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tensorflow/c/c_api_test.cc
TF_DeviceList* device_list = list.get(); CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); const int num_devices = TF_DeviceListCount(device_list); LOG(INFO) << "There are " << num_devices << " devices."; for (int i = 0; i < num_devices; ++i) { const char* device_name = TF_DeviceListName(device_list, i, s); CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
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) -
.bazelrc
# Debug config build:dbg -c dbg # Only include debug info for files under tensorflow/, excluding kernels, to # reduce the size of the debug info in the binary. This is because if the debug # sections in the ELF binary are too large, errors can occur. See # https://github.com/tensorflow/tensorflow/issues/48919. # Users can still include debug info for a specific kernel, e.g. with:
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Thu May 02 19:34:20 GMT 2024 - 52.8K bytes - Viewed (2) -
tensorflow/BUILD
) config_setting( name = "with_xla_support", define_values = {"with_xla_support": "true"}, visibility = ["//visibility:public"], ) # By default, XLA GPU is compiled into tensorflow when building with # --config=cuda even when `with_xla_support` is false. The config setting # here allows us to override the behavior if needed. config_setting( name = "no_xla_deps_in_cuda",
Plain Text - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 09 18:15:11 GMT 2024 - 53.4K bytes - Viewed (8) -
configure.py
# Get the linker version ld_version = run_shell([gcc_env, '-Wl,-version']).split() ld_version_int = convert_version_to_int(ld_version[3]) if ld_version_int is None: ld_version_int = convert_version_to_int(ld_version[4]) # Enable if 'ld' version >= 2.35 if ld_version_int >= 2035000: write_to_bazelrc( 'build --copt="-DEIGEN_ALTIVEC_ENABLE_MMA_DYNAMIC_DISPATCH=1"')
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1)