream.
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Add pattern to fuse quant weights into transpose conv.
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Add pattern to fuse quant weights into transpose conv.
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[XLA:GPU] Clang-tidy cleanup for shadowed class member in xla/service/gpu/tests/gpu_fused_mha_test.cc
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[XLA:GPU] Clang-tidy cleanup for shadowed class member in xla/service/gpu/tests/gpu_fused_mha_test.cc
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[XLA:GPU] #includes cleanup for xla/service/gpu/tests/gemm_rewrite_test.cc, nop_custom_call_test.cc
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[XLA:GPU] #includes cleanup for xla/service/gpu/tests/gemm_rewrite_test.cc, nop_custom_call_test.cc
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Change to add attribute before building
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Change to add attribute before building
Avoids issues when converting to properties early (which happens along most
generated build paths today and should be all in future).
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upgrading oneDNN version 3.4.1
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This PR upgrades oneDNN version from v3.3.4 to v3.4.1, this PR has been tested on several models across different platforms including cascade-lake, sapphire-rapids, and granite-rapids
Several bug fixes have been resolved in this version. Details can be found here https://github.com/oneapi-src/oneDNN/releases
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Move schema_fbs_with_reflection to mlir/lite/schema.
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Move unplaced ops that have a single output of an identity to the same as the
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Move unplaced ops that have a single output of an identity to the same as the
identity op.
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[Testing] Code Coverage: Increase Code Coverage of //third_party/tensorflow/core/runtime_fallback/util to at least 75%
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[Testing] Code Coverage: Increase Code Coverage of //third_party/tensorflow/core/runtime_fallback/util to at least 75%
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PR_kwDOArmXAs5vlAIi
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Update TFRT dependency to use revision
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Update TFRT dependency to use revision
http://github.com/tensorflow/runtime/commit/ac3f51614db030270303c593a41f46bea68dab3d.
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12439 from trevor-m:tmorris-multinode-runner ad1705053185c32abbf4d917f2b1fd669d5b6893
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Add a pattern to lower a stablehlo.composite with `jax.image.resize` in `nearest` mode to a tflite.resize_nearest_neighbor op.
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Add a pattern to lower a stablehlo.composite with `jax.image.resize` in `nearest` mode to a tflite.resize_nearest_neighbor op.
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PR_kwDOArmXAs5vk-VS
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Recreate iterator on the end of epoch instead of at begininng
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[
"Hi @austinzh It looks like your PR relates to the Keras component. Please submit it to the github.com/keras-team/keras repository instead. Thank you for your contribution!\r\n@fchollet, @qlzh727",
"@gbaned A little confused. I found the master of keras-team/keras is not the same as the keras in tensorflow repo.\r\nWhat is the proper process of contribute to the keras version that tensorflow now integrate with?"
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We already create a data_iterator at the beginning. No point to recreate it again at the beginning of epoch.
This should fix issue like [this](https://stackoverflow.com/questions/69843184/using-sagemaker-pipe-mode-with-an-s3-directory-of-tfrecords/77532311#77532311)
Also will improve cool start time when use data that have slow initialization and do prefetch or buffering at init.
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PR_kwDOArmXAs5vk-Sy
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Add SavedModel to StableHLO Converter to TensorFlow pip package
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NONE
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Add SavedModel to StableHLO Converter to TensorFlow pip package
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Add a function to get delegate options using the C API.
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Add a function to get delegate options using the C API.
- Remove redundant helper function.
- Store the weight cache path inside the delegate and update the internal
options object to use it.
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XNNPack weight cache provider: update the internal options object to keep track of the cache path.
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NONE
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XNNPack weight cache provider: update the internal options object to keep track of the cache path.
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PR_kwDOArmXAs5vk2Hh
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Move schema_fbs_with_mutable to mlir/lite/schema.
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NONE
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Move schema_fbs_with_mutable to mlir/lite/schema.
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[xla:ffi] Add support for FFI execution context to PjRtCpuClient
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[xla:ffi] Add support for FFI execution context to PjRtCpuClient
Add a test for passing arbitrary user data via execution context side channel to XLA FFI handlers registered for a HOST platform
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PR #12439: [GPU] Multinode support for multihost_hlo_runner
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PR #12439: [GPU] Multinode support for multihost_hlo_runner
Imported from GitHub PR https://github.com/openxla/xla/pull/12439
This PR adds multinode support to the multihost_hlo_runner. To use, there is a new command line argument `address` for the address of the coordinator/root node.
