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tensorflow/c/eager/parallel_device/parallel_device_lib.h
// `StartExecute`s will deadlock). // // If `is_async=false` (constructor argument), `cancellation_manager` must // live until `Join` finishes. If `is_async=true` it must live until `Join` is // followed by `TFE_ContextAsyncWait` to clear pending operations. It will be // used to cancel all other operations if any fails. // // Set step_id to configure the step id used for rendezvous creation. step id
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tensorflow/c/c_api.h
// Similar to TF_GraphToFunction but allows specifying control outputs of the // function. // // The arguments of TF_GraphToFunction have the same meaning, but the new // arguments are as follows: // // ncontrol_outputs: Number of control outputs of the function. // control_outputs: vector of TF_Operation objects to be marked as control
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ci/official/wheel_test/README.md
Packages are imported one by one in alphabetical order during runtime. The test doesn't identify package's order-dependent issues; for instance, importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on "tf.foo" being imported first. The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2
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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache_test.cc
TF_EXPECT_OK(ReadCache(&cache, "", 0, 1, &out)); calls.push_back(block_size); // Cache miss followed by cache hit. TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out)); TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out)); calls.push_back(2 * block_size); // Cache miss followed by cache hit. Causes eviction of LRU element. TF_EXPECT_OK(ReadCache(&cache, "", 2 * block_size, 1, &out));
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ci/official/utilities/repack_libtensorflow.sh
# Source files generated by annotation processors appear directly # under the root of srcjars jars created by bazel, rather than under # the maven-style src/main/java subdirectory. # # Bazel manages annotation generated source as follows: First, it # calls javac with options that create generated files under a # bazel-out directory. Next, it archives the generated source files # into a srcjar directly under the root. There doesn't appear to be a
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tensorflow/c/eager/tape.h
// - target: dy in dx/dy // - source: dx in dx/dy // - tensor: one of the many inputs or outputs of an operation // // Below here we do the gradient algorithm. It works as follows: // // First we filter the tape to just the subset of operations we want to // differentiate. In the process of doing so we count how many times each Tensor
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CONTRIBUTING.md
```bash docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10 ``` Once you have the packages installed, you can run a specific unit test in bazel by doing as follows: ```bash export flags="--config=opt -k" ``` If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and add the `cuda` option flag ```bash
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ci/official/containers/linux_arm64/devel.usertools/repack_libtensorflow.sh
# Source files generated by annotation processors appear directly # under the root of srcjars jars created by bazel, rather than under # the maven-style src/main/java subdirectory. # # Bazel manages annotation generated source as follows: First, it # calls javac with options that create generated files under a # bazel-out directory. Next, it archives the generated source files # into a srcjar directly under the root. There doesn't appear to be a
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tensorflow/c/experimental/filesystem/filesystem_interface.h
/// this file to ensure a compliant plugin can be built and that the plugin can /// be used without recompilation in the widest range of TensorFlow versions. /// /// The header is divided into sections, as follows: /// 1. Opaque plugin private data structures and wrappers for type safety; /// 2. Function tables for plugin functionality; /// 3. Versioning metadata; /// 4. Plugin registration API and the DSO entry point.
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RELEASE.md
import os;os.environ["TF_USE_LEGACY_KERAS"]=1. Please note that this will set it for all packages in your Python runtime program * 1. Change import of keras from tensorflow as follows * import tensorflow.keras as keras and import keras to import tf_keras as keras * **Apple Silicon users:** If you previously installed TensorFlow using
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