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.gitignore
*.pbxproj *.xcworkspace /*.podspec /tensorflow/lite/**/coreml/**/BUILD /tensorflow/lite/**/ios/BUILD /tensorflow/lite/**/objc/BUILD /tensorflow/lite/**/swift/BUILD /tensorflow/lite/examples/ios/simple/data/*.tflite /tensorflow/lite/examples/ios/simple/data/*.txt Podfile.lock Pods
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ci/official/README.md
# variables in between script executions. To forcibly remove the # container and start fresh, run "docker rm -f tf". Removing the container # destroys some temporary bazel data and causes longer builds. # # You will need the NVIDIA Container Toolkit for GPU testing: # https://github.com/NVIDIA/nvidia-container-toolkit # # Note: if you interrupt a bazel command on docker (ctrl-c), you
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tensorflow/c/BUILD
] + if_not_mobile([ "//tensorflow/core/kernels:tensor_list", "//tensorflow/core/kernels:tensor_list_util", "//tensorflow/core/kernels:variant_ops_util", "//tensorflow/core/kernels/data:optional_ops_util", "//tensorflow/core/platform:abi", ]), alwayslink = 1, ) tf_cuda_library( name = "ops", srcs = [ "ops.cc", ], hdrs = [
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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
"//tensorflow/core/config:flag_defs", "//tensorflow/core/config:flags", "//tensorflow/core/data/service:dispatcher_client", "//tensorflow/core/data/service:grpc_util", "//tensorflow/core/data/service:py_utils", "//tensorflow/core/data/service:server_lib", "//tensorflow/core/debug", "//tensorflow/core/distributed_runtime:server_lib",
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requirements_lock_3_11.txt
tblib==2.0.0 \ --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \ --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7 # via -r requirements.in tensorboard-data-server==0.7.2 \ --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \ --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
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requirements_lock_3_10.txt
tblib==2.0.0 \ --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \ --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7 # via -r requirements.in tensorboard-data-server==0.7.2 \ --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \ --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
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.bazelrc
build:windows --host_copt=/d2ReducedOptimizeHugeFunctions # Enable the runfiles symlink tree on Windows. This makes it possible to build # the pip package on Windows without an intermediate data-file archive, as the # build_pip_package script in its current form (as of Aug 2023) uses the # runfiles symlink tree to decide what to put into the Python wheel. startup --windows_enable_symlinks
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ci/official/envs/macos_x86
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-x86_64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/System/Volumes/Data/bazel_output" TFCI_MACOS_INSTALL_BAZELISK_ENABLE=1 TFCI_MACOS_INSTALL_BAZELISK_URL="https://github.com/bazelbuild/bazelisk/releases/download/v1.11.0/bazelisk-darwin-amd64" TFCI_MACOS_TWINE_INSTALL_ENABLE=1
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requirements_lock_3_12.txt
tblib==2.0.0 \ --hash=sha256:9100bfa016b047d5b980d66e7efed952fbd20bd85b56110aaf473cb97d18709a \ --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7 # via -r requirements.in tensorboard-data-server==0.7.2 \ --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \ --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \
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