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ci/official/utilities/code_check_changed_files.bats
} @test "API compatibility test passes, ensuring no unexpected changes to the TF API" { bazel test $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/api/tests:api_compatibility_test echo "You have to re-generate the TF API goldens and have the API changes reviewed." echo "Look at the instructions for ':api_compatibility_test -- --update_goldens=True'" } teardown_file() { bazel shutdown
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ci/official/envs/rbe
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ci/official/wheel_test/README.md
## Wheel Test This directory is dedicated to tests that require a built TensorFlow wheel file for testing, such as: * Ensuring the entire API is importable * Testing downstream projects against the wheel Ensure you have Bazel installed and accessible from your command line. These tests use hermetic Python. They also require a built TensorFlow wheel file and a requirements_lock file. The requirements_lock file is generated by the
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# 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 # > on the host machine. If we don't have --distinct_host_configuration=false, # > the core TensorFlow code will be built once for the host and once for the # > target platform.
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tensorflow/c/eager/c_api_test.cc
int num_retvals = 1; TFE_Execute(matmul, &retvals[0], &num_retvals, status.get()); ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get()); // The CPU handle should have been copied and have a mirror on the GPU ASSERT_TRUE(cpu_arg->HasLocalMirror(gpu_device)); TFE_DeleteOp(matmul); TFE_DeleteTensorHandle(retvals[0]); TFE_DeleteTensorHandle(hgpu); }
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tensorflow/c/experimental/filesystem/modular_filesystem.cc
#include "tensorflow/core/platform/file_system_helper.h" #include "tsl/platform/errors.h" // TODO(b/139060984): After all filesystems are converted, all calls to // methods from `FileSystem` will have to be replaced to calls to private // methods here, as part of making this class a singleton and the only way to // register/use filesystems. namespace tensorflow { using UniquePtrTo_TF_Status =
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tensorflow/c/eager/c_api_experimental_test.cc
server_def_0.mutable_default_session_config()->set_isolate_session_state( false); tensorflow::ServerDef server_def_1 = ReplaceTaskInServerDef(server_def_0, /*task_index=*/0); // These server defs have task index set to 0. string serialized_server_def_0 = server_def_0.SerializeAsString(); string serialized_server_def_1 = server_def_1.SerializeAsString(); // Create two worker tasks.
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tensorflow/c/c_api_test.cc
TF_DeleteTensor(fetchValues[1]); } // REGISTER_OP for CApiAttributesTest test cases. // Registers two ops, each with a single attribute called 'v'. // The attribute in one op will have a type 'type', the other // will have list(type). #define ATTR_TEST_REGISTER_OP(type) \ REGISTER_OP("CApiAttributesTestOp" #type) \ .Attr("v: " #type) \
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tensorflow/c/eager/dlpack_test.cc
TestHandleFromDLPack(status, ctx, {4}, {1}); TestHandleFromDLPack(status, ctx, {4, 3, 2}, {}); TestHandleFromDLPack(status, ctx, {4, 3, 2}, {6, 2, 1}); // Test that dims with size=1 can have any stride. TestHandleFromDLPack(status, ctx, {1}, {1}); TestHandleFromDLPack(status, ctx, {1}, {0}); TestHandleFromDLPack(status, ctx, {4, 1, 2}, {2, 1, 1}); TestHandleFromDLPack(status, ctx, {4, 1, 2}, {2, 0, 1});
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ci/official/envs/linux_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python
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