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tensorflow/c/c_api_experimental.cc
// below. Allocate enough space so that no reallocation happens, which will // make the pointers invalid. all_input_tensors.reserve(num_inputs); for (int i = 0; i < num_inputs; ++i) { if (input_tensors[i] == nullptr) continue; all_input_tensors.emplace_back(); Tensor& input_tensor = all_input_tensors.back(); status->status = TF_TensorToTensor(input_tensors[i], &input_tensor);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 29.4K bytes - Viewed (0) -
tensorflow/c/c_test_util.cc
return false; } } } return found_t && found_n; } bool IsNeg(const tensorflow::NodeDef& node_def, const string& input) { return node_def.op() == "Neg" && node_def.name() == "neg" && node_def.input_size() == 1 && node_def.input(0) == input; } bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def) { TF_Status* s = TF_NewStatus(); TF_Buffer* buffer = TF_NewBuffer();
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Oct 15 03:16:52 GMT 2021 - 17.8K bytes - Viewed (2) -
tensorflow/c/eager/gradients.cc
GradientFunction* gradient_function, const string& op_name) { std::vector<int64_t> input_ids(inputs.size()); std::vector<tensorflow::DataType> input_dtypes(inputs.size()); for (int i = 0; i < inputs.size(); i++) { input_ids[i] = ToId(inputs[i]); input_dtypes[i] = inputs[i]->DataType(); } std::vector<TapeTensor> tape_tensors; tape_tensors.reserve(outputs.size());
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 19.3K bytes - Viewed (0) -
tensorflow/c/c_api_function.cc
"Encountered while processing input ", i, " into function '", fn_name, "'"); TF_RETURN_WITH_CONTEXT_IF_ERROR(ValidateNonRefOutput(node, idx), "Encountered while processing input ", i, " into function '", fn_name, "'"); input_tensors->emplace_back(node, idx); const auto& iter = input_nodes->find(node); if (iter == input_nodes->end()) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 13.6K bytes - Viewed (2) -
tensorflow/c/eager/c_api_unified_experimental_test.cc
// Build an abstract input tensor. TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(eager_execution_ctx, status.get()); ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get()); TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, 2.0f); TF_AbstractTensor* input_t = TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get());
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri May 19 21:44:52 GMT 2023 - 39.1K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device.cc
implicitly_broadcast_tensors.reserve(inputs.size()); // not tight for (const auto& input : inputs) { if (absl::holds_alternative<TFE_TensorHandle*>(input)) { if (operation_name == std::string("_EagerConst")) { // Non-parallel tensors from _EagerConst/tf.constant are implicitly // broadcast, i.e. set as the input to each parallel operation. This
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Mar 29 22:05:31 GMT 2023 - 18.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api_distributed_test.cc
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 23.5K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib.cc
TFE_OpReset(op_.get(), operation_name, device_.c_str(), status); if (TF_GetCode(status) != TF_OK) return; } TFE_OpAddAttrs(op_.get(), attributes); for (int input_index = 0; input_index < inputs.size(); ++input_index) { TFE_OpAddInput(op_.get(), inputs[input_index], status); if (TF_GetCode(status) != TF_OK) return; } std::vector<TFE_TensorHandle*> unwrapped_results(expected_max_outputs);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Feb 09 07:47:20 GMT 2024 - 25.4K bytes - Viewed (1) -
tensorflow/c/c_api_experimental_test.cc
const std::vector<TF_Tensor*>& input_tensors, const absl::optional<std::vector<int64_t>>& expected_shape) { // Create input_shapes. TF_ShapeAndTypeList* input_shapes = TF_NewShapeAndTypeList(input_shapes_vec.size()); for (size_t i = 0; i < input_shapes_vec.size(); ++i) { const auto& input_shape = input_shapes_vec[i];
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/experimental/gradients/math_grad.cc
namespace gradients { namespace { static Status SafeConj(AbstractContext* ctx, AbstractTensorHandle* const input, AbstractTensorHandle** output, const char* name) { auto dtype = input->DataType(); if (DataTypeIsFloating(BaseType(dtype)) || DataTypeIsInteger(BaseType(dtype))) { return tensorflow::ops::Identity(ctx, input, output, name); } else if (!DataTypeIsComplex(BaseType(dtype)) &&
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 15.2K bytes - Viewed (0)