Example usage with SLURM:
```
bazel run //xla/tools/multihost_hlo_runner:hlo_runner_main -- \
--task_id=${SLURM_PROCID} \
--num_nodes=${SLURM_NTASKS} \
--address="${SLURM_LAUNCH_NODE_IPADDR}:12345" \
...
```
Copybara import of the project:
--
ad1705053185c32abbf4d917f2b1fd669d5b6893 by Trevor Morris <[email protected]>:
Multinode changes for hlo_runner_main
Merging this change closes #12439
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12439 from trevor-m:tmorris-multinode-runner ad1705053185c32abbf4d917f2b1fd669d5b6893
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Updating schema location.
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Updating schema location.
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[XLA] [NFC] Serialize all autotuning results
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[XLA] [NFC] Serialize all autotuning results
The previous logic for filtering by-module wasn't correct, as instructions
could be modified after autotuning, resuling in not all relevant information
serialized.
This could result in excessive data serialized, but autotuning results are very
small compared to the module size and the compiled artifact.
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Remove broken TSL tests from `TARGET_FILTERS`, tag them as `no_oss` instead
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Remove broken TSL tests from `TARGET_FILTERS`, tag them as `no_oss` instead
They will be fixed post TSL move
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Use StreamExecutorInterface::CreateEvent in event_pool.cc.
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NONE
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Use StreamExecutorInterface::CreateEvent in event_pool.cc.
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Make compiler/jit targets use StreamExecutorInterface::CreateEvent to create stream_executor::Events.
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Make compiler/jit targets use StreamExecutorInterface::CreateEvent to create stream_executor::Events.
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PR_kwDOArmXAs5vkYhR
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Propagate error to output if the input buffer has error.
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Propagate error to output if the input buffer has error.
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[Multi-host GPU]Integrate GPU topology into PjRtClient for multi-host GPU support
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[Multi-host GPU]Integrate GPU topology into PjRtClient for multi-host GPU support
--Integrate GpuTopology into PjRtTopologyDescription to represent multi-host GPU topologies
--Utilize GlobalTopology to build GpuTopology during PjRt client creation
--Update relevant tests
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[Cleanup] Update all instances of tfrt::t:: to use tfrt::tfrt_tensor
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[Cleanup] Update all instances of tfrt::t:: to use tfrt::tfrt_tensor
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Clean up the build tags for the gpu runner test target. Removes this test from *san due to this: go/cuda#sanitizers-for-cuda-host-code.
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Clean up the build tags for the gpu runner test target. Removes this test from *san due to this: go/cuda#sanitizers-for-cuda-host-code.
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PR_kwDOArmXAs5vj6CN
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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PR_kwDOArmXAs5vjr9S
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Add checks to catch use-before-create and use-after-delete uses of remote tensor handles before the remote manager attempts to deserialize a handle
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Add checks to catch use-before-create and use-after-delete uses of remote tensor handles before the remote manager attempts to deserialize a handle
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When computing the set of reduced times, keep just the latest one if multiple primitives enter the liveness profile consecutively.
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NONE
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When computing the set of reduced times, keep just the latest one if multiple primitives enter the liveness profile consecutively.
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gpu_delegate: Allow broadcast of [1, 1] to [1, x, y, z]
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gpu_delegate: Allow broadcast of [1, 1] to [1, x, y, z]
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Fix a batch of ClangTidy issues.
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NONE
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Fix a batch of ClangTidy issues.
Mostly naming, some includes, some miscellaneous other style guide
violations.
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[XLA:GPU] Error out early on missing autotuning cache when required
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NONE
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[XLA:GPU] Error out early on missing autotuning cache when required
This is technically a performance optimization: we would still error out later
on otherwise, but after recompiling & running a bunch of modules, hence no test.
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PR_kwDOArmXAs5vjVva
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PR #12515: [ROCm] Fix build break introduced in ffa7bb5 and df736d7
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NONE
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PR #12515: [ROCm] Fix build break introduced in ffa7bb5 and df736d7
Imported from GitHub PR https://github.com/openxla/xla/pull/12515
Fix build break introduced in ffa7bb5 and df736d7
Copybara import of the project:
--
499687ea87e38be681cb978d15ebd314377623c4 by Harsha HS <[email protected]>:
Fix build break introduced in ffa7bb5 and df736d7
Merging this change closes #12515
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12515 from ROCm:ci_fix_build_break_20240515 499687ea87e38be681cb978d15ebd314377623c4
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Use absl::Status instead of xla::Status now that they're identical.
