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tensorflow/c/eager/c_api_unified_experimental.h
typedef struct TF_AbstractFunction TF_AbstractFunction; // This allows the client to swap the implementation of the tracing engine. // Any future call to TF_CreateFunction will use the implementation defined // here. void TF_SetTracingImplementation(const char* name, TF_Status*); // Creates a new TensorFlow function. A Function is an execution context, and as
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tensorflow/c/eager/c_api.h
TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op, const char* output_name, TF_Status* status); // Execute the operation defined by 'op' and return handles to computed // tensors in `retvals`. // // 'retvals' must point to a pre-allocated array of TFE_TensorHandle* and // '*num_retvals' should be set to the size of this array. It is an error if
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tensorflow/c/experimental/grappler/grappler.cc
limitations under the License. ==============================================================================*/ // This file extends/implements core graph optimizer base classes in terms of // the C API defined in grappler.h. A class "CSomething" represents a // "Something" that can be manipulated via calls in the C interface and a C // struct called "TP_Something". #include "tensorflow/c/experimental/grappler/grappler.h"
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Wed Sep 06 19:12:29 GMT 2023 - 15K bytes - Viewed (1) -
tensorflow/c/eager/c_api_experimental.h
TFE_Context*); // ----------------------------------------------------------------------------- // Dynamic cluster API. // Update an existing context with a new set of servers defined in a ServerDef // proto. Servers can be added to and removed from the list of remote workers // in the context. A New set of servers identified by the ServerDef must be up // when the context is updated. //
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CONTRIBUTING.md
These are issues that we believe are particularly well suited for outside contributions, often because we probably won't get to them right now. If you decide to start on an issue, leave a comment so that other people know that you're working on it. If you want to help out, but not alone, use the issue comment thread to coordinate. ### Contribution guidelines and standards
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tensorflow/c/eager/gradients.cc
const ForwardOperation& op, std::unique_ptr<GradientFunction>* gradient_function) const { auto iter = registry_.find(op.op_name); if (iter == registry_.end()) { const string error_msg = "No gradient defined for op: " + op.op_name + "."; return errors::NotFound(error_msg); } gradient_function->reset(iter->second(op)); return absl::OkStatus(); }
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tensorflow/c/c_api_experimental_test.cc
ASSERT_EQ(TF_OK, code) << status_msg; TF_DeletePluggableDeviceLibraryHandle(lib); #endif // !defined(TENSORFLOW_NO_SHARED_OBJECTS) #endif // !defined(PLATFORM_WINDOWS) } TEST(CAPI_EXPERIMENTAL, LibraryNextPluggableDeviceLoadFunctions) { // TODO(penpornk): Enable this test on Windows. #if !defined(PLATFORM_WINDOWS) #if !defined(TENSORFLOW_NO_SHARED_OBJECTS) // Load the library. TF_Status* status = TF_NewStatus();
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Jan 17 22:27:52 GMT 2023 - 13.1K bytes - Viewed (1) -
tensorflow/c/eager/c_api.cc
int64_t init_timeout_in_ms, int retries, TF_Status* status, bool clear_existing_contexts) { #if defined(IS_MOBILE_PLATFORM) status->status = tensorflow::errors::Unimplemented( "TFE_ContextSetServerDef not supported on mobile"); #else // !defined(IS_MOBILE_PLATFORM) tensorflow::ServerDef server_def; if (!server_def.ParseFromArray(proto, proto_len)) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 43.9K bytes - Viewed (2) -
ci/official/utilities/setup_macos.sh
if [[ "${TFCI_MACOS_BAZEL_TEST_DIR_ENABLE}" == 1 ]]; then mkdir -p "${TFCI_MACOS_BAZEL_TEST_DIR_PATH}" export TEST_TMPDIR="${TFCI_MACOS_BAZEL_TEST_DIR_PATH}" fi # "TFCI_MACOS_INSTALL_BAZELISK_ENABLE" is used to decide if we need to install # Bazelisk manually. We enable this for macOS x86 builds as those VMs do not # have Bazelisk pre-installed. "TFCI_MACOS_INSTALL_BAZELISK_URL" contains the
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tensorflow/c/eager/c_api_unified_experimental_internal.h
// backends (graph/MLIR). // // This defines a set of abstract classes that are intended to provide the // functionality of the opaque C types exposed in the public APIs defined in the // `c_api_unified_experimental.h` header. // ============================================================================= // Represents either a MlirTensor or a GraphTensor.
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