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ci/devinfra/docker_windows/Dockerfile
# Install Visual C++ Redistributable for Visual Studio 2015-2022. RUN New-Item -Path "C:/" -Name "TEMP" -ItemType "directory"; \ Invoke-WebRequest "https://aka.ms/vs/17/release/vc_redist.x64.exe" \ -OutFile C:/TEMP/vc_redist.x64.exe -UseBasicParsing; \ Start-Process -filepath C:/TEMP/vc_redist.x64.exe -ArgumentList '/install', '/passive', '/norestart' -Wait; \ Remove-Item C:/TEMP/vc_redist.x64.exe
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ci/official/README.md
# Finally: Run your script of choice. # If you've clicked on a test result from our CI (via a dashboard or GitHub link), # click to "Invocation Details" and find BUILD_CONFIG, which will contain a # "build_file" item that indicates the script used. ci/official/wheel.sh # Advanced: Select specific build/test targets with "any.sh". # TF_ANY_TARGETS=":your/target" TF_ANY_MODE="test" ci/official/any.sh
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tensorflow/BUILD
"//tensorflow/core/grappler/graph_analyzer:graph_analyzer_tool", "//tensorflow/core/grappler/optimizers:meta_optimizer", "//tensorflow/core/grappler:grappler_item", "//tensorflow/core/grappler:grappler_item_builder", "//tensorflow/core/kernels:data_service_ops", "//tensorflow/core/kernels:dataset_ops", "//tensorflow/core/platform:logging",
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RELEASE.md
ML authoring is generally discouraged. * Add support for unsigned 16-bit integer tensor types in cast op. * Experimental support for lowering `list_ops.tensor_list_set_item` with `DynamicUpdateSlice`. * Enabled a new MLIR-based dynamic range quantization backend by default * The new backend is used for post-training int8 dynamic range
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