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NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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[] | 2024-05-15T14:50:30 | 2024-05-15T18:16:53 | 2024-05-15T18:16:53 |
NONE
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Use absl::Status instead of xla::Status now that they're identical.
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PR_kwDOArmXAs5vi4Bp
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[XLA:GPU] Remove GpuStatus.
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[] | 2024-05-15T14:43:56 | 2024-05-16T09:57:11 | 2024-05-16T09:57:10 |
NONE
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[XLA:GPU] Remove GpuStatus.
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Use absl::Status instead of xla::Status now that they're identical.
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[] | 2024-05-15T14:38:54 | 2024-05-16T23:26:16 | 2024-05-16T23:26:13 |
NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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[] | 2024-05-15T14:36:04 | 2024-05-16T19:32:53 | 2024-05-16T19:32:50 |
NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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[] | 2024-05-15T14:35:29 | 2024-05-16T21:16:02 | 2024-05-16T21:16:01 |
NONE
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Use absl::Status instead of xla::Status now that they're identical.
Reverts c031655ca9514e7946bb87eda17cf5932c381a8b
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PR_kwDOArmXAs5vix_a
| 67,646 |
Fix wrong register constraints produced for some types in WGMMAWaitGroupOpPattern
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NONE
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Fix wrong register constraints produced for some types in WGMMAWaitGroupOpPattern
This is a minimal patch to unblock folks. I'll work on polishing it up and upstreaming a proper fix to OpenAI.
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PR_kwDOArmXAs5vixn7
| 67,645 |
[XLA:GPU] Use IndexingMap::RemoveUnusedSymbols instead of WithoutRangeVars
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[XLA:GPU] Use IndexingMap::RemoveUnusedSymbols instead of WithoutRangeVars
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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PR_kwDOArmXAs5viwlM
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
Reverts c031655ca9514e7946bb87eda17cf5932c381a8b
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I_kwDOArmXAs6I-jz_
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ABORTED: Shutdown in `tf.raw_ops.PriorityQueueV2`
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[
"@x0w3n `tf.raw_ops.PriorityQueueV2` function creates a priority queue data structure. The container name \"test_container\" contains characters that are not allowed. Could we try to rename the container to use only alphanumeric characters (a-z, A-Z, 0-9) and underscores (_). Avoid special characters like \"-\", \"*\", \"!\". I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/5615a41a5b64ea5bc2de53ad94a3ce71/67642.ipynb). Thank you!",
"> @x0w3n `tf.raw_ops.PriorityQueueV2` function creates a priority queue data structure. The container name \"test_container\" contains characters that are not allowed. Could we try to rename the container to use only alphanumeric characters (a-z, A-Z, 0-9) and underscores (_). Avoid special characters like \"-\", \"*\", \"!\". I was able to replicate the issue reported [here](https://colab.research.google.com/gist/sushreebarsa/5615a41a5b64ea5bc2de53ad94a3ce71/67642.ipynb). Thank you!\r\n\r\nNoted with thanks.",
"@x0w3n Could you please let us know if the issue got resolved ?",
"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.",
"> @x0w3n Could you please let us know if the issue got resolved ?\r\n\r\nI have got it. Thank you.",
"Are you satisfied with the resolution of your issue?\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/67642\">Yes</a>\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/67642\">No</a>\n"
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NONE
| null | null | null |
### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
tf 2.16
### Custom code
Yes
### OS platform and distribution
Linux Ubuntu 22.04.3 LTS (x86_64)
### Mobile device
_No response_
### Python version
3.11
### Bazel version
_No response_
### GCC/compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current behavior?
When the component_types parameter of tf.raw_ops.PriorityQueueV2 contains some special characters, such as "-", "*", "!" etc., it will trigger "Local rendezvous is aborting with status: ABORTED: Shutdown" error.
