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Update README\RELEASE.md for 2.38.0/23.09 (#6357)
* Update README\RELEASE.md for 2.38.0/23.09 * Revert Windows changes
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| <!-- | ||
| # Copyright 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved. | ||
| # | ||
| # Redistribution and use in source and binary forms, with or without | ||
| # modification, are permitted provided that the following conditions | ||
| # are met: | ||
| # * Redistributions of source code must retain the above copyright | ||
| # notice, this list of conditions and the following disclaimer. | ||
| # * Redistributions in binary form must reproduce the above copyright | ||
| # notice, this list of conditions and the following disclaimer in the | ||
| # documentation and/or other materials provided with the distribution. | ||
| # * Neither the name of NVIDIA CORPORATION nor the names of its | ||
| # contributors may be used to endorse or promote products derived | ||
| # from this software without specific prior written permission. | ||
| # | ||
| # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY | ||
| # EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | ||
| # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR | ||
| # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR | ||
| # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, | ||
| # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, | ||
| # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR | ||
| # PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY | ||
| # OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
| # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE | ||
| # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
| --> | ||
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| # Release Notes for 2.38.0 | ||
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| ## New Freatures and Improvements | ||
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| * Triton now has Python bindings for the C API. Please refer to | ||
| [this PR](https://github.com/triton-inference-server/core/pull/265) for | ||
| usage. | ||
|
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| * Triton now forwards request parameters to each of the composing models of an | ||
| ensemble model. | ||
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| * The Filesystem API now supports named temporary cache directories when | ||
| downloading models using the repository agent. | ||
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| * Added the number of requests currently in the queue to the metrics API. | ||
| Documentation can be found | ||
| [here](https://github.com/triton-inference-server/server/blob/r23.09/docs/user_guide/metrics.md#pending-request-count-queue-size-per-model). | ||
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| * Python backend models can now respond with error codes in addition to error | ||
| messages. | ||
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| * TensorRT backend now supports | ||
| [TensortRT version compatibility](https://github.com/triton-inference-server/tensorrt_backend/tree/r23.09#command-line-options) | ||
| across models generated with the same major version of TensorRT. Use the | ||
| `--backend-config=tensorrt,--version-compatible=true` flag to enable this | ||
| feature. | ||
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| * Triton’s backend API now supports accessing the inference response outputs by | ||
| name or by index. See the new API | ||
| [here](https://github.com/triton-inference-server/core/blob/r23.09/include/triton/core/tritonbackend.h#L1572-L1608). | ||
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| * The Python backend now supports loading | ||
| [Pytorch models directly](https://github.com/triton-inference-server/python_backend/tree/r23.08#pytorch-platform-experimental). | ||
| This feature is experimental and should be treated as Beta. | ||
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| * Fixed an issue where if the user didn't call `SetResponseReleaseCallback`, | ||
| canceling a new request could cancel the old response factory as well. Now | ||
| when canceling a request which is being re-used, a new response factory is | ||
| created for each inference. | ||
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| * Refer to the 23.09 column of the | ||
| [Frameworks Support Matrix](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html) | ||
| for container image versions on which the 23.09 inference server container is | ||
| based. | ||
|
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| ## Known Issues | ||
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| * When using decoupled models, there is a possibility that response order as | ||
| sent from the backend may not match with the order in which these responses | ||
| are received by the streaming gRPC client. Note that this only applies to | ||
| responses from different requests. Any responses corresponding to the same | ||
| request will still be received in their expected order, relative to each | ||
| other. | ||
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| * The FasterTransformer backend is only officially supported for 22.12, though | ||
| it can be built for Triton container versions up to 23.07. | ||
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| * The Java CAPI is known to have intermittent segfaults we’re looking for a | ||
| root cause. | ||
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| * Some systems which implement `malloc()` may not release memory back to the | ||
| operating system right away causing a false memory leak. This can be mitigated | ||
| by using a different malloc implementation. Tcmalloc and jemalloc are | ||
| installed in the Triton container and can be | ||
| [used by specifying the library in LD_PRELOAD](https://github.com/triton-inference-server/server/blob/r22.12/docs/user_guide/model_management.md). | ||
| We recommend experimenting with both `tcmalloc` and `jemalloc` to determine | ||
| which one works better for your use case. | ||
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| * Auto-complete may cause an increase in server start time. To avoid a start | ||
| time increase, users can provide the full model configuration and launch the | ||
| server with `--disable-auto-complete-config`. | ||
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| * Auto-complete does not support PyTorch models due to lack of metadata in the | ||
| model. It can only verify that the number of inputs and the input names | ||
| matches what is specified in the model configuration. There is no model | ||
| metadata about the number of outputs and datatypes. Related PyTorch bug: | ||
| https://github.com/pytorch/pytorch/issues/38273 | ||
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| * Triton Client PIP wheels for ARM SBSA are not available from PyPI and pip | ||
| will install an incorrect Jetson version of Triton Client library for Arm | ||
| SBSA. The correct client wheel file can be pulled directly from the Arm SBSA | ||
| SDK image and manually installed. | ||
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| * Traced models in PyTorch seem to create overflows when int8 tensor values are | ||
| transformed to int32 on the GPU. Refer to | ||
| https://github.com/pytorch/pytorch/issues/66930 for more information. | ||
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| * Triton cannot retrieve GPU metrics with MIG-enabled GPU devices (A100 and A30). | ||
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| * Triton metrics might not work if the host machine is running a separate DCGM | ||
| agent on bare-metal or in a container. | ||
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| * When cloud storage (AWS, GCS, AZURE) is used as a model repository and a model | ||
| has multiple versions, Triton creates an extra local copy of the cloud model’s | ||
| folder in the temporary directory, which is deleted upon server’s shutdown. |