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CODE_OF_CONDUCT.md
## Conflict Resolution Conflicts in an open source project can take many forms, from someone having a bad day and using harsh and hurtful language in the issue queue, to more serious instances such as sexist/racist statements or threats of violence, and everything in between.
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ci/official/README.md
1. Creating a PR and observing the presubmit test results 2. Running the CI scripts locally, as explained below 3. **Google employees only**: Google employees can use an internal-only tool called "MLCI" that makes testing more convenient: it can execute any full CI job against a pending change. Search for "MLCI" internally to find it. You may invoke a CI script of your choice by following these instructions: ```bash
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# Can be removed once upb is updated, since a type definition is used within # offset of in the current version of ubp. # See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183. build --copt=-Wno-gnu-offsetof-extensions # Store performance profiling log in the mounted artifact directory. # The profile can be viewed by visiting chrome://tracing in a Chrome browser.
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ci/official/utilities/cleanup_docker.sh
# ============================================================================== cat <<EOF IMPORTANT: These tests ran under docker. This script does not clean up the container for you! You can delete the container with: $ docker rm -f tf You can also execute more commands within the container with e.g.: $ docker exec tf bazel clean $ docker exec -it tf bash EOF
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.github/bot_config.yml
Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below: * Try Google Colab to use TensorFlow. * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install``` to install any other preferred TF version.
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tensorflow/c/experimental/grappler/grappler.h
// https://github.com/tensorflow/community/pull/257/files. // * Note that the API is still under active development and doesn't have // versioning guarantees yet. // * `void* ext` is a free-form field that can be populated by // a plugin in `TP_*` structs or potential future extension points . // // Example usage: // // /* Sample TensorFlow code below, exact implementation might differ. */
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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
``` (You can paste links or attach files by dragging & dropping them below) - Provide links to your updated versions of the above two colab notebooks. - Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model. ``` #### Option B: Paste your code here or provide a link to a custom end-to-end colab ``` (You can paste links or attach files by dragging & dropping them below)
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SECURITY.md
Therefore, if you run a `tf.train.Server` in your network, anybody with access to the network can execute arbitrary code with the privileges of the user running the `tf.train.Server`. ## Untrusted inputs during training and prediction TensorFlow supports a wide range of input data formats. For example it can process images, audio, videos, and text. There are several modules specialized
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ci/official/containers/linux_arm64/cuda.packages.txt
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation libcudnn8=8.9.6.50-1+cuda12.2 libcudnn8-dev=8.9.6.50-1+cuda12.2 # This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image. # For now it ensures that we install at least version 12.3.107 of PTXAS, # since 12.3.103 has a bug.
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tensorflow/c/eager/dlpack_test.cc
TestHandleFromDLPack(status, ctx, {4}, {1}); TestHandleFromDLPack(status, ctx, {4, 3, 2}, {}); TestHandleFromDLPack(status, ctx, {4, 3, 2}, {6, 2, 1}); // Test that dims with size=1 can have any stride. TestHandleFromDLPack(status, ctx, {1}, {1}); TestHandleFromDLPack(status, ctx, {1}, {0}); TestHandleFromDLPack(status, ctx, {4, 1, 2}, {2, 1, 1}); TestHandleFromDLPack(status, ctx, {4, 1, 2}, {2, 0, 1});
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