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Results 1 - 10 of 14 for new_retvals (0.27 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/resource_op_lifting.cc
for (auto branch : branches) { auto new_retvals = llvm::to_vector<4>(branch.front().getTerminator()->getOperands()); new_retvals.resize(new_retvals.size() + resource_arg_to_new_output.size()); for (const auto& entry : resource_arg_to_new_output) { int64_t resource_arg_index = entry.getFirst(); int64_t output_index = entry.getSecond(); new_retvals[output_index] = branch.getArgument(resource_arg_index);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 55.1K bytes - Viewed (0) -
tensorflow/c/experimental/ops/gen/cpp/golden/testing_ops.cc.golden
TF_RETURN_IF_ERROR(op_ptr->Reset("Neg", raw_device_name)); TF_RETURN_IF_ERROR(MaybeSetOpName(op_ptr.get(), name)); TF_RETURN_IF_ERROR(op_ptr->AddInput(x)); int num_retvals = 1; return op_ptr->Execute(absl::MakeSpan(y, 1), &num_retvals); } // Op: MatMul() // Summary: // // Description:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 6.5K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/core/ops/variable_ops.cc
strlen(ResourceHandle::ANONYMOUS_NAME))); AbstractTensorHandle* var_handle = nullptr; int num_retvals = 1; TF_RETURN_IF_ERROR(varhandle_op->Execute( absl::MakeSpan(&var_handle, num_retvals), &num_retvals)); AbstractTensorHandlePtr owned_var_handle(var_handle); if (!tensorflow::isa<ImmediateExecutionTensorHandle>( owned_var_handle.get())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 11:28:19 UTC 2024 - 5K bytes - Viewed (0) -
tensorflow/c/experimental/ops/gen/cpp/renderers/op_implementation_renderer.cc
ArgView output_arg = op_.OnlyOutput(); Statement("int num_retvals = $0.size()", output_arg.VariableName()); Statement("return " + Call(op_.VariableName(), "Execute", {output_arg.VariableName(), "&num_retvals"})); } void OpImplementationRenderer::RenderExecutionSingleOutput() { ArgView output_arg = op_.OnlyOutput(); Statement("int num_retvals = 1");
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 28 05:51:40 UTC 2024 - 3.7K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.cc
} if (TF_GetCode(status) != TF_OK) return nullptr; TFE_TensorHandle* var_handle = nullptr; int num_retvals = 1; TFE_Execute(op, &var_handle, &num_retvals, status); if (TF_GetCode(status) != TF_OK) return nullptr; TFE_DeleteOp(op); if (TF_GetCode(status) != TF_OK) return nullptr; CHECK_EQ(1, num_retvals); // Assign 'value' to it. op = TFE_NewOp(ctx, "AssignVariableOp", status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 22:37:46 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/internal/saved_model_api_test.cc
// TODO(bmzhao): Finish API on FunctionMetadata args, so we know how many // inputs + outputs a function has. TFE_TensorHandle* compute_fn_outputs[1] = {nullptr}; int num_retvals = 1; TFE_Execute(compute_fn_op, &compute_fn_outputs[0], &num_retvals, status); EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); TF_Tensor* result = TFE_TensorHandleResolve(compute_fn_outputs[0], status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 08:08:45 UTC 2024 - 21.3K bytes - Viewed (0) -
tensorflow/c/eager/c_api_distributed_test.cc
ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); } TFE_TensorHandle* retvals[1] = {nullptr}; int num_retvals = 1; TFE_Execute(func, &retvals[0], &num_retvals, status); EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); ASSERT_EQ(1, num_retvals); TFE_DeleteOp(func); TFE_DeleteTensorHandle(packed_handle); TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/tape/tape_operation.cc
AbstractOperation* TapeOperation::GetBackingOperation() { return parent_op_; } Status TapeOperation::Execute(absl::Span<AbstractTensorHandle*> retvals, int* num_retvals) { TF_RETURN_IF_ERROR(parent_op_->Execute(retvals, num_retvals)); for (int i = 0; i < *num_retvals; i++) { // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs. forward_op_.outputs.push_back(retvals[i]); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 06:16:45 UTC 2024 - 9K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_xla_computations_pass.cc
NodeDef* call_def) { Graph* graph = graph_ptr->get(); const int num_args = input_permutation->size(); const int num_retvals = output_permutation->size(); std::vector<Node*> args; std::vector<Node*> retvals; args.reserve(num_args); retvals.reserve(num_retvals); for (Node* n : graph->nodes()) { if (n->type_string() == "_Arg") { // Check if this is a guaranteed constant.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 15.1K bytes - Viewed (0) -
tensorflow/c/eager/gradients_test.cc
ASSERT_EQ(errors::OK, s.code()) << s.message(); int num_retvals = 1; std::vector<AbstractTensorHandle*> outputs(1); GradientRegistry registry; s = RegisterGradients(®istry); ASSERT_EQ(errors::OK, s.code()) << s.message(); auto tape = std::make_unique<Tape>(/*persistent=*/false); s = Execute(check_numerics_op.get(), ctx.get(), absl::MakeSpan(outputs), &num_retvals, &forward_op, tape.get(), registry);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 7K bytes - Viewed (0)