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tensorflow/c/BUILD
deps = [ ":c_api", ":c_api_experimental", ":env", ":kernels", ], ) tf_cuda_cc_test( name = "c_api_test", size = "medium", srcs = ["c_api_test.cc"], data = [ ":test_op1.so", "//tensorflow/cc/saved_model:saved_model_half_plus_two", ], linkopts = select({
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.bazelrc
# Load rc file with user-specific options. try-import %workspace%/.bazelrc.user # Here are bazelrc configs for release builds # Build TensorFlow v2. test:release_base --test_size_filters=small,medium # Ensure release_base is set on linux build:release_linux_base --config=release_base # Target the AVX instruction set build:release_linux_base --config=avx_linux # Enable support for all targets
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tensorflow/c/eager/BUILD
"//tensorflow/core:lib", "//tensorflow/core:protos_all_cc", "//tensorflow/core:test", ], ) tf_cuda_cc_test( name = "c_api_test", size = "medium", srcs = [ "c_api_debug_test.cc", "c_api_test.cc", ], tags = [ "no_cuda_asan", # TODO(b/181771536) "guitar", # "multi_gpu", b/180748118 ],
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configure.py
write_to_bazelrc('build --config=cuda') def system_specific_test_config(environ_cp): """Add default build and test flags required for TF tests to bazelrc.""" write_to_bazelrc('test --test_size_filters=small,medium') # Each instance of --test_tag_filters or --build_tag_filters overrides all # previous instances, so we need to build up a complete list and write a # single list of filters for the .bazelrc file.
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RELEASE.md
([Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html) and newer CPUs.) * [Example performance speedups.](https://medium.com/intel-analytics-software/leverage-intel-deep-learning-optimizations-in-tensorflow-129faa80ee07) * For older CPUs, oneDNN optimizations are disabled by default.
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