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ci/official/envs/rbe
That setting must exist for this script to function correctly. EOF exit 1 fi TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" # These flags share the user's gcloud credentials with the container, so that bazel # inside the container can authenticate. Note: TF's CI does not have any credential # stored here.
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tensorflow/c/eager/unified_api_testutil.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, std::vector<AbstractTensorHandle*>* params);
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tensorflow/c/eager/c_api_unified_experimental.cc
return nullptr; } tensorflow::PartialTensorShape partial_shape; if (shape.num_dims != -1) { DCHECK(shape.dim_sizes != nullptr); Status status = tensorflow::PartialTensorShape::MakePartialShape( reinterpret_cast<int64_t*>(shape.dim_sizes), shape.num_dims, &partial_shape); if (!status.ok()) { tsl::Set_TF_Status_from_Status(s, status); return nullptr;
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tensorflow/c/eager/immediate_execution_tensor_handle.cc
namespace tensorflow { std::string ImmediateExecutionTensorHandle::DebugString() const { PartialTensorShape shape; std::string shape_string; if (Shape(&shape).ok()) { shape_string = shape.DebugString(); } else { shape_string = "<error computing shape>"; } std::string value_string; if (!SummarizeValue(value_string).ok()) { value_string = "<error computing value>"; }
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tensorflow/c/eager/immediate_execution_distributed_manager.h
// on cluster configurations provided in `server_def`; otherwise, update // existing context state with the provided `server_def`. Contexts created // on remote tasks will be considered stale and garbage collected after // `keep_alive_secs` of inactivity. virtual Status SetOrUpdateServerDef(const ServerDef& server_def, bool reset_context, int keep_alive_secs,
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ci/official/README.md
# export TFCI=py311,linux_x86,no_docker # Advanced: Use Remote Build Execution (RBE) (internal developers only) # # RBE dramatically speeds up builds and testing. It also gives you a # public URL to share your build results with collaborators. However, # it is only available to a limited set of internal TensorFlow developers. # # RBE is incompatible with local caching, so you must remove
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tensorflow/c/eager/unified_api_test.cc
absl::Span<AbstractTensorHandle*> outputs) { PartialTensorShape shape; TF_RETURN_IF_ERROR(inputs[0]->Shape(&shape)); if (shape.dims() != 0) { return errors::InvalidArgument( "Tensor expected to have scalar shape found rank: ", shape.dims()); } return absl::OkStatus(); } TEST_P(UnifiedAPI, TestTensorShapeScalar) { if (UseFunction() && UseMlir()) {
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tensorflow/c/eager/unified_api_testutil.cc
tracing::TracingTensorHandle* handle = nullptr; for (auto input : inputs) { PartialTensorShape shape; TF_RETURN_IF_ERROR(input->Shape(&shape)); TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingContext>(ctx)->AddParameter( input->DataType(), shape, &handle)); params->emplace_back(handle); } return absl::OkStatus(); } // Runs `model` maybe wrapped in a function.
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ci/official/utilities/rename_and_verify_wheels.sh
"$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)' "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)' fi # VERY basic check to ensure the [and-cuda] package variant is installable.
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ci/official/containers/linux_arm64/devel.usertools/wheel_verification.bats
python3 -m pip install "$TF_WHEEL" } @test "TensorFlow is importable" { source /tf/venv/bin/activate python3 -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)' } # Is this still useful? @test "TensorFlow has Keras" { source /tf/venv/bin/activate python3 -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
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