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ci/official/utilities/get_versions.sh
# where fields are strings separated by whitespace. export TF_VER_MAJOR=$(awk '/#define TF_MAJOR_VERSION/ {print $3}' tensorflow/core/public/version.h) export TF_VER_MINOR=$(awk '/#define TF_MINOR_VERSION/ {print $3}' tensorflow/core/public/version.h) export TF_VER_PATCH=$(awk '/#define TF_PATCH_VERSION/ {print $3}' tensorflow/core/public/version.h) # Note: in awk, "print $N" prints the Nth "field", where fields are strings separated
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jan 10 19:39:41 GMT 2024 - 2.3K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/nn_grad_test.cc
absl::Span<AbstractTensorHandle*> outputs) { return ops::BiasAdd(ctx, inputs[0], inputs[1], &outputs[0], "NHWC", "BiasAdd"); } class CppGradients : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> { protected: void SetUp() override { TF_StatusPtr status(TF_NewStatus()); TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
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ci/official/bisect.sh
Shell Script - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Thu Feb 01 03:21:19 GMT 2024 - 1.8K bytes - Viewed (0) -
ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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tensorflow/c/c_api_test.cc
EXPECT_EQ("New summary", api_def.summary()); TF_DeleteBuffer(api_def_buf); TF_DeleteApiDefMap(api_def_map); TF_DeleteBuffer(op_list_buf); } class DummyKernel : public tensorflow::OpKernel { public: explicit DummyKernel(tensorflow::OpKernelConstruction* context) : OpKernel(context) {} void Compute(tensorflow::OpKernelContext* context) override {} };
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ci/official/envs/public_cache_push
# authentication. If you are not a Googler, source "public_cache" to enable the # public read-only cache. # The cache configs are different for MacOS and Linux if [[ $(uname -s) == "Darwin" ]]; then TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache_push" else TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_cache_push"
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tensorflow/c/experimental/gradients/nn_grad.cc
using tensorflow::ops::BiasAddGrad; using tensorflow::ops::Mul; using tensorflow::ops::ReluGrad; namespace tensorflow { namespace gradients { namespace { class ReluGradientFunction : public GradientFunction { public: explicit ReluGradientFunction(vector<AbstractTensorHandle*> f_outputs) : forward_outputs_(f_outputs) { for (auto output : forward_outputs_) { if (output) { output->Ref(); }
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tensorflow/c/eager/graph_function.h
#include "tensorflow/core/platform/refcount.h" namespace tensorflow { namespace tracing { namespace graph { using tensorflow::AbstractFunction; // Thin wrapper around a FunctionDef. class GraphFunction : public AbstractFunction { public: explicit GraphFunction(FunctionDef fdef); ~GraphFunction() override; // GraphFunction maybe stay alive for the duration of the returned // FunctionDef.
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ci/official/containers/linux_arm64/cuda.packages.txt
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation 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/eager/immediate_execution_distributed_manager.h
class CoordinationServiceAgent; } namespace tensorflow { class ImmediateExecutionContext; class ServerDef; class WorkerEnv; class WorkerCacheInterface; class ImmediateExecutionDistributedManager { public: virtual ~ImmediateExecutionDistributedManager() {} // Set up distributed execution environment on local and remote tasks. // When `reset_context` is true, initialize new cluster context state based
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