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.github/ISSUE_TEMPLATE/tflite-other.md
us what you see! value: "A bug happened!" render: shell validations: required: true - type: textarea id: code-to-reproduce attributes: label: Standalone code to reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
if possible): - TensorFlow Lite in Play Services SDK version (found in `build.gradle`): - Google Play Services version (`Settings` > `Apps` > `Google Play Services` > `App details`): **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.
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ci/official/requirements_updater/README.md
export TF_PYTHON_VERSION=3.11 ``` To specify the version via a Bazel command argument, use the following: ``` --repo_env=TF_PYTHON_VERSION=3.11 ``` ## Requirements updater Requirements updater is a standalone tool, intended to simplify process of updating requirements for multiple minor versions of Python. It takes in a file with a set of dependencies, and produces a more detailed
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.github/ISSUE_TEMPLATE/tflite-op-request.md
- TensorFlow installed from (source or binary): - TensorFlow version (or github SHA if from source): **Provide the text output from tflite_convert** ``` # Copy and paste here ``` **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 Colab/Jupyter/any notebook.
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
placeholder: Tell us what you see! validations: required: true - type: textarea id: code-to-reproduce attributes: label: Standalone code to reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. Please share a link to Colab, Jupyter, or any notebook.
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.bazelrc
# rbe_base: General RBE options shared by all flavors. # rbe_linux: General RBE options used on all linux builds. # rbe_win_base: General RBE options used on all Windows builds. Not to be used standalone. # rbe_win_clang: Options specific to compiling using Clang. # # rbe_linux_cpu: RBE options to build with only CPU support.
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tensorflow/BUILD
"//tensorflow/cc:cc_ops", "//tensorflow/cc:client_session", "//tensorflow/cc:scope", "//tensorflow/core:tensorflow", "//tensorflow/core/data:standalone", # Exports for pywrap_tensorflow_internal. Many of these are transitive # depedencies of the above, but must be explicitly listed for # cc_shared_library to work.
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RELEASE.md
package. * Support configuring TPU software version from cloud tpu client. * Allowed TPU embedding weight decay factor to be multiplied by learning rate. * XLA Support: * Add standalone XLA AOT runtime target + relevant .cc sources to pip package. * Add check for memory alignment to MemoryAllocation::MemoryAllocation()
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