### Standalone code to reproduce the issue
```shell
import tensorflow as tf
shapes = [1, 1]
component_types = [tf.float32, tf.int32]
capacity = 10
container = "test_container"
shared_name = "testsharedname"
queue_handle = tf.raw_ops.PriorityQueueV2(
shapes=shapes,
component_types=component_types,
capacity=capacity,
container=container,
shared_name=shared_name
)
```
### Relevant log output
```shell
2024-05-15 14:25:39.269296: W tensorflow/core/framework/op_kernel.cc:1839] OP_REQUIRES failed at resource_op_kernel.h:76 : INVALID_ARGUMENT: container contains invalid characters: test!container
2024-05-15 14:25:39.269340: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: INVALID_ARGUMENT: container contains invalid characters: test!container
Traceback (most recent call last):
File "/home/tf/test.py", line 10, in <module>
queue_handle = tf.raw_ops.PriorityQueueV2(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/anaconda3/envs/tf2.16/lib/python3.11/site-packages/tensorflow/python/util/tf_export.py", line 377, in wrapper
return f(**kwargs)
^^^^^^^^^^^
File "/root/anaconda3/envs/tf2.16/lib/python3.11/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 3240, in priority_queue_v2
return priority_queue_v2_eager_fallback(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/anaconda3/envs/tf2.16/lib/python3.11/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 3312, in priority_queue_v2_eager_fallback
_result = _execute.execute(b"PriorityQueueV2", 1, inputs=_inputs_flat,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/anaconda3/envs/tf2.16/lib/python3.11/site-packages/tensorflow/python/eager/execute.py", line 53, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tensorflow.python.framework.errors_impl.InvalidArgumentError: {{function_node __wrapped__PriorityQueueV2_device_/job:localhost/replica:0/task:0/device:CPU:0}} container contains invalid characters: test!container [Op:PriorityQueueV2]
2024-05-15 14:25:39.422495: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: ABORTED: Shutdown
```
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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PR #9827: [ROCm] Stream executor API logging API
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PR #9827: [ROCm] Stream executor API logging API
Imported from GitHub PR https://github.com/openxla/xla/pull/9827
Separated from https://github.com/openxla/xla/pull/9593.
This adds a low-overhead ability to log stream executor API calls, for testing purposes (unit tests can enable the functionality and use it to verify that high-level operations result in correct sequences of low-level calls). At present, this only covers BlasGemm / BlasLt calls on ROCm backend.
Copybara import of the project:
--
41732ac48c5383f33d428fe76fcebe02506d5b52 by Eugene Kuznetsov <[email protected]>:
Stream executor API logging API
Merging this change closes #9827
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/9827 from ROCm:ci_se_logging 41732ac48c5383f33d428fe76fcebe02506d5b52
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PR_kwDOArmXAs5vicci
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[PJRT:CPU] Bump the stack size for the CPU client thread pool to 8MB.
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[PJRT:CPU] Bump the stack size for the CPU client thread pool to 8MB.
2MB was found to be causing crashes in JAX linear algebra tests that call into lapack/blas.
OpenBLAS appears to have fairly large stack size requirements.
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[PJRT:CPU] Provide a compile-time thread pool.
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[PJRT:CPU] Provide a compile-time thread pool.
The OneDNN matmul rewriter starts a thread pool if one wasn't provided as a compile option, spawning many threads per compilation. If we pass a preexisting thread pool, we can save the cost of creating and tearing down threads.
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/9666 from ROCm:ci_fused_conv 8792f892770aba54e38a5352d9bec1d003e341d3
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PR_kwDOArmXAs5vhwbO
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Reduces the # of memory constraints to a subset of times (instead of all possible times).
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Reduces the # of memory constraints to a subset of times (instead of all possible times).
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PR_kwDOArmXAs5vht3m
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Normalize layouts for Scatter.
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Normalize layouts for Scatter.
Unfortunately this requires to temporarily use unsorted update_window_dims
attribute. ScatterSimplifier can turn this into valid HLO again.
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Change kMaxDims value to TFLITE_STABLEHLO_PAD_PARAMS_MAX_DIMENSION_COUNT to avoid buffer size mismatch in tensorflow/lite/kernels/stablehlo_pad.cc
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"Hi @majiddadashi Any update on this PR? Please. Thank you!"
] | 2024-05-15T11:52:04 | 2024-06-08T18:05:56 | null |
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The bug was found by Svace static analyzer:
1. `kMaxDims` is assigned 6 on https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/stablehlo_pad.cc#L36
2. Arrays `edge_pad_low_`, `edge_pad_high_` and `interior_pad_` of `kMaxDims` uint64_t elements are used later as destinations in `memcpy` operations (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/kernels/stablehlo_pad.cc#L99-L107) with size operand that equals `TFLITE_STABLEHLO_PAD_PARAMS_MAX_DIMENSION_COUNT * sizeof(uint64_t)`. It may lead to a buffer overflow.
