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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
// only once. Hence, this function keeping another static pointer to a vector // which contains only the schemes under test. // // Without this additional step, when there are schemes available but the user // only requests schemes that don't exist, first instantiation of the test would // filter out all the user provided schemes (as they are not registered) but
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# Find all one-step dependencies of those tests which are from //tensorflow # (since external deps will come from Python-level pip dependencies), # excluding dependencies and files that are known to be unneccessary.
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.github/workflows/arm-ci.yml
strategy: matrix: pyver: ['3.10'] steps: - name: Stop old running containers (if any) shell: bash run: | running_containers=$(docker ps -q) && \ if [[ $running_containers == "" ]]; then echo "No running containers"; else echo "Running container(s) found" && \ docker stop $running_containers; fi
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ci/official/utilities/code_check_full.bats
# Find all one-step dependencies of those tests which are from //tensorflow # (since external deps will come from Python-level pip dependencies), # excluding dependencies and files that are known to be unneccessary.
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ci/official/wheel_test/README.md
[requirements updater readme](https://github.com/tensorflow/tensorflow/blob/master/ci/official/requirements_updater/README.md) ### Prerequisites for Local Testing To run tests locally, follow these steps: 1. Navigate to the relevant directory: ``` cd ci/official/wheel_test ``` 2. Run a script for creating requirements file: ```
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.github/workflows/issue-on-pr-rollback.yml
contents: read issues: write pull-requests: read if: | github.repository == 'tensorflow/tensorflow' && startsWith(github.event.head_commit.message, 'Rollback of PR #') steps: - name: Checkout repo uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0 - name: Create a new Github Issue
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tensorflow/c/experimental/filesystem/plugins/posix/copy_file_portable.cc
std::unique_ptr<char[]> buffer(new char[kPosixCopyFileBufferSize]); off_t offset = 0; int bytes_transferred = 0; int rc = 1; // When `sendfile` returns 0 we stop copying and let callers handle this. while (offset < size && rc > 0) { size_t chunk = size - offset; if (chunk > kPosixCopyFileBufferSize) chunk = kPosixCopyFileBufferSize;
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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.cc
return true; } size_t RamFileBlockCache::CacheSize() const { absl::MutexLock lock(&mu_); return cache_size_; } void RamFileBlockCache::Prune() { while (!stop_pruning_thread_.WaitForNotificationWithTimeout( absl::Microseconds(1000000))) { absl::MutexLock lock(&mu_); uint64_t now = timer_seconds_(); while (!lra_list_.empty()) {
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Jul 16 01:39:09 GMT 2020 - 11.1K bytes - Viewed (0) -
RELEASE.md
`(batch_size, 1)`. This enables `Model` subclasses to process scalar data in their `train_step()`/`test_step()`/`predict_step()` methods. \ Note that this change may break certain subclassed models. You can revert back to the previous behavior by adding upranking yourself in the `train_step()`/`test_step()`/`predict_step()` methods, e.g. `if x.shape.rank == 1: x = tf.expand_dims(x, axis=-1)`. Functional models as
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.github/workflows/arm-ci-extended-cpp.yml
strategy: matrix: pyver: ['3.10'] steps: - name: Stop old running containers (if any) shell: bash run: | running_containers=$(docker ps -q) && \ if [[ $running_containers == "" ]]; then echo "No running containers"; else echo "Running container(s) found" && \ docker stop $running_containers; fi
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