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ISSUES.md
If you open a GitHub Issue, here is our policy: 1. It must be a bug/performance issue or a feature request or a build issue or a documentation issue (for small doc fixes please send a PR instead). 1. Make sure the Issue Template is filled out. 1. The issue should be related to the repo it is created in. **Here's why we have this policy:** We want to focus on the work that benefits the whole community, e.g., fixing bugs and adding features. Individual support
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tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem_helper.cc
off_t size) { int src_fd = open(src, O_RDONLY); if (src_fd < 0) return -1; // When creating file, use the same permissions as original mode_t open_mode = mode & (S_IRWXU | S_IRWXG | S_IRWXO); // O_WRONLY | O_CREAT | O_TRUNC: // Open file for write and if file does not exist, create the file. // If file exists, truncate its size to 0. int dst_fd = open(dst, O_WRONLY | O_CREAT | O_TRUNC, open_mode);
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tensorflow/c/experimental/filesystem/plugins/gcs/gcs_helper.cc
std::remove(name_.c_str()); } const std::string TempFile::getName() const { return name_; } bool TempFile::truncate() { std::fstream::close(); std::fstream::open(name_, std::ios::binary | std::ios::out); return std::fstream::is_open();
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CODE_OF_CONDUCT.md
# TensorFlow Code of Conduct In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to make participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation. ## Our Standards
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.zenodo.json
{ "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.", "license": "Apache-2.0", "title": "TensorFlow", "upload_type": "software", "creators": [ { "name": "TensorFlow Developers" }
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tensorflow/BUILD
selects.config_setting_group( name = "is_cuda_enabled_and_windows", match_all = [ ":is_cuda_enabled", ":windows", ], ) # Config setting to use in select()s to distinguish open source build from # google internal build on configurable attributes. # # For non-configurable distinction between OSS and Google builds, see # `if_oss()` and `if_google()` macros in tensorflow.bzl. config_setting(
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tensorflow/c/experimental/filesystem/plugins/gcs/gcs_filesystem.cc
delete gcs_file; } void Append(const TF_WritableFile* file, const char* buffer, size_t n, TF_Status* status) { auto gcs_file = static_cast<GCSFile*>(file->plugin_file); if (!gcs_file->outfile.is_open()) { TF_SetStatus(status, TF_FAILED_PRECONDITION, "The internal temporary file is not writable."); return; } TF_VLog(3, "Append: gs://%s/%s size %u", gcs_file->bucket.c_str(),
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RELEASE.md
- It could also be a simple python or TF utility that you could easily copy over to your own codebase. In those case, just make it your own! - If you believe it should definitely be a public Keras API, please open a feature request in keras GitHub repo. - As a workaround, you could import the same private symbol keras `keras.src`, but keep in mind the `src` namespace is not stable and those APIs may change or be removed in the future.
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.github/workflows/stale-issues.yml
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ci/official/wheel_test/test_import_api_packages.py
api_packages_path = pkg_resources.resource_filename( "tensorflow", "_api/v2/api_packages.txt" ) logging.info("Load api packages file: %s", api_packages_path) with open(api_packages_path) as file: return set(file.read().splitlines()) super().setUp() self.api_packages_v2 = _get_api_packages_v2() # Some paths in the api_packages_path file cannot be directly imported.
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