Closes #66834
cc @mihaimaruseac
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PR_kwDOArmXAs5vgfY8
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PR #12436: [XLA:CPU][oneDNN] Enable Matmul + BiasAdd + Elu / Tanh / Relu6 fusions for onednn
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PR #12436: [XLA:CPU][oneDNN] Enable Matmul + BiasAdd + Elu / Tanh / Relu6 fusions for onednn
Imported from GitHub PR https://github.com/openxla/xla/pull/12436
This PR enables MatMul fusions with different activations viz. Elu, Tanh and Relu6.
Copybara import of the project:
--
9895b022aa66ee0f1040d0f6e557382c9dd77b99 by Gauri1 Deshpande <[email protected]>:
Enable Matmul + BiasAdd + Elu / Tanh / Relu6 fusions for onednn
--
c277c70da3a1bbe05d0d637ec2d4e9ce220f7f3f by Gauri1 Deshpande <[email protected]>:
address review comments - sort name, remove default layout and remove default attributes
Merging this change closes #12436
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12436 from Intel-tensorflow:gaurides/mm_activations c277c70da3a1bbe05d0d637ec2d4e9ce220f7f3f
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PR #10803: Expose CompiledMemoryStats on CPU and GPU
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PR #10803: Expose CompiledMemoryStats on CPU and GPU
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 a given executable. Buffer-related fields in CompiledMemoryStats are currently missing for both the GPU and the CPU backend. This PR computes the missing fields using the executable's underlying [BufferAssignment](https://github.com/openxla/xla/blob/50c6489cb058881cc65622605c9c55029abebc5b/xla/service/buffer_assignment.h#L491) / buffer allocations.
# Example
```python
import jax
import jax.numpy as jnp
def f(a, b):
ms = jnp.sum(a, axis=1, keepdims=True) / a.shape[1]
return a * jax.lax.rsqrt(ms) + b
a0 = jax.random.uniform(jax.random.PRNGKey(0), (128, 128))
b0 = jax.random.uniform(jax.random.PRNGKey(0), (128, 128))
f_jit = jax.jit(f, donate_argnums=(0,))
print(f_jit.lower(a0, b0).compile().memory_analysis())
# CompiledMemoryStats(
# generated_code_size_in_bytes=5792,
# argument_size_in_bytes=131072,
# output_size_in_bytes=65536,
# alias_size_in_bytes=65536,
# temp_size_in_bytes=512,
# host_generated_code_size_in_bytes=0,
# host_argument_size_in_bytes=0,
# host_output_size_in_bytes=0,
# host_alias_size_in_bytes=0,
# host_temp_size_in_bytes=0)
```
Note the use of `donate_argnums=(0,)` which allows XLA to modify the first input buffer in-place and reuse it as the output. This is reflected in `alias_size_in_bytes` -- without buffer donation that number is zero.
# Open questions
- Does this match the semantics for the TPU backend?
- `dynamic_cast`-ing on `gpu::Executable` ain't great. Do we want `Executable`s to expose their buffer allocations publicly (i.e. GpuExecutable's [GetAllocations](https://github.com/openxla/xla/blob/f6ce6c11ceac904c9c4840fcec5f1ee715291425/xla/service/gpu/gpu_executable.h#L164) but for all Executables)?
Copybara import of the project:
--
f9ae2c4e367aed813af74ae50edfd27a6f9304eb by Georg Stefan Schmid <[email protected]>:
Expose CompiledMemoryStats on CPU and GPU
Merging this change closes #10803
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/10803 from gspschmid:georg/compiledmemstats-gpu f9ae2c4e367aed813af74ae50edfd27a6f9304eb
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I_kwDOArmXAs6I72NF
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Exit code 137 in `tf.raw_ops.ResizeNearestNeighborGrad`
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"Hi **@LongZE666** ,\r\n- I tried to run your code on colab using TF v2.16.1, nightly and faced the same issue. Please find the [gist](https://colab.sandbox.google.com/gist/Venkat6871/1a43c3a531959a59e48bd735e643f6df/67626_2-16-1-nightly.ipynb) here for reference. \r\n\r\nThank you!"
] | 2024-05-15T09:47:39 | 2024-05-22T04:11:38 | null |
NONE
| null | null | null |
### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
Yes
### Source
source
### TensorFlow version
tf 2.16.1
### Custom code
Yes
### OS platform and distribution
Ubuntu 20.04
### Mobile device
_No response_
### Python version
_No response_
### Bazel version
_No response_
### GCC/compiler version
_No response_
### CUDA/cuDNN version
_No response_
### GPU model and memory
_No response_
### Current behavior?
When the value in the input `size` is too large, program exceeds the memory limit.
