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tensorflow/c/eager/c_api_experimental.h
// // Arguments provide enough information to reconstruct the original `TFE_Op`, // or construct a transformed version, by inspecting the passed `op`. // // TFE_OpGetDevice(op) records the original placement of the operation. It may // be an empty string if no device was explicitly requested, but will // otherwise be the name of this custom device. Ops are placed onto a custom
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tensorflow/c/eager/tape.h
// // This is a no-op if the tensor is already being watched either from an // earlier call to `GradientTape::Watch` or being an output of an op with // watched inputs. void Watch(int64_t tensor_id); // Records an operation with inputs `input_tensor_id` and outputs // `output_tensors` on the tape and marks all its outputs as watched if at // least one input of the op is watched and has trainable dtype. //
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tensorflow/c/eager/graph_function.h
absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord() override { return func_record_.GetNewRef(); } // For LLVM style RTTI. static bool classof(const AbstractFunction* ptr) { return ptr->getKind() == kGraph; } private: core::RefCountPtr<FunctionRecord> func_record_; }; } // namespace graph } // namespace tracing } // namespace tensorflow
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tensorflow/c/c_api.cc
if (TF_GetCode(status) == TF_OK) { // This modification only updates the destination node for // the purposes of running this graph in a session. Thus, we don't // record the source node as being modified. RecordMutation(graph, *dst.oper, "updating input tensor"); } } // Apis that are corresponding to python c api. --------------------------
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tensorflow/c/BUILD
], ) tf_cc_test( name = "c_api_experimental_test", size = "medium", srcs = ["c_api_experimental_test.cc"], data = [ "testdata/tf_record", "//tensorflow/c/experimental/stream_executor/test:test_pluggable_device.so", "//tensorflow/core/common_runtime/next_pluggable_device/c:test_next_pluggable_device_plugin.so", ],
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ci/official/libtensorflow.sh
# limitations under the License. # ============================================================================== source "${BASH_SOURCE%/*}/utilities/setup.sh" # Record GPU count and CUDA version status if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then tfrun nvidia-smi fi # Update the version numbers for Nightly only if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
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ci/official/wheel.sh
# limitations under the License. # ============================================================================== source "${BASH_SOURCE%/*}/utilities/setup.sh" # Record GPU count and CUDA version status if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then tfrun nvidia-smi fi # Update the version numbers for Nightly only if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
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tensorflow/c/eager/c_api.cc
tensorflow::core::RefCountPtr<tensorflow::FunctionRecord> record = tensorflow::unwrap(ctx)->FindRecord(name); if (record == nullptr) { status->status = tensorflow::errors::NotFound( "Unable to find Function with name: ", name); return nullptr; } TF_Function* result = new TF_Function(); record->Ref(); result->record = record.get(); return result; }
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tensorflow/c/eager/c_api_experimental.cc
auto function_record = tensorflow::unwrap(ctx)->FindRecord(function_name); if (function_record == nullptr) { status->status = tensorflow::errors::NotFound( "Unable to find function with name: ", function_name); return; } tensorflow::GraphDebugInfo debug_info = tensorflow::StackTracesMapToGraphDebugInfo( function_record->stack_traces());
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tensorflow/c/eager/c_api_unified_experimental_graph.cc
graph_outputs.size(), graph_outputs.data(), nullptr, nullptr, name_.data(), s); *f = new GraphFunction(std::move(func->record->fdef())); TF_DeleteFunction(func); TF_RETURN_IF_ERROR(StatusFromTF_Status(s)); TF_DeleteStatus(s); return absl::OkStatus(); } Status RegisterFunction(AbstractFunction* func) override {
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