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ci/official/envs/disk_cache
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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ci/official/envs/public_cache_push
# Sourcing this enables Bazel remote cache (read and write) # Note that "_push" cache configs write to GCS buckets and require # authentication. If you are not a Googler, source "public_cache" to enable the # public read-only cache. # The cache configs are different for MacOS and Linux if [[ $(uname -s) == "Darwin" ]]; then TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache_push" else
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ci/official/README.md
# Ex. macos_arm64 -- arm64 MacOS platform # 3. Add modifiers. Some modifiers for local execution are: # Ex. disk_cache -- Use a local cache # Ex. public_cache -- Use TF's public cache (read-only) # Ex. public_cache_push -- Use TF's public cache (read and write, Googlers only) # Ex. rbe -- Use RBE for faster builds (Googlers only; see below)
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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tensorflow/c/eager/BUILD
"//tensorflow/core/distributed_runtime/rpc:grpc_channel", "//tensorflow/core/distributed_runtime/rpc:grpc_server_lib", "//tensorflow/core/distributed_runtime/rpc:grpc_worker_cache", "//tensorflow/core/distributed_runtime/rpc:grpc_worker_service", "//tensorflow/core/distributed_runtime/rpc:rpc_rendezvous_mgr", "//tensorflow/core/distributed_runtime/rpc/eager:grpc_eager_client",
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ci/official/envs/public_cache
# Sourcing this enables Bazel remote cache (public, read-only) # The cache configs are different for MacOS and Linux if [[ $(uname -s) == "Darwin" ]]; then TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache" else TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_cache"
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RELEASE.md
* NNAPI * Removed deprecated `Interpreter::UseNNAPI(bool)` C++ API. * Use `NnApiDelegate()` and related delegate configuration methods directly. * Replaced the model cache key for models computation algorithm with one guaranteed to be stable across runs. * 16 bits quantization * Added int16x8 support for ABS, REDUCE_MAX and REDUCE_MIN operators.
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tensorflow/c/experimental/filesystem/plugins/gcs/BUILD
deps = [ "//tensorflow/c:env", ], ) cc_library( name = "cleanup", hdrs = ["cleanup.h"], ) cc_library( name = "ram_file_block_cache", srcs = ["ram_file_block_cache.cc"], hdrs = ["ram_file_block_cache.h"], deps = [ ":cleanup", "//tensorflow/c:env", "//tensorflow/c:logging", "//tensorflow/c:tf_status",
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.bazelrc
# Cache pushes are limited to TF's CI system. build:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials # Public cache for macOS builds build:tf_public_macos_cache --remote_cache="https://storage.googleapis.com/tensorflow-macos-bazel-cache/oct2023" --remote_upload_local_results=false
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