def demo(im_filename, out_filename, no_optimalisations):
from blip.code.trace_optimiser import Optimiser, ImmediatePass, PeepholePass, MemoryPass
from blip.simulator import interpreter
from blip.support import imageio
from blip.simulator.opcodes import Imm, Mul, Add
# settings
block_size = (32, 32)
out_ptr = block_size[0] * block_size[1]
coeff = [[1, -2, 1]] * 3
# convolution implementation with map_neighborhood_to_pixel skeleton
def convolution_op(code, coeff_v, val, acc, args, block_size):
""" Simple convolution implementation. """
with scoped_alloc(code, 2) as (v, coeff_r):
yield Imm(coeff_r, coeff_v)
yield Mul(v, coeff_r, val)
yield Add(acc, acc, v)
def codegen(code, block_size, args):
""" Map convolution to image. """
return map_neighborhood_to_pixel(code, 0, out_ptr, coeff, convolution_op, args, block_size)
# Wrap optimisers
optimiser = Optimiser(50)
optimiser.register_pass(ImmediatePass(optimiser))
# optimiser.register_pass(PeepholePass(optimiser))
optimiser.register_pass(MemoryPass(optimiser))
def optim_wrapper(code, block_size, args):
if no_optimalisations:
print "optimalisations disabled"
return codegen(code, block_size, args)
else:
return optimiser.run(code, codegen, block_size, args)
# Render instruction trace
f = open(out_filename + "_trace.txt", "w")
def tag_str(instr):
return ", ".join(instr.tag) if hasattr(instr, "tag") else ""
f.write("\n".join(str(x).ljust(40) + " tags: " + tag_str(x) for x in optim_wrapper(Code(), block_size, {})))
f.close()
# Run simulation
code = Code()
code.set_generator(optim_wrapper, block_size, {})
image = imageio.read(im_filename)
sim = interpreter.Interpreter(code, image, block_size)
sim.run()
out = sim.gen_output_image(1)
imageio.write(out_filename, out, 1)
def optimiser_wrapper(codegen): optimiser = Optimiser(400) # the loop hint doesn't improve the optimiser optimiser.register_pass(ImmediatePass(optimiser)) optimiser.register_pass(MemoryPass(optimiser)) # use this pass to avoid eliminate Nop annotations optimiser.register_pass(PeepholePass(optimiser)) def optim_wrapper(code, block_size, args): for x in optimiser.run(code, codegen, block_size, args): yield x return optim_wrapper
