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ci/official/wheel_test/README.md
``` #### Requirements Updater Script This script automates the process of updating TensorFlow requirements for a specific Python version. ##### Parameters `path_to_tensorflow_wheel`: The local path to the TensorFlow wheel file. Example: `/tmp/tensorflow-2.14.0-cp311-cp311-linux_x86_64.whl` `python_version`: The target Python version, replacing `.` with `_`.
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tensorflow/c/eager/unified_api_testutil.h
#include "tensorflow/core/platform/status.h" namespace tensorflow { // Builds and returns a `TracingContext` using the default tracing impl. AbstractContext* BuildFunction(const char* fn_name); // Creates parameters (placeholders) in the tracing `ctx` using the shape and // dtype of `inputs`. Status CreateParamsForInputs(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
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tensorflow/c/experimental/filesystem/plugins/gcs/expiring_lru_cache.h
InsertLocked(key, *value); } } /// Clear the cache. void Clear() { absl::MutexLock lock(&mu_); cache_.clear(); lru_list_.clear(); } /// Accessors for cache parameters. uint64_t max_age() const { return max_age_; } size_t max_entries() const { return max_entries_; } private: struct Entry { /// The timestamp (seconds) at which the entry was added to the cache.
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ci/official/utilities/setup.sh
export -p | grep TFCI # Load those stored pre-existing TFCI_ vars, if any if [[ -s "$FROM_ENV" ]]; then echo '==TFCI==: NOTE: Loading the following env parameters, which were' echo 'already set in the shell environment. If you want to disable this' echo 'behavior, create a new shell.' cat "$FROM_ENV" source "$FROM_ENV" rm "$FROM_ENV" fi fi
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Jan 26 00:33:34 GMT 2024 - 5.2K bytes - Viewed (1) -
tensorflow/c/eager/gradient_checker.h
#include "tensorflow/c/eager/unified_api_testutil.h" namespace tensorflow { namespace gradients { /* Returns numerical grad inside `dtheta_approx` given `forward` model and * parameter specified by `input_index`. * * I.e. if y = <output of the forward model> and w = inputs[input_index], * this will calculate dy/dw numerically. *
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ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh
ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic" ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm" # Download glibc's shared and development libraries based on the value of the # `VERSION` parameter. # Note: 'Templatizing' this and the other conditional branches would require # defining several variables (version, os, path) making it difficult to maintain # and extend for future modifications. mkdir -p glibc-src
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ci/official/requirements_updater/README.md
While this isn't necessary for running the updater, it is required for actually using the new version with Tensorflow. 2) In the `WORKSPACE` file, add the new version to the `python_versions` parameter of the `python_register_multi_toolchains` function. 3) In the `BUILD.bazel` file, add a load statement for the new version, e.g. ``` load("@python//3.11:defs.bzl",
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tensorflow/c/eager/c_api_unified_experimental.h
// Represents a (partially-defined) shape. typedef struct TF_Shape { int num_dims; // Must be >= -1; -1 represents unknown rank. int64_t* dim_sizes; } TF_Shape; // Add a new parameter to a TensorFlow Function. TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func, TF_DataType dtype, TF_Shape shape, TF_Status* s);
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ci/official/requirements_updater/updater_config_repository.bzl
''' Repository rule to set some environment variables. Can be set via build parameter "--repo_env=<VARIABLE_NAME>=<value>" e.g "--repo_env=REQUIREMENTS_FILE_NAME=requirements.in" List of variables: REQUIREMENTS_FILE_NAME ''' def _updater_config_repository_impl(repository_ctx): repository_ctx.file("BUILD", "") requirements_file_name = repository_ctx.os.environ.get("REQUIREMENTS_FILE_NAME", "requirements.in") repository_ctx.file(
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tensorflow/c/eager/c_api_unified_experimental_internal.h
class TracingContext : public AbstractContext { protected: explicit TracingContext(AbstractContextKind kind) : AbstractContext(kind) {} public: // Add a function parameter and return the corresponding tensor. virtual Status AddParameter(DataType dtype, const PartialTensorShape& shape, TracingTensorHandle**) = 0;
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