Remove unused experimental APIs
PiperOrigin-RevId: 312330039 Change-Id: I721642d67294ea5e0ba3702058106ea423db72d1
This commit is contained in:
Alexandre Passos
TensorFlower Gardener
parent
c12107003b
commit
b4360f894c
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@ -325,205 +325,6 @@ TF_Buffer* TFE_GetServerDef(const char* text_proto, TF_Status* status) {
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return ret;
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return ret;
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}
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}
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TFE_Context* TFE_CreateContextFromSession(TF_Session* session,
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TF_Status* status) {
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auto* opts = TFE_NewContextOptions();
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// Reduce GPU memory allocation, and set appropriate config options for TFE
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// context.
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auto* config = TF_CreateConfig(
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/*xla*/ false, /* gpu_memory_allow_growth */ true, /* num_cpu_devices */
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10);
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TFE_ContextOptionsSetConfig(opts, config->data, config->length, status);
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if (!status->status.ok()) {
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CHECK(!config);
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TFE_DeleteContextOptions(opts);
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return nullptr;
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}
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auto* ctx = TFE_NewContextFromSession(opts, session, status);
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TF_DeleteBuffer(config);
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TFE_DeleteContextOptions(opts);
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return ctx;
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}
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// TODO: retrieve the device string via TFE_ContextListDevices()
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static const char DEFAULT_CPU_DEVICE[] =
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"/job:localhost/replica:0/task:0/device:CPU:0";
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static TFE_TensorHandle* createTFEQueue(TFE_Context* ctx, TF_DataType inputType,
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int tensor_id, TF_Status* status) {
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std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> queueOp(
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TFE_NewOp(ctx, "FIFOQueueV2", status), TFE_DeleteOp);
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TFE_OpSetDevice(queueOp.get(), DEFAULT_CPU_DEVICE, status);
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if (!status->status.ok()) return nullptr;
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// TODO: use NAMED_TENSOR_QUEUE_CAPACITY in S4TF compiler.
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TFE_OpSetAttrInt(queueOp.get(), "capacity", 1);
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TFE_OpSetAttrTypeList(queueOp.get(), "component_types", &inputType, 1);
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auto shared_name = tensorflow::strings::StrCat("fifo_queue_", tensor_id);
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TFE_OpSetAttrString(queueOp.get(), "shared_name", shared_name.data(),
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shared_name.size());
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TFE_OpSetAttrString(queueOp.get(), "container", "", 0);
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// TODO: consider making this an unknown shape.
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const int64_t* dims_ptr = nullptr;
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int num_dims = 0;
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TFE_OpSetAttrShapeList(queueOp.get(), "shapes", &dims_ptr, &num_dims,
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/*num_values*/ 0, status);
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if (!status->status.ok()) return nullptr;
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int num_retvals = 1;
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TFE_TensorHandle* queue = nullptr;
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TFE_Execute(queueOp.get(), &queue, &num_retvals, status);
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if (!status->status.ok()) return nullptr;
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CHECK_EQ(num_retvals, 1);
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return queue;
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}
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static void createTFEEnqueue(TFE_Context* ctx, TF_DataType inputType,
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TFE_TensorHandle* queue, TFE_TensorHandle* tensor,
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TF_Status* status) {
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TFE_Op* op = TFE_NewOp(ctx, "QueueEnqueueV2", status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op_deleter(op, TFE_DeleteOp);
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TFE_OpSetDevice(op, DEFAULT_CPU_DEVICE, status);
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if (!status->status.ok()) return;
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TFE_OpAddInput(op, queue, status);
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if (!status->status.ok()) return;
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TFE_OpAddInput(op, tensor, status);
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if (!status->status.ok()) return;
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TFE_OpSetAttrTypeList(op, "Tcomponents", &inputType, 1);
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TFE_OpSetAttrInt(op, "timeout_ms", -1);
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int num_retvals = 0;
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TFE_Execute(op, nullptr /*retvals*/, &num_retvals, status);
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if (!status->status.ok()) return;
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CHECK_EQ(num_retvals, 0);
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}
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static TFE_TensorHandle* createTFEDequeue(TFE_Context* ctx,
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TF_DataType inputType,
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TFE_TensorHandle* queue,
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TF_Status* status) {
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TFE_Op* op = TFE_NewOp(ctx, "QueueDequeueV2", status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op_deleter(op, TFE_DeleteOp);
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TFE_OpSetDevice(op, DEFAULT_CPU_DEVICE, status);
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if (!status->status.ok()) return nullptr;
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TFE_OpAddInput(op, queue, status);
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if (!status->status.ok()) return nullptr;
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TFE_OpSetAttrTypeList(op, "component_types", &inputType, 1);
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TFE_OpSetAttrInt(op, "timeout_ms", -1);
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TFE_TensorHandle* ret;
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int num_retvals = 1;
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TFE_Execute(op, &ret, &num_retvals, status);
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if (!status->status.ok()) return nullptr;
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CHECK_EQ(num_retvals, 1);
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return ret;
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}
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TFE_TensorHandle* TFE_DequeueNamedTensor(TF_Session* session, int tensor_id,
