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ci/official/debug_tfci.sh
# See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # This script dumps some information about the environment. It's most useful # for verifying changes to the TFCI scripts system, and most users won't need # to interact with it at all. source "${BASH_SOURCE%/*}/utilities/setup.sh"
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CONTRIBUTING.md
#### Debug builds When [building Tensorflow](https://www.tensorflow.org/install/source), passing `--config=dbg` to Bazel will build with debugging information and without optimizations, allowing you to use GDB or other debuggers to debug C++ code. For example, you can build the pip package with debugging information by running: ```bash bazel build --config=dbg //tensorflow/tools/pip_package:build_pip_package ```
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tensorflow/api_template_v1.__init__.py
_current_module.__path__ = [_module_dir] + _current_module.__path__ _CONTRIB_WARNING = """ The TensorFlow contrib module will not be included in TensorFlow 2.0. For more information, please see: * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md * https://github.com/tensorflow/addons * https://github.com/tensorflow/io (for I/O related ops)
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SECURITY.md
### Reporting process Please use [Google Bug Hunters reporting form](https://g.co/vulnz) to report security vulnerabilities. Please include the following information along with your report: - A descriptive title - Your name and affiliation (if any). - A description of the technical details of the vulnerabilities.
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tensorflow/c/eager/c_api_experimental.h
TF_Status* status, void* device_info); // Method to execute an operation. // // Arguments provide enough information to reconstruct the original `TFE_Op`, // or construct a transformed version, by inspecting the passed `op`. // // TFE_OpGetDevice(op) records the original placement of the operation. It may
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
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tensorflow/c/c_api.cc
size_t proto_len, TF_Status* status) { // shape.ParseFromArray takes an int as length, this function takes size_t, // make sure there is no information loss. if (proto_len > std::numeric_limits<int>::max()) { status->status = InvalidArgument( "proto_len (", proto_len, " bytes) is too large to be parsed by the protocol buffer library");
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RELEASE.md
validates TFLite compatibility. If an incompatible operation is encountered during execution, an exception will be raised with information about the incompatible ops. * Add lite.experimental.Analyzer API * An experimental tool to analyze TFLite flatbuffer models. This API can be used to investigate TFLite model structure and check
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tensorflow/c/c_api_experimental.cc
std::vector<const Tensor*> input_tensors_vector(num_inputs, nullptr); // A vector to keep track of newly created `tf::Tensor` objects. std::vector<Tensor> all_input_tensors; // Update the vector with information from `input_tensors` if provided. if (input_tensors != nullptr) { // Note that we take the address of the elements in `all_input_tensors` // below. Allocate enough space so that no reallocation happens, which will
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tensorflow/c/c_api.h
// Conventions: // * We use the prefix TF_ for everything in the API. // * Objects are always passed around as pointers to opaque structs // and these structs are allocated/deallocated via the API. // * TF_Status holds error information. It is an object type // and therefore is passed around as a pointer to an opaque // struct as mentioned above. // * Every call that has a TF_Status* argument clears it on success
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