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ci/official/README.md
- Continuous jobs (Run on every GitHub commit) - Uses `pycpp.sh` - Presubmit jobs (Run on every GitHub PR) - Uses `pycpp.sh`, `code_check_changed_files.sh` These "env" files match up with an environment matrix that roughly covers: - Different Python versions - Linux, MacOS, and Windows machines (these pool definitions are internal) - x86 and arm64
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tensorflow/c/c_api.cc
#include <algorithm> #include <cstring> #include <limits> #include <memory> #include <optional> #include <unordered_set> #include <utility> #include <vector> #include "absl/strings/match.h" // Required for IS_MOBILE_PLATFORM #include "tensorflow/core/platform/platform.h" // NOLINT #if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD) #include "tensorflow/c/experimental/filesystem/modular_filesystem.h"
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 102.3K bytes - Viewed (0) -
tensorflow/c/eager/dlpack.cc
default: return tensorflow::errors::InvalidArgument("Unsupported Type Codes: ", dtype.code); } } // Wraps the deleter function of DLManagedTensor to match the function signature // TFE_NewTensorHandleFromDeviceMemory. void DeallocatorWrapperFunc(void* data, size_t len, void* dlmt_vptr) { TFE_CallDLManagedTensorDeleter(dlmt_vptr); }
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CONTRIBUTING.md
your changes by running the command: ```bash tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh ``` This will catch most license, Python coding style and BUILD file issues that may exist in your changes. #### Running unit tests There are two ways to run TensorFlow unit tests.
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RELEASE.md
* `tf.data`: * Graduated experimental APIs: * [`tf.data.Dataset.ragged_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ragged_batch), which batches elements of `tf.data.Dataset`s into `tf.RaggedTensor`s. * [`tf.data.Dataset.sparse_batch`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#sparse_batch), which batches elements of `tf.data.Dataset`s into `tf.sparse.SparseTensor`s.
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tensorflow/BUILD
selects.config_setting_group( name = "is_cuda_enabled_and_oss", match_all = [ ":is_cuda_enabled", ":oss", ], ) # Config setting that is satisfied when building with --config=cuda for Windows selects.config_setting_group( name = "is_cuda_enabled_and_windows", match_all = [ ":is_cuda_enabled", ":windows", ], )
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tensorflow/c/eager/c_api_experimental.cc
#include "tensorflow/c/eager/c_api_experimental.h" #include <cstdint> #include <memory> #include <utility> #include <vector> #include "absl/container/flat_hash_map.h" #include "absl/strings/match.h" #include "absl/time/time.h" #include "tensorflow/c/c_api.h" #include "tensorflow/c/eager/c_api_internal.h" #include "tensorflow/c/eager/tfe_context_internal.h" #include "tensorflow/c/eager/tfe_op_internal.h"
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.github/workflows/update-rbe.yml
# metadata. gcr.io helpfully includes it in the header of the response # as docker-content-digest: sha256:[digest]. Note we use egrep to # match exactly sha256:<hash> because curl may include a ^M symbol at # the end of the line. # See https://cloud.google.com/architecture/using-container-images#exploring_image_manifests_digests_and_tags
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configure.py
for compute_capability in tf_cuda_compute_capabilities.split(','): m = re.match('[0-9]+.[0-9]+', compute_capability) if not m: # We now support sm_35,sm_50,sm_60,compute_70. sm_compute_match = re.match('(sm|compute)_?([0-9]+[0-9]+)', compute_capability) if not sm_compute_match: print('Invalid compute capability: %s' % compute_capability)
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.bazelrc
# --incompatible_remove_legacy_whole_archive flag does. # This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate # Tensorflow to the default, however test coverage wasn't enough to catch the # errors. # There is ongoing work on Bazel team's side to provide support for transitive # shared libraries. As part of migrating to transitive shared libraries, we
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