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TF_DataType inputType,
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TF_Status* status) {
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assert(session);
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VLOG(1) << "Dequeuing data tensor with id " << tensor_id;
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auto ctx = TFE_CreateContextFromSession(session, status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> ctx_deleter(
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ctx, TFE_DeleteContext);
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TFE_TensorHandle* queue = createTFEQueue(ctx, inputType, tensor_id, status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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auto* ret = createTFEDequeue(ctx, inputType, queue, status);
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return ret;
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}
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TFE_TensorHandle* TFE_DequeueNamedTensorFromCtx(TFE_Context* ctx, int tensor_id,
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TF_DataType inputType,
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TF_Status* status) {
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TFE_TensorHandle* queue = createTFEQueue(ctx, inputType, tensor_id, status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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auto* ret = createTFEDequeue(ctx, inputType, queue, status);
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return ret;
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}
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void TFE_EnqueueNamedTensor(TF_Session* session, int tensor_id,
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TFE_TensorHandle* tensor, TF_Status* status) {
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assert(session);
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VLOG(1) << "Enqueuing data tensor with id " << tensor_id;
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auto ctx = TFE_CreateContextFromSession(session, status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> ctx_deleter(
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ctx, TFE_DeleteContext);
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TF_DataType inputType = TFE_TensorHandleDataType(tensor);
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TFE_TensorHandle* queue = createTFEQueue(ctx, inputType, tensor_id, status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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createTFEEnqueue(ctx, inputType, queue, tensor, status);
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}
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void TFE_EnqueueNamedTensorFromCtx(TFE_Context* ctx, int tensor_id,
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TFE_TensorHandle* tensor,
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TF_Status* status) {
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VLOG(1) << "Enqueuing data tensor with id " << tensor_id;
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TF_DataType inputType = TFE_TensorHandleDataType(tensor);
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TFE_TensorHandle* queue = createTFEQueue(ctx, inputType, tensor_id, status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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createTFEEnqueue(ctx, inputType, queue, tensor, status);
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}
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void TFE_EnqueueVariantTensor(TF_Session* session, int tensor_id,
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TFE_TensorHandle* tensor, TF_Status* status) {
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VLOG(1) << "Enqueuing variant tensor with id " << tensor_id;
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auto ctx = TFE_CreateContextFromSession(session, status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> ctx_deleter(
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ctx, TFE_DeleteContext);
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TFE_TensorHandle* queue = createTFEQueue(ctx, TF_VARIANT, tensor_id, status);
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if (!status->status.ok()) return;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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createTFEEnqueue(ctx, TF_VARIANT, queue, tensor, status);
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}
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TFE_TensorHandle* TFE_DequeueVariantTensor(TF_Session* session, int tensor_id,
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TF_Status* status) {
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VLOG(1) << "Dequeuing variant tensor with id " << tensor_id;
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auto ctx = TFE_CreateContextFromSession(session, status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> ctx_deleter(
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ctx, TFE_DeleteContext);
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TFE_TensorHandle* queue = createTFEQueue(ctx, TF_VARIANT, tensor_id, status);
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if (!status->status.ok()) return nullptr;
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std::unique_ptr<TFE_TensorHandle, decltype(&TFE_DeleteTensorHandle)>
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queue_deleter(queue, TFE_DeleteTensorHandle);
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return createTFEDequeue(ctx, TF_VARIANT, queue, status);
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}
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void TF_MakeInternalErrorStatus(TF_Status* status, const char* errMsg) {
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void TF_MakeInternalErrorStatus(TF_Status* status, const char* errMsg) {
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status->status = tensorflow::errors::Internal(errMsg);
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status->status = tensorflow::errors::Internal(errMsg);
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}
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}
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@ -622,10 +423,9 @@ void TF_AttrBuilderSetType(TF_AttrBuilder* builder, const char* attr_name,
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void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
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void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
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const TF_DataType* values, int num_values) {
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const TF_DataType* values, int num_values) {
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auto iter = builder->attr_names.insert(attr_name).first;
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auto iter = builder->attr_names.insert(attr_name).first;
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builder->Set(
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builder->Set(*iter, tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
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(*iter).c_str(),
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reinterpret_cast<const tensorflow::DataType*>(values),
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tensorflow::gtl::ArraySlice<const tensorflow::DataType>(
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num_values));
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reinterpret_cast<const tensorflow::DataType*>(values), num_values));
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}
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}
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void TF_AttrBuilderCheckCanRunOnDevice(TF_AttrBuilder* builder,
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void TF_AttrBuilderCheckCanRunOnDevice(TF_AttrBuilder* builder,
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@ -146,48 +146,6 @@ TF_CAPI_EXPORT extern void TF_EnqueueNamedTensor(TF_Session* session,
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// Create a serialized tensorflow.ServerDef proto.
