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CONTRIBUTING.md
bazel by doing as follows: ```bash 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" ```
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tensorflow/c/BUILD
"//tensorflow/core:lib_internal", "//tensorflow/core:op_gen_lib", "//tensorflow/core:protos_all_cc", "//tensorflow/core/config:flag_defs", "//tensorflow/core/config:flags", "//tensorflow/core/distributed_runtime:server_lib", "//tensorflow/core/kernels:logging_ops", "@com_google_absl//absl/strings", ], }),
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tensorflow/c/eager/BUILD
hdrs = ["tape.h"], visibility = ["//tensorflow:internal"], deps = [ "//tensorflow/core:framework", "//tensorflow/core:lib", "//tensorflow/core/config:flag_defs", "//tensorflow/core/config:flags", ], ) filegroup( name = "headers", srcs = [ "c_api.h", "c_api_experimental.h", "dlpack.h", ],
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tensorflow/c/c_api_experimental.cc
// These XLA flags are needed to trigger XLA properly from C (more generally // non-Python) clients. If this API is called again with `enable` set to // false, it is safe to keep these flag values as is. tensorflow::MarkForCompilationPassFlags* flags = tensorflow::GetMarkForCompilationPassFlags(); flags->tf_xla_cpu_global_jit = true; flags->tf_xla_min_cluster_size = 1; } else {
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tensorflow/c/eager/tape.h
// maintains the data structures required to do so. #include <stack> #include <unordered_map> #include <unordered_set> #include <vector> #include "tensorflow/core/config/flag_defs.h" #include "tensorflow/core/config/flags.h" #include "tensorflow/core/framework/tensor_shape.h" #include "tensorflow/core/framework/types.h" #include "tensorflow/core/lib/gtl/array_slice.h" #include "tensorflow/core/lib/gtl/cleanup.h"
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 02 12:40:29 GMT 2024 - 47.2K bytes - Viewed (1)