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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=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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ci/official/code_check_full.sh
# limitations under the License. # ============================================================================== source "${BASH_SOURCE%/*}/utilities/setup.sh"
Shell Script - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Feb 06 17:29:44 GMT 2024 - 840 bytes - Viewed (0) -
ci/official/utilities/code_check_changed_files.bats
git diff --diff-filter ACMRT --name-only origin/master > $BATS_FILE_TMPDIR/changed_files fi } # Note: this is excluded on the full code base, since any submitted code must # have passed Google's internal style guidelines. @test "Check buildifier formatting on BUILD files" { echo "buildifier formatting is recommended. Here are the suggested fixes:"
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# Build TensorFlow v2 build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1 # Prevent double-compilation of some TF code, ref. b/183279666 (internal) # > TF's gen_api_init_files has a genrule to run the core TensorFlow code # > on the host machine. If we don't have --distinct_host_configuration=false, # > the core TensorFlow code will be built once for the host and once for the # > target platform.
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tensorflow/c/c_api_test.cc
TEST(CAPI, StatusEnum) { EXPECT_EQ(TF_OK, static_cast<TF_Code>(tensorflow::error::OK)); EXPECT_EQ(TF_CANCELLED, static_cast<TF_Code>(tensorflow::error::CANCELLED)); EXPECT_EQ(TF_UNKNOWN, static_cast<TF_Code>(tensorflow::error::UNKNOWN)); EXPECT_EQ(TF_INVALID_ARGUMENT, static_cast<TF_Code>(absl::StatusCode::kInvalidArgument)); EXPECT_EQ(TF_DEADLINE_EXCEEDED, static_cast<TF_Code>(tensorflow::error::DEADLINE_EXCEEDED));
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 96.9K bytes - Viewed (3) -
tensorflow/c/experimental/gradients/nn_grad_test.cc
status_ = StatusFromTF_Status(status.get()); ASSERT_EQ(errors::OK, status_.code()) << status_.message(); { AbstractContext* ctx_raw = nullptr; status_ = BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw); ASSERT_EQ(errors::OK, status_.code()) << status_.message(); immediate_execution_ctx_.reset(ctx_raw); }
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_testutil.h
absl::Span<AbstractTensorHandle*>)>; // Runs `model` maybe wrapped in a function call op. This can be thought as // being equivalent to the following python code. // // if use_function: // outputs = tf.function(model)(inputs) // else: // outputs = model(inputs) Status RunModel(Model model, AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental_test.cc
protected: void SetUp() override { TF_StatusPtr status(TF_NewStatus()); TF_SetTracingImplementation(std::get<0>(GetParam()), status.get()); Status s = StatusFromTF_Status(status.get()); CHECK_EQ(errors::OK, s.code()) << s.message(); } }; TEST_P(UnifiedCAPI, TestBasicEager) { std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( TF_NewStatus(), TF_DeleteStatus);
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tensorflow/c/eager/c_api_test.cc
} else { // In async mode we expect forwarding to work without releasing the input // handle since by the time the kernel is executed we have released the // handle in the client code. EXPECT_EQ(orig_ptr, TF_TensorData(t)); } } else { if (forward_input) { // Since the input was forwarded, we released the input handle right away
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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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