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tensorflow/c/c_api.cc
// directly, instead of requiring us to serialize to a GraphDef and // call Session::Extend(). bool ExtendSessionGraphHelper(TF_Session* session, TF_Status* status) { if (session->graph != nullptr) { // Take the graph lock before the session lock to avoid deadlock. This is // safe since session->graph does not change. session->graph->mu.lock(); mutex_lock session_lock(session->mu);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 102.3K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/grad_test_helper.cc
absl::Span<AbstractTensorHandle*> outputs) -> Status { Tape tape(/*persistent=*/false); for (size_t i{}; i < inputs.size(); ++i) { tape.Watch(inputs[i]); } std::vector<AbstractTensorHandle*> temp_outputs(1); AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry)); TF_RETURN_IF_ERROR( forward_model(tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs)));
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/custom_gradient_test.cc
Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); // Watch x. AbstractTensorHandle* exp_output; TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp")); std::unique_ptr<GradientFunction> gradient_function( new PassThroughGradientFunction); tape.RecordOperation(inputs, {exp_output}, gradient_function.release()); TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 4.8K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad_test.cc
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h" #include "tensorflow/c/eager/unified_api_testutil.h" #include "tensorflow/c/experimental/gradients/grad_test_helper.h" #include "tensorflow/c/experimental/gradients/tape/tape_context.h" #include "tensorflow/c/experimental/ops/math_ops.h" #include "tensorflow/c/tf_status_helper.h" #include "tensorflow/core/platform/tensor_float_32_utils.h" #include "tensorflow/core/platform/test.h"
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Apr 13 17:32:14 GMT 2023 - 16.3K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib_test.cc
ParallelTensor::FromTensorHandles(parallel_device, std::move(mixed_handles), status.get()); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK); // Can't take the shape of a parallel tensor with varying numbers of axes, but // running operations on them is OK. TF_ASSERT_OK(unknown_length_vector->Shape(&shape)); EXPECT_THAT(*shape, ElementsAre(-1));
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Jul 08 23:47:35 GMT 2021 - 15.3K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.cc
std::vector<Tensor> all_input_tensors; // Update the vector with information from `input_tensors` if provided. if (input_tensors != nullptr) { // Note that we take the address of the elements in `all_input_tensors` // below. Allocate enough space so that no reallocation happens, which will // make the pointers invalid. all_input_tensors.reserve(num_inputs);
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/eager/gradients_test.cc
absl::Span<AbstractTensorHandle*> outputs) { Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); AbstractTensorHandle* neg_output; TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg")); tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg"); return tape.ComputeGradient(ctx, /*targets=*/{neg_output},
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
theta_inputs[input_index] = thetaMinus.get(); TF_RETURN_IF_ERROR( RunAndMaybeSum(ctx, forward, theta_inputs, f_outputs, use_function)); AbstractTensorHandlePtr fMinus(f_outputs[0]); // Take Difference of both estimates: (f(theta + eps) - f(theta - eps)). TF_RETURN_IF_ERROR( ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top")); AbstractTensorHandlePtr fDiff(f_outputs[0]);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/experimental/filesystem/modular_filesystem_registration.cc
return OkStatus(); } // Validates the operations supplied by the plugin. // // Uses the 4 simpler `ValidateHelper(const TF_...*)` to validate each // individual function table and then checks that the function table for a // specific file type exists if the plugin offers support for creating that // type of files. static Status ValidateOperations(const TF_FilesystemPluginOps* ops) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 07 22:08:43 GMT 2023 - 12.8K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/tape/tape_operation.cc
==============================================================================*/ #include "tensorflow/c/experimental/gradients/tape/tape_operation.h" #include "tensorflow/c/eager/abstract_context.h" #include "tensorflow/c/eager/gradients.h" namespace tensorflow { namespace gradients { TapeOperation::TapeOperation(AbstractOperation* parent_op, Tape* tape, const GradientRegistry& registry) : AbstractOperation(kTape),
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Tue Jun 07 01:53:35 GMT 2022 - 9K bytes - Viewed (1)