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ci/official/containers/linux_arm64/cuda.packages.txt
libcudnn8=8.9.6.50-1+cuda12.2 libcudnn8-dev=8.9.6.50-1+cuda12.2 # This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image. # For now it ensures that we install at least version 12.3.107 of PTXAS, # since 12.3.103 has a bug.
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tensorflow/c/BUILD
load( "//tensorflow:tensorflow.bzl", "check_deps", "if_google", "if_not_mobile", "tf_cc_test", "tf_copts", "tf_cuda_library", "tf_custom_op_library", "tf_kernel_library", ) load("//tensorflow:tensorflow.default.bzl", "filegroup", "tf_cuda_cc_test") load( "//tensorflow/core/tpu:build_defs.bzl", "if_libtpu_tf_status", ) package(
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ci/official/README.md
# build. This should also match the system you're using--you cannot build # the TF MacOS package from Linux. # Ex. linux_x86 -- x86_64 Linux platform # Ex. linux_x86_cuda -- x86_64 Linux platform, with Nvidia CUDA support # Ex. macos_arm64 -- arm64 MacOS platform # 3. Add modifiers. Some modifiers for local execution are: # Ex. disk_cache -- Use a local cache
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CONTRIBUTING.md
export flags="--config=opt -k" ``` If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and add the `cuda` option flag ```bash export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH" export flags="--config=opt --config=cuda -k" ``` For example, to run all tests under tensorflow/python, do: ```bash
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src/main/resources/fess_indices/fess/id/stopwords.txt
berapa berapakah berapalah berapapun betulkah sebetulnya biasa biasanya bila bilakah bisa bisakah sebisanya boleh bolehkah bolehlah buat bukan bukankah bukanlah bukannya cuma percuma dahulu dalam dan dapat dari daripada dekat demi demikian demikianlah sedemikian dengan depan di dia dialah dini diri dirinya terdiri dong
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tensorflow/BUILD
# Config setting that is satisfied when TensorFlow is being built with CUDA # support through e.g. `--config=cuda` (or `--config=cuda_clang` in OSS). alias( name = "is_cuda_enabled", actual = if_oss( "@local_config_cuda//:is_cuda_enabled", "@local_config_cuda//cuda:using_clang", ), ) # Config setting that is satisfied when CUDA device code should be compiled
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tensorflow/c/eager/BUILD
load( "//tensorflow:tensorflow.bzl", "tf_cc_test", "tf_copts", "tf_cuda_cc_test", "tf_cuda_library", ) load("//tensorflow:tensorflow.default.bzl", "cc_header_only_library", "filegroup") load( "//tensorflow/core/platform:build_config_root.bzl", "tf_cuda_tests_tags", ) load("//tensorflow/core/platform:rules_cc.bzl", "cc_library") package(
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ci/official/envs/linux_x86_cuda
source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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RELEASE.md
* Move `layers_dense_variational_impl.py` to `layers_dense_variational.py`. ## Known Bugs * Using XLA:GPU with CUDA 9 and CUDA 9.1 results in garbage results and/or `CUDA_ILLEGAL_ADDRESS` failures. Google discovered in mid-December 2017 that the PTX-to-SASS compiler in CUDA 9 and CUDA 9.1 sometimes does not properly compute the carry bit when
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CREDITS
github.com/pkg/xattr https://github.com/pkg/xattr ---------------------------------------------------------------- Copyright (c) 2012 Dave Cheney. All rights reserved. Copyright (c) 2014 Kuba Podgórski. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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