### Standalone code to reproduce the issue
```shell
# Signal --4;2024-05-14 00:40:39.895950: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.2024-05-14 00:40:39.896316: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.2024-05-14 00:40:39.900744: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.2024-05-14 00:40:39.956390: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.2024-05-14 00:40:40.842339: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
# ResizeNearestNeighborOpGrad
import tensorflow as tf
align_corners = True
half_pixel_centers = False
grads = tf.constant(1.5e+300, shape=[1,8,16,3], dtype=tf.float64)
size = tf.constant([65534,65534], shape=[2], dtype=tf.int32)
tf.raw_ops.ResizeNearestNeighborGrad(grads=grads, size=size, align_corners=align_corners, half_pixel_centers=half_pixel_centers)
```
### Relevant log output
```shell
(tensorflow-2.16.1-orig) root@b29bda27c601:/mnt# python tests/ResizeNearestNeighborGrad.py
2024-05-15 08:43:01.439844: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-05-15 08:43:01.440211: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
2024-05-15 08:43:01.444264: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
2024-05-15 08:43:01.498275: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-05-15 08:43:02.744313: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
Killed
```
```
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XNNPack weight cache provider: refactor code.
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XNNPack weight cache provider: refactor code.
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PR #9666: [ROCm] Fused convolution+bias+activation
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PR #9666: [ROCm] Fused convolution+bias+activation
Imported from GitHub PR https://github.com/openxla/xla/pull/9666
This PR enables MIOpen convolution+bias+activation fusion for ROCm and updates fusion unit tests accordingly.
Copybara import of the project:
--
bd5be494abe6621dfd2c4ebcca4f8992077d8a89 by Eugene Kuznetsov <[email protected]>:
Switch to NHWC for ROCm and F16
--
8792f892770aba54e38a5352d9bec1d003e341d3 by Eugene Kuznetsov <[email protected]>:
Fused convolution+bias+activation
Merging this change closes #9666
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/9666 from ROCm:ci_fused_conv 8792f892770aba54e38a5352d9bec1d003e341d3
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[XLA:GPU] Pass the CUDA / ROCm toolkit version explicitly for autotuning and GEMM rewriting.
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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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[XLA:GPU] Migrate while loop extraction to utility function.
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[XLA:GPU] Migrate while loop extraction to utility function.
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12463 from ROCm:ci_fix_build_break_20240514 fd95e342a4e8de6c8348df3576510584a0020150
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I_kwDOArmXAs6I7EVj
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Does anyone know which version of ROCM is used to build the tensorflow-rocm ?
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[
"@jaslip ROCm 6.0.2: This version is used to build tensorflow-rocm version 2.14.0.602 \r\nROCm 6.0.0 (or later): This version is used to build tensorflow-rocm versions 2.13.1.602 and later \r\nIt's important to note that not all tensorflow-rocm versions are compatible with all ROCm6 versions.\r\n\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. Please reopen if you'd like to work on this further.",
"Are you satisfied with the resolution of your issue?\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/67620\">Yes</a>\n<a href=\"https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/67620\">No</a>\n"
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NONE
| null | null | null |
In this Pypi page, there is no ROCM version information. I need to confirm whether ROCM 6 is used.
https://pypi.org/project/tensorflow-rocm/2.14.0.600/#files
Can someone help? Thank you very much.
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PR_kwDOArmXAs5vfbIf
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Fix ROCm build after TypedKernel change
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Fix ROCm build after TypedKernel change
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PR #12463: [ROCm] Fix build break in `xla/service/gpu/runtime/convolution_thunk.cc`
Imported from GitHub PR https://github.com/openxla/xla/pull/12463
Fix build break introduced in db8f9c0cf2bf08b171aec2cbe3da2fcb074a6207
Copybara import of the project:
--
42d5839ffb47362a7f6789ba98ef50b31189dccc by Harsha HS <[email protected]>:
[ROCm] Fix build break in `xla/service/gpu/runtime/convolution_thunk.cc`
--
fd95e342a4e8de6c8348df3576510584a0020150 by Harsha HS <[email protected]>:
Gaurd header using TENSORFLOW_USE_ROCM
Merging this change closes #12463
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12463 from ROCm:ci_fix_build_break_20240514 fd95e342a4e8de6c8348df3576510584a0020150
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[XLA:GPU] Remove unused sleep kernel
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[XLA:GPU] Remove unused sleep kernel
Nothing is using the sleep kernel, so let's remove it
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"Hi @james-choncholas Can you please sign the CLA? Thank you!",
"Force-pushed to update the commits email address to the one associated with my Google contributor CLA.",
"Hi @rohan100jain Any update on this PR? Please. Thank you!"
