public GradLoopState(WhileContext forward_ctxt, GradLoopState outer_grad_state_)
{
// Information needed by backprop.
_unused_exits = new List <Tensor>();
_deferred_exits = new List <Tensor>();
_forward_loop_exits = list(forward_ctxt.loop_exits);
pending_exits_count = len(forward_ctxt.loop_exits);
_outer_grad_state = outer_grad_state_;
ControlFlowContext outer_forward_ctxt = null;
if (outer_grad_state_ != null)
{
outer_forward_ctxt = outer_grad_state_.forward_context;
}
// Add the forward loop counter.
// with forward_ctxt._graph.as_default():
Tensor cnt, forward_index;
{
if (outer_forward_ctxt != null)
{
outer_forward_ctxt.Enter();
}
(cnt, forward_index) = forward_ctxt.AddForwardLoopCounter(outer_grad_state);
if (outer_forward_ctxt != null)
{
outer_forward_ctxt.Exit();
}
}
_forward_context = forward_ctxt;
_forward_index = forward_index;
// Add the backprop WhileContext, and the backprop loop counter.
if (outer_grad_state != null)
{
// This is a nested loop. Remember the iteration counts for each
// execution of this inner loop.
throw new NotImplementedException("GradLoopState");
}
else
{
if (outer_forward_ctxt != null)
{
outer_forward_ctxt.Enter();
}
_grad_context = new WhileContext(
maximum_iterations: forward_ctxt.maximum_iterations,
parallel_iterations: forward_ctxt.parallel_iterations,
back_prop: forward_ctxt.back_prop,
swap_memory: forward_ctxt.swap_memory,
name: forward_ctxt.Name,
grad_state: this);
_grad_index = _grad_context.AddBackpropLoopCounter(cnt, outer_grad_state);
if (outer_forward_ctxt != null)
{
outer_forward_ctxt.Exit();
}
}
}