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// Create a serialized tensorflow.ServerDef proto.
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TF_Buffer* TFE_GetServerDef(const char* text_proto, TF_Status* status);
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TF_Buffer* TFE_GetServerDef(const char* text_proto, TF_Status* status);
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// TODO: remove this API in favor of the next one.
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TF_CAPI_EXPORT extern TFE_Context* TFE_NewContextFromSession(
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const TFE_ContextOptions* opts, TF_Session* sess, TF_Status* status);
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// Creates from `session` a new eager context to run a graph function or
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// sends/recvs, so that these concurrent TFE executions can share (via
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// `session` and its associated device mgr) the same set of fifo queue resource
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// ops, used for host<->TF tensor transfers. This way the sends/recvs calls and
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// graph function execution can access the same fifo queue resource handles
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// (associated with devices managed by the device manager, which can be obtained
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// from `session`).
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//
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// TODO: Remove this function once we migrate away from using session.
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TF_CAPI_EXPORT extern TFE_Context* TFE_CreateContextFromSession(
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TF_Session* session, TF_Status* status);
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// TODO: Retire this API in favor of the next one.
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TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_DequeueNamedTensor(
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TF_Session* session, int tensor_id, TF_DataType inputType,
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TF_Status* status);
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TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_DequeueNamedTensorFromCtx(
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TFE_Context* ctx, int tensor_id, TF_DataType inputType, TF_Status* status);
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TF_CAPI_EXPORT extern void TFE_EnqueueNamedTensor(TF_Session* session,
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int tensor_id,
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TFE_TensorHandle* tensor,
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TF_Status* status);
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TF_CAPI_EXPORT extern void TFE_EnqueueNamedTensorFromCtx(
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TFE_Context* ctx, int tensor_id, TFE_TensorHandle* tensor,
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TF_Status* status);
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// TODO: consider folding the 2 APIs below into the ones above.
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TF_CAPI_EXPORT extern void TFE_EnqueueVariantTensor(TF_Session* session,
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int tensor_id,
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TFE_TensorHandle* tensor,
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TF_Status* status);
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TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_DequeueVariantTensor(
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TF_Session* session, int tensor_id, TF_Status* status);
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TF_CAPI_EXPORT extern void TF_MakeInternalErrorStatus(TF_Status* status,
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TF_CAPI_EXPORT extern void TF_MakeInternalErrorStatus(TF_Status* status,
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const char* errMsg);
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const char* errMsg);
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@ -727,24 +727,6 @@ TFE_Context* TFE_NewContext(const TFE_ContextOptions* opts, TF_Status* status) {
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tensorflow::GetDefaultCustomKernelCreator()));
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tensorflow::GetDefaultCustomKernelCreator()));
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}
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}
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TFE_Context* TFE_NewContextFromSession(const TFE_ContextOptions* opts,
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TF_Session* sess, TF_Status* status) {
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const tensorflow::DeviceMgr* device_mgr = nullptr;
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status->status = sess->session->LocalDeviceManager(&device_mgr);
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if (!status->status.ok()) return nullptr;
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tensorflow::Rendezvous* r =
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new tensorflow::IntraProcessRendezvous(device_mgr);
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return tensorflow::wrap(new tensorflow::EagerContext(
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opts->session_options.options,
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static_cast<tensorflow::ContextDevicePlacementPolicy>(
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opts->device_placement_policy),
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static_cast<tensorflow::ContextMirroringPolicy>(opts->mirroring_policy),
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opts->async, opts->lazy_remote_inputs_copy, device_mgr,
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/*device_mgr_owned*/ false, r,
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tensorflow::GetDefaultCustomKernelCreator()));
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}
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void TFE_DeleteContext(TFE_Context* ctx) {
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void TFE_DeleteContext(TFE_Context* ctx) {
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if (ctx == nullptr) {
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if (ctx == nullptr) {
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return;
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return;
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