] | 2024-05-15T06:29:19 | 2024-06-07T17:23:52 | null |
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ConcreteFunction properly flattens structured inputs (e.g. composite tensors) when called, but it does not pack/un-flatten the outputs. When ConcreteFunction outputs are structured, they must be packed back into their structured form to match the function signature.
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PR #12328: Make shared cache read/write logic more clearly for transpose mlir emitter
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PR #12328: Make shared cache read/write logic more clearly for transpose mlir emitter
Imported from GitHub PR https://github.com/openxla/xla/pull/12328
Current transpose mlir emitter allocate shared cache with shape 32x1x32 for transpose 2-1-0. But the read indices of shared cache are {0, y, x} as [this line](https://github.com/openxla/xla/blob/main/xla/service/gpu/fusions/transpose_mlir.cc#L190) shows, which is not compatible with 32x1x32 shape. What's strange is that transpose 2-1-0 can run successfully using transpose mlir emitter. I find the reason is that lower tensor pass use [linear index](https://github.com/openxla/xla/blob/main/xla/service/gpu/fusions/mlir/lower_tensors.cc#L148) to access shared cache, which is lucky to get right result. For example, the strides of 32x1x32 are {32, 32, 1}, and the linear index of {0, y ,x} is 0 * 32 + y * 32 + 32.
I am not sure if it is as expected or just mistake. If reviewer think no need of this PR, feel free to close.
Copybara import of the project:
--
bfb21798ee518dc11293a5683669add619a38e53 by Zhou, Lingzhi <[email protected]>:
make shared cache read/write logic more clearly for transpose mlir emitter
--
0c9033334835bc8a14310e5ee059489cea7b5309 by Zhou, Lingzhi <[email protected]>:
refactor
--
5554110835fc18207fb466587c1aeb20c3a542fe by Zhou, Lingzhi <[email protected]>:
pad shared cache
--
8c17818baa1e2477952df15e412a6463f73106ab by Zhou, Lingzhi <[email protected]>:
include missing file
Merging this change closes #12328
FUTURE_COPYBARA_INTEGRATE_REVIEW=https://github.com/openxla/xla/pull/12328 from lingzhi98:lingzhi/transpose_mlir_210 8c17818baa1e2477952df15e412a6463f73106ab
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Fixed the test failure.
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Fixed the test failure.
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In `xla::ShardingPropagation`, remove users and the parameters in the called computations in `already_inferred_from_operands` when clearing the cache.
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In `xla::ShardingPropagation`, remove users and the parameters in the called computations in `already_inferred_from_operands` when clearing the cache.
Before this cl, shardings may not be completely propagated.
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Add unit test for async_value_tensor.
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Add unit test for async_value_tensor.
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Use absl/numeric/bits.h for bit manipulation.
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NONE
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Use absl/numeric/bits.h for bit manipulation.
This reduces code duplication and allows us to reuse optimized code.
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Use absl::Status instead of xla::Status now that they're identical.
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NONE
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Use absl::Status instead of xla::Status now that they're identical.
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Allow overriding some methods in all_gather_decomposer.
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NONE
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Allow overriding some methods in all_gather_decomposer.
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Updates the benchmarking tool documentation with discovery text about flex ops, more information about flex ops, and an additional section regarding creating a custom version of the app with user-supplied custom ops.
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NONE
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Updates the benchmarking tool documentation with discovery text about flex ops, more information about flex ops, and an additional section regarding creating a custom version of the app with user-supplied custom ops.
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Disable pjrt runner for scatter test as it fails on some cases
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NONE
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Disable pjrt runner for scatter test as it fails on some cases
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Improve errors upon service shutdown.
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Improve errors upon service shutdown.
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Remove unused Stream methods and includes in stream.h.
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Remove unused Stream methods and includes in stream.h.
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[XLA:GPU] Clang-tidy cleanup for xla/service/gpu/... for const-correctness
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[XLA:GPU] Clang-tidy cleanup for xla/service/gpu/... for const-correctness
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Make TpuExecutor use StreamExecutorInterface to create Events.
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Make TpuExecutor use StreamExecutorInterface to create Events.
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PR_kwDOArmXAs5vdfEc
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Reduces the # of memory constraints to a subset of times (instead of all possible times).
