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tensorflow/c/eager/c_api_unified_experimental.cc
} // end namespace tensorflow // ============================================================================= // Public C API entry points // // These are only the generic entry points for the C API. This file does not // have any visibility into the graph/eager implementation and is only providing // C bindings to the abstract classes defined in the // c_api_unified_experimental_internal.h header. //
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tensorflow/c/c_api.cc
"ApiDefMap is not supported on mobile."); return nullptr; #else mutex_lock l(api_def_map->lock); if (!api_def_map->update_docs_called) { api_def_map->api_def_map.UpdateDocs(); api_def_map->update_docs_called = true; } string name_str(name, name_len); const auto* api_def = api_def_map->api_def_map.GetApiDef(name_str); if (api_def == nullptr) {
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.github/bot_config.yml
*TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.* Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load. Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below: * Try Google Colab to use TensorFlow.
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Oct 17 11:48:07 GMT 2023 - 4K bytes - Viewed (0) -
CODEOWNERS
/tensorflow/core/kernels/sparse/ @penpornk /tensorflow/core/nccl/ @azaks2 @chsigg /tensorflow/python/autograph/ @mdanatg /tensorflow/python/debug @caisq /tensorflow/python/eager @rohan100jain /tensorflow/tools/docs/ @markdaoust /tensorflow/compiler/mlir/ @aminim /tensorflow/core/ir/ @aminim /tensorflow/core/transforms/ @aminim
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tensorflow/api_template_v1.__init__.py
# Delete modules that should be hidden from dir(). # Don't fail if these modules are not available. # For e.g. this file will be originally placed under tensorflow/_api/v1 which # does not have "python", "core" directories. Then, it will be copied # to tensorflow/ which does have these two directories. try: del python except NameError: pass try: del core except NameError: pass try: del compiler
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Jan 23 02:14:00 GMT 2024 - 7.4K bytes - Viewed (0) -
ci/official/utilities/cleanup_docker.sh
# limitations under the License. # ============================================================================== cat <<EOF IMPORTANT: These tests ran under docker. This script does not clean up the container for you! You can delete the container with: $ docker rm -f tf You can also execute more commands within the container with e.g.: $ docker exec tf bazel clean $ docker exec -it tf bash
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 10 20:26:29 GMT 2023 - 998 bytes - Viewed (0) -
tensorflow/c/eager/c_api.h
int num_inputs, TF_Status* status); // Fetches the current number of inputs attached to `op`. // // Does not use the operation's definition to determine how many inputs should // be attached. It is intended for use with TFE_OpGetFlatInput to inspect an // already-finalized operation. //
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CONTRIBUTING.md
Once you are setup to build from source, you can run the tests: ```bash bazel run //tensorflow/tools/docs:tf_doctest ``` or ```bash bazel run //tensorflow/tools/docs:tf_doctest -- --module=ops.array_ops ``` The `--module` is relative to `tensorflow.python`. #### Debug builds
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tensorflow/c/eager/c_api_experimental.h
// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This // is for performance optimization by reusing an exiting unused op rather than // creating a new op every time. If `raw_device_name` is `NULL` or empty, it // does not set the device name. If it's not `NULL`, then it attempts to parse // and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster // than separately calling it because if the existing op has the same
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ci/official/README.md
# generated artifacts like .whl files, and "script.log", from the script. # Note that files created under Docker will be owned by "root". ls build_output ``` ## Contribution & Maintenance The TensorFlow team does not yet have guidelines in place for contributing to this directory. We are working on it. Please join a TF SIG Build meeting (see: bit.ly/tf-sig-build-notes) if you'd like to discuss the future of contributions.
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