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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which # drops all the bazel dependencies for each py_test; this makes all the tests # use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. #
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ci/official/requirements_updater/README.md
``` ## How to add a new Python version Note: Updating the [rules-python](https://github.com/bazelbuild/rules_python/releases) version may be required before going through the steps below. This is due to the new Python versions becoming available through `rules-python`. \ See [here](https://github.com/tensorflow/tensorflow/commit/f91457f258fdd78f693044a57efa63a38335d1de), and
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CONTRIBUTING.md
the change has been submitted internally, your pull request will be merged automatically on GitHub. If you want to contribute, start working through the TensorFlow codebase, navigate to the [GitHub "issues" tab](https://github.com/tensorflow/tensorflow/issues) and start looking through interesting issues. If you are not sure of where to start, then start by trying one of the smaller/easier issues here i.e.
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ci/official/utilities/rename_and_verify_wheels.sh
# ============================================================================== # # Usage: rename_and_verify_wheels.sh # This script is aware of TFCI_ variables, so it doesn't need any arguments. # Puts new wheel through auditwheel to rename and verify it, deletes the old # one, checks the filesize, and then ensures the new wheel is installable. set -euxo pipefail cd "$TFCI_OUTPUT_DIR"
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which # drops all the bazel dependencies for each py_test; this makes all the tests # use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. #
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tensorflow/c/c_api_test.cc
EXPECT_TRUE(feed == feed2); ASSERT_TRUE(GetNodeDef(feed, &node_def)); ASSERT_TRUE(GetNodeDef(feed2, &node_def2)); EXPECT_EQ(node_def.DebugString(), node_def2.DebugString()); // Test iterating through the nodes of a graph. found_placeholder = false; found_scalar_const = false; found_add = false; bool found_neg = false; size_t pos = 0; TF_Operation* oper;
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tensorflow/c/experimental/next_pluggable_device/c_api.h
// should allow registering a plugin device with TensorFlow. #ifdef __cplusplus extern "C" { #endif // TF_Device is a C wrapper to the C++ TF Device class. This is to be passed // through TF_OpKernelContext, and is opaque to plugin. typedef struct TF_Device TF_Device; typedef struct TF_VariableInfo TF_VariableInfo; // Returns a `TF_Device` pointer, which actually points to a C++ `Device`.
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tensorflow/c/eager/unified_api_testutil.h
absl::Span<AbstractTensorHandle* const>, absl::Span<AbstractTensorHandle*>)>; // Runs `model` maybe wrapped in a function call op. This can be thought as // being equivalent to the following python code. // // if use_function: // outputs = tf.function(model)(inputs) // else: // outputs = model(inputs) Status RunModel(Model model, AbstractContext* ctx,
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tensorflow/c/eager/c_api_experimental.h
TF_CAPI_EXPORT extern void TFE_HostAddressSpace(TFE_Context* ctx, TF_Buffer* buf); // APIs for generically dealing with op attributes (e.g. when forwarding them // through custom device implementations). // // TODO(allenl): Currently these are black boxes, but we should have some way to // inspect values. This would let people e.g. copy over most attributes and then
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RELEASE.md
* Introducing `tf.types.experimental.AtomicFunction` as the fastest way to perform TF computations in Python. * Can be accessed through `inference_fn` property of `ConcreteFunction`s * Does not support gradients.
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