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Reduces the # of memory constraints to a subset of times (instead of all possible times).
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PR_kwDOArmXAs5vdcrN
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Move Event creation into StreamExecutorInterface.
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Move Event creation into StreamExecutorInterface.
This is the first step in eliminating the pimpl pattern from Events. Backward references made me had to temporarily eliminate the event target. Eventually having Event inherit from EventInterface will enable it to be separated out again.
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PR_kwDOArmXAs5vdcph
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Bump ODML to target StableHLO v1.0.0
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}
|
Bump ODML to target StableHLO v1.0.0
|
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| 2,296,504,294 |
PR_kwDOArmXAs5vdR7b
| 67,592 |
Remove references to unused tags in XLA build script
|
{
"login": "copybara-service[bot]",
"id": 56741989,
"node_id": "MDM6Qm90NTY3NDE5ODk=",
"avatar_url": "https://avatars.githubusercontent.com/in/44061?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/copybara-service%5Bbot%5D",
"html_url": "https://github.com/apps/copybara-service",
"followers_url": "https://api.github.com/users/copybara-service%5Bbot%5D/followers",
"following_url": "https://api.github.com/users/copybara-service%5Bbot%5D/following{/other_user}",
"gists_url": "https://api.github.com/users/copybara-service%5Bbot%5D/gists{/gist_id}",
"starred_url": "https://api.github.com/users/copybara-service%5Bbot%5D/starred{/owner}{/repo}",
"subscriptions_url": "https://api.github.com/users/copybara-service%5Bbot%5D/subscriptions",
"organizations_url": "https://api.github.com/users/copybara-service%5Bbot%5D/orgs",
"repos_url": "https://api.github.com/users/copybara-service%5Bbot%5D/repos",
"events_url": "https://api.github.com/users/copybara-service%5Bbot%5D/events{/privacy}",
"received_events_url": "https://api.github.com/users/copybara-service%5Bbot%5D/received_events",
"type": "Bot",
"site_admin": false
}
|
[] |
closed
| false |
{
"login": "ddunl",
"id": 31703846,
"node_id": "MDQ6VXNlcjMxNzAzODQ2",
"avatar_url": "https://avatars.githubusercontent.com/u/31703846?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/ddunl",
"html_url": "https://github.com/ddunl",
"followers_url": "https://api.github.com/users/ddunl/followers",
"following_url": "https://api.github.com/users/ddunl/following{/other_user}",
"gists_url": "https://api.github.com/users/ddunl/gists{/gist_id}",
"starred_url": "https://api.github.com/users/ddunl/starred{/owner}{/repo}",
"subscriptions_url": "https://api.github.com/users/ddunl/subscriptions",
"organizations_url": "https://api.github.com/users/ddunl/orgs",
"repos_url": "https://api.github.com/users/ddunl/repos",
"events_url": "https://api.github.com/users/ddunl/events{/privacy}",
"received_events_url": "https://api.github.com/users/ddunl/received_events",
"type": "User",
"site_admin": false
}
|
[
{
"login": "ddunl",
"id": 31703846,
"node_id": "MDQ6VXNlcjMxNzAzODQ2",
"avatar_url": "https://avatars.githubusercontent.com/u/31703846?v=4",
"gravatar_id": "",
"url": "https://api.github.com/users/ddunl",
"html_url": "https://github.com/ddunl",
"followers_url": "https://api.github.com/users/ddunl/followers",
"following_url": "https://api.github.com/users/ddunl/following{/other_user}",
"gists_url": "https://api.github.com/users/ddunl/gists{/gist_id}",
"starred_url": "https://api.github.com/users/ddunl/starred{/owner}{/repo}",
"subscriptions_url": "https://api.github.com/users/ddunl/subscriptions",
"organizations_url": "https://api.github.com/users/ddunl/orgs",
"repos_url": "https://api.github.com/users/ddunl/repos",
"events_url": "https://api.github.com/users/ddunl/events{/privacy}",
"received_events_url": "https://api.github.com/users/ddunl/received_events",
"type": "User",
"site_admin": false
}
] | null |
[] | 2024-05-14T22:19:36 | 2024-05-14T23:37:39 | 2024-05-14T23:37:38 |
NONE
| null | true |
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"patch_url": "https://github.com/tensorflow/tensorflow/pull/67592.patch",
"merged_at": "2024-05-14T23:37:39"
}
|
Remove references to unused tags in XLA build script
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