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CONTRIBUTING.md
These are issues that we believe are particularly well suited for outside contributions, often because we probably won't get to them right now. If you decide to start on an issue, leave a comment so that other people know that you're working on it. If you want to help out, but not alone, use the issue comment thread to coordinate.
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
**Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to or attach code demonstrating the problem. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files
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WORKSPACE
# 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. load("@//tensorflow:workspace3.bzl", "tf_workspace3") tf_workspace3()
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tensorflow/c/experimental/ops/README.md
***tensorflow/c/experimental/ops/\*_ops.{cc,h}***. Run this `update_cpp_ops.sh` script when Op definitions change in the registry. To generate additional operators, extend the lists in this script. Note that category names correspond to generated source file names, and should be consistent with the original source files registering each operator. For example since `REGISTER_OP("MatMul")` appears in ***core/math_ops.cc***, the "MatMul"
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tensorflow/c/BUILD
"//tensorflow/compiler/tf2xla:xla_compiler", ], "//conditions:default": [], }) + if_tensorrt([ "//tensorflow/compiler/tf2tensorrt:trt_convert_api", ]), ) # Check that c_api_no_xla does not depend on xla. check_deps( name = "c_api_no_xla_check_deps", disallowed_deps = ["//tensorflow/compiler/jit:xla_kernel_creator"], deps = [":c_api_no_xla"], ) tf_cuda_library(
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SECURITY.md
available to TensorFlow is powerful enough that you should assume that the TensorFlow process effectively executes arbitrary code. The risk of loading untrusted checkpoints depends on the code or graph that you are working with. When loading untrusted checkpoints, the values of the traced variables from your model are also going to be untrusted. That means that if
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LICENSE
"Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the
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CODE_OF_CONDUCT.md
and orientation. ## Our Standards Examples of behavior that contributes to creating a positive environment include: * Using welcoming and inclusive language. * Being respectful of differing viewpoints and experiences. * Gracefully accepting constructive criticism. * Focusing on what is best for the community. * Showing empathy towards other community members.
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ci/official/requirements_updater/requirements.in
dill == 0.3.7 astor == 0.7.1 typing_extensions == 4.8.0 gast == 0.4.0 termcolor == 2.3.0 wrapt == 1.16.0 tblib == 2.0.0 # Install tensorboard, and keras # Note that here we want the latest version that matches TF major.minor version # Note that we must use nightly here as these are used in nightly jobs # For release jobs, we will pin these on the release branch keras-nightly ~= 3.0.0.dev tb-nightly ~= 2.17.0.a
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RELEASE.md
etc.) may break. * Code that uses full path for `get_concrete_function` to trace Keras symbolic inputs directly should switch to building matching `tf.TensorSpec`s directly and tracing the `TensorSpec` objects. * Code that relies on the exact number and names of the op layers that TensorFlow operations were converted into may have changed.
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