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tensorflow/c/eager/graph_function.h
limitations under the License. ==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_ #define TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_ #include "tensorflow/c/eager/abstract_function.h" #include "tensorflow/core/framework/function.h" #include "tensorflow/core/platform/refcount.h" namespace tensorflow { namespace tracing { namespace graph {
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Mar 04 19:49:06 GMT 2024 - 1.8K bytes - Viewed (0) -
tensorflow/c/eager/abstract_function.h
limitations under the License. ==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_ #define TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_ #include "absl/status/statusor.h" #include "tensorflow/core/framework/function.pb.h" #include "tensorflow/core/platform/intrusive_ptr.h" #include "tensorflow/core/platform/refcount.h" #include "tensorflow/core/platform/status.h"
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tensorflow/c/c_api.h
int index; // The index of the output within oper. } TF_Output; // TF_Function is a grouping of operations with defined inputs and outputs. // Once created and added to graphs, functions can be invoked by creating an // operation whose operation type matches the function name. typedef struct TF_Function TF_Function; // Function definition options. TODO(iga): Define and implement
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tensorflow/c/eager/abstract_context.h
// it in this context. virtual AbstractOperation* CreateOperation() = 0; // Registers a function with this context, after this the function is // available to be called/referenced by its name in this context. virtual Status RegisterFunction(AbstractFunction*) = 0; // Remove a function. 'func' argument is the name of a previously added // FunctionDef. The name is in fdef.signature.name.
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
std::vector<std::unique_ptr<DeviceThread>> device_threads_; // A cancellation manager to use if the caller does not provide one. When ops // are executed asynchronously this must outlive the queued op, so it can't be // function-local to Execute. mutable std::unique_ptr<CancellationManager> default_cancellation_manager_; }; // Contains a tuple of tensors, one on each of the `underlying_devices_` of the // ParallelDevice.
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tensorflow/c/eager/c_api.h
// TFE_Execute by creating an op with the same name as the function. TF_CAPI_EXPORT extern void TFE_ContextAddFunction(TFE_Context* ctx, TF_Function* function, TF_Status* status); // Removes a function from the context. Once removed, you can no longer // TFE_Execute it or TFE_Execute any TFE_Op which has it as an attribute or any
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tensorflow/c/eager/tape.h
// (`output_tensors`). // // If provided, a non-null `forward_function` will be used instead of the // backward function (`backward_function_getter` / // `backward_function_deleter`) to compute jvps for this operation. If // `forward_function` is null, a GradientTape is used on the backward function // to compute the jvp, which will waste computation when executing eagerly. //
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tensorflow/c/c_test.c
#include "tensorflow/c/kernels.h" // A create function. This will never actually get called in this test, it's // just nice to know that it compiles. void* create(TF_OpKernelConstruction* ctx) { TF_DataType type; TF_Status* s = TF_NewStatus(); TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s); TF_DeleteStatus(s); return NULL; } // A compute function. This will never actually get called in this test, it's
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tensorflow/c/eager/tfe_monitoring_internal.h
using TFE_MonitoringGauge::TFE_MonitoringGauge; }; struct TFE_MonitoringBuckets { explicit TFE_MonitoringBuckets( std::function<std::unique_ptr<tensorflow::monitoring::Buckets>(void)> fn) { create_buckets = fn; } std::function<std::unique_ptr<tensorflow::monitoring::Buckets>(void)> create_buckets; }; struct TFE_MonitoringSamplerCell {
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tensorflow/c/eager/c_api_unified_experimental.h
// here. void TF_SetTracingImplementation(const char* name, TF_Status*); // Creates a new TensorFlow function. A Function is an execution context, and as // such it can trace operations through TF_ExecuteOperation. After completing // tracing, a function can be obtained by TF_FinalizeFunction. TF_ExecutionContext* TF_CreateFunction(const char* fn_name, TF_Status* status);
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