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ci/official/utilities/code_check_full.bats
--@local_config_cuda//:enable_cuda \ --define framework_shared_object=false \ "somepath(//tensorflow/tools/pip_package:wheel, " \ "@local_config_cuda//cuda:cudart + "\ "@local_config_cuda//cuda:cudart + "\ "@local_config_cuda//cuda:cuda_driver + "\ "@local_config_cuda//cuda:cudnn + "\ "@local_config_cuda//cuda:curand + "\ "@local_config_cuda//cuda:cusolver + "\
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.bazelrc
build:mkl_aarch64_threadpool -c opt # CUDA: This config refers to building CUDA op kernels with nvcc. build:cuda --repo_env TF_NEED_CUDA=1 build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain build:cuda --@local_config_cuda//:enable_cuda # CUDA: This config refers to building CUDA op kernels with clang. build:cuda_clang --config=cuda # Enable TensorRT optimizations https://developer.nvidia.com/tensorrt
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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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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", ) load("@local_tsl//tsl/platform:rules_cc.bzl", "cc_library")
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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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ci/official/wheel.sh
# limitations under the License. # ============================================================================== source "${BASH_SOURCE%/*}/utilities/setup.sh" # Record GPU count and CUDA version status if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then tfrun nvidia-smi fi # Update the version numbers for Nightly only if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
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docs/pt/docs/python-types.md
```Python first_name="john", last_name="doe" ``` É uma coisa diferente. Estamos usando dois pontos (`:`), não é igual a (`=`). E adicionar type hints normalmente não muda o que acontece do que aconteceria sem elas. Mas agora, imagine que você está novamente no meio da criação dessa função, mas com type hints. No mesmo ponto, você tenta acionar o preenchimento automático com o `Ctrl Space` e vê:
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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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tensorflow/c/c_api_test.cc
TF_DeleteTensor(t); EXPECT_TRUE(deallocator_called); } TEST(CAPI, LibraryLoadFunctions) { // TODO(b/73318067): Fix linking for the GPU test generated by the // tf_cuda_cc_test() bazel rule and remove the next line. if (!GPUDeviceName().empty()) return; #if !defined(TENSORFLOW_NO_SHARED_OBJECTS) { // Load the library. TF_Status* status = TF_NewStatus();
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