def gen_program_worker(input_types):
"""
Generate programs with the given input types.
Statements are generated by choosing a function randomly, and then sampling parameters so that
unused variables take precedence. Programs that has unused variables are discarded.
"""
def helper(functions, program, programs):
random.shuffle(functions)
if progress_counter.value >= num_programs:
return True
if len(program) >= program_len:
if get_unused_indices(program) or program in programs:
return False
else:
programs.add(program)
progress_counter.value += 1
print("\rGenerating programs... %d\\%d" %
(progress_counter.value, num_programs),
end="")
return True
type_to_vars = collections.defaultdict(list)
for i, typ in enumerate(program.var_types):
type_to_vars[typ].insert(0, i)
# Move free indices to the front
free_indxs = get_free_indices(program, program_len)
for typ in program.var_types:
for var in type_to_vars[typ]:
if var in free_indxs:
type_to_vars[typ].remove(var)
type_to_vars[typ].insert(0, var)
for func in LAMBDAS:
type_to_vars[func.type].append(func)
used = set(program.statements)
for function in functions:
for args in iterate_inputs(function, type_to_vars):
if len([arg for arg in args if arg in free_indxs]) == 0:
continue
statement = Statement(function, args)
if statement in used:
continue
next_program = Program(program.input_types,
program.statements + [statement])
if helper(functions, next_program, programs):
return True
program_base = Program(input_types, [])
res = set()
while progress_counter.value < num_programs:
helper(ALL_FUNCTIONS, program_base, res)
return res
def helper(functions, program, programs):
random.shuffle(functions)
if progress_counter.value >= num_programs:
return True
if len(program) >= program_len:
if get_unused_indices(program) or program in programs:
return False
else:
programs.add(program)
progress_counter.value += 1
print("\rGenerating programs... %d\\%d" %
(progress_counter.value, num_programs),
end="")
return True
type_to_vars = collections.defaultdict(list)
for i, typ in enumerate(program.var_types):
type_to_vars[typ].insert(0, i)
# Move free indices to the front
free_indxs = get_free_indices(program, program_len)
for typ in program.var_types:
for var in type_to_vars[typ]:
if var in free_indxs:
type_to_vars[typ].remove(var)
type_to_vars[typ].insert(0, var)
for func in LAMBDAS:
type_to_vars[func.type].append(func)
used = set(program.statements)
for function in functions:
for args in iterate_inputs(function, type_to_vars):
if len([arg for arg in args if arg in free_indxs]) == 0:
continue
statement = Statement(function, args)
if statement in used:
continue
next_program = Program(program.input_types,
program.statements + [statement])
if helper(functions, next_program, programs):
return True
def tokens_to_program(seq, input_types):
tokens = [reverse_program_vocab[token] for token in seq]
if tokens[0] == START_PROGRAM_TOKEN:
tokens = tokens[1:]
indx = 0
statements = []
while indx < len(tokens) and tokens[indx] != END_PROGRAM_TOKEN:
token = tokens[indx]
if not token in ALL_FUNCTIONS:
return None
if isinstance(token.input_type, tuple):
num_args = len(token.input_type)
else:
num_args = 1
args = tokens[indx + 1:indx + 1 + num_args]
statements.append(Statement(token, args))
indx = indx + 1 + num_args
return Program(input_types, statements)
def solve_problem_worker(data):
examples = Example.from_line(data)
env = ProgramEnv(examples)
if method == 'beam':
solution = cab(env, max_program_