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WORKSPACE
) load("@pypi//:requirements.bzl", "install_deps") install_deps() # Initialize the TensorFlow repository and all dependencies. # # The cascade of load() statements and tf_workspace?() calls works around the # restriction that load() statements need to be at the top of .bzl files. # E.g. we can not retrieve a new repository with http_archive and then load() # a macro from that repository in the same file.
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ci/official/containers/linux_arm64/devel.usertools/repack_libtensorflow.sh
# under the root of srcjars jars created by bazel, rather than under # the maven-style src/main/java subdirectory. # # Bazel manages annotation generated source as follows: First, it # calls javac with options that create generated files under a # bazel-out directory. Next, it archives the generated source files # into a srcjar directly under the root. There doesn't appear to be a
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.github/workflows/stale-issues.yml
#Comma separated list of labels that can be assigned to PRs to exclude them from being marked as stale exempt-pr-labels: "override-stale" #Limit the No. of API calls in one run default value is 30. operations-per-run: 1000 days-before-issue-stale: 7 days-before-issue-close: 7 stale-issue-label: "stale"
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ci/official/utilities/repack_libtensorflow.sh
# under the root of srcjars jars created by bazel, rather than under # the maven-style src/main/java subdirectory. # # Bazel manages annotation generated source as follows: First, it # calls javac with options that create generated files under a # bazel-out directory. Next, it archives the generated source files # into a srcjar directly under the root. There doesn't appear to be a
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