====================
Interactive Debugger
====================

'''Seed of discussion for what an interactive debugging tool might look like. 2009.03.27.'''

== Interactive debugger ( #352 ) ==

The interactive debugger should allow the user to go step by step in a graph to debug it. It should allow setting breakpoints on arbitrary Ops or subgraphs. If we can group ops by the user's function that defined them, we could have a logical grouping of the graph into subgraphs.

The debugger should save the inputs at each step so the user loses no info through inplace operations. Ideally, the debugger should be a normal python shell enriched with commands to control the flow and all the inputs should be made available so the user can use numpy interactively on them.

Command wishlist
 * py_perform (perform the current operation using the python implementation)
 * c_perform (perform the current operation using the C implementation)
 * perform (use the Linker's preference)
 * get_inputs (get the inputs of the current op)
 * set_inputs (set the inputs of the current op)
 * get_outputs (get the outputs of the current op)
 * set_outputs (set the outputs of the current op (bypasses its perform))
 * next (perform and go to the next breakpoint)
 * breakpoint (set a breakpoint on the current Op or subgraph)
 * step (perform and go to the next Op or subgraph)
 * step_in (go to the first Op inside the current subgraph)
 * step_out (exit the subgraph containing this Op)
 * Of course, normal python shell functionality!
 * The global context where the debugger was called (so the user can define his own helper functions, etc.)

A good, simple way to do it would be to have those commands as methods of a structure that would be returned by a DebugLinker. This would allow an interactive session like the following:

{{{
>>> a, b, c = Tensor(), Tensor(), Tensor()
>>> d = b * c
>>> e = a + d
>>> debug = DebugLinker(Env([a, b, c], [e])).make_function()
>>> debug.set_breakpoint(d)
>>> debug.debug(10, 20, 30) # a, b, c = 10, 20, 30
Now at: Mul(b, c)
Context: d = b * c
>>> debug.get_inputs() # we are at the node d = b * c
[20, 30]
>>> debug.get_outputs()
[None]
>>> debug.py_perform()
>>> debug.get_outputs()
[600]
>>> debug.step()
Now at: Add(a, Mul)
Context: e = a + d
>>> debug.get_inputs()
[30, 600]
>>> debug.step()
Finished.
[630]
>>>
}}}


