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tensorflow/c/eager/parallel_device/BUILD
# tensorflow/python:_pywrap_parallel_device. filegroup( name = "lib_headers", srcs = ["parallel_device_lib.h"], ) filegroup( name = "lib_sources", srcs = ["parallel_device_lib.cc"], ) filegroup( name = "device_headers", srcs = ["parallel_device.h"], ) filegroup( name = "device_sources", srcs = ["parallel_device.cc"], ) filegroup( name = "headers",
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.github/ISSUE_TEMPLATE/tflite-other.md
- type: input id: OS attributes: label: OS Platform and Distribution description: placeholder: e.g., Linux Ubuntu 16.04 validations: required: false - type: input id: Mobile attributes: label: Mobile device description: placeholder: e.g., Linux Ubuntu 16.04 validations: required: false - type: input id: Python attributes: label: Python version description: placeholder: e.g., 3.9 validations: required: false
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
--- name: TensorFlow Lite in Play Services issue about: Use this template for issues with TensorFlow Lite in Google Play Services labels: 'comp:lite-in-play-services' --- **System information** - Android Device information (use `adb shell getprop ro.build.fingerprint` if possible): - TensorFlow Lite in Play Services SDK version (found in `build.gradle`): - Google Play Services version
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tensorflow/c/BUILD
srcs = ["c_api_experimental_test.cc"], data = [ "testdata/tf_record", "//tensorflow/c/experimental/stream_executor/test:test_pluggable_device.so", "//tensorflow/core/common_runtime/next_pluggable_device/c:test_next_pluggable_device_plugin.so", ], extra_copts = if_google(["-DTENSORFLOW_NO_SHARED_OBJECTS=1"]), linkopts = select({ "//tensorflow:macos": ["-headerpad_max_install_names"],
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tensorflow/c/eager/BUILD
"//tensorflow/core:test_main", "@com_google_absl//absl/strings", ], ) cc_library( name = "custom_device_testutil", testonly = True, srcs = ["custom_device_testutil.cc"], hdrs = ["custom_device_testutil.h"], visibility = ["//tensorflow:internal"], deps = [ ":c_api", ":c_api_experimental", ":c_api_test_util",
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tensorflow/BUILD
) # Config setting that is satisfied when CUDA device code should be compiled # with clang. It does not imply that CUDA support has been enabled. alias( name = "is_cuda_compiler_clang", actual = if_oss( "@local_config_cuda//:is_cuda_compiler_clang", "@local_config_cuda//cuda:TRUE", ), ) # Config setting that is satisfied when CUDA device code should be compiled
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tensorflow/c/experimental/next_pluggable_device/BUILD
"//tensorflow/compiler/jit:variable_info", "//tensorflow/compiler/jit:variable_info_util", "//tensorflow/core:framework", "//tensorflow/core/common_runtime/next_pluggable_device:plugin_resource", "//tensorflow/core/platform:refcount", "//tensorflow/core/platform:status", "//tensorflow/core/tfrt/common:pjrt_util", "@com_google_absl//absl/status",
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RELEASE.md
* The following APIs are not longer experimental: `tf.config.list_logical_devices`, `tf.config.list_physical_devices`, `tf.config.get_visible_devices`, `tf.config.set_visible_devices`, `tf.config.get_logical_device_configuration`, `tf.config.set_logical_device_configuration`. * `tf.config.experimentalVirtualDeviceConfiguration` has been renamed to
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# Use Python 3.X as installed in container image build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3" build --python_path="/usr/local/bin/python3" # Build TensorFlow v2 build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1 # Prevent double-compilation of some TF code, ref. b/183279666 (internal) # > TF's gen_api_init_files has a genrule to run the core TensorFlow code
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README.md
[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and Windows)*: ``` $ pip install tensorflow ``` Other devices (DirectX and MacOS-metal) are supported using [Device plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices). A smaller CPU-only package is also available: ``` $ pip install tensorflow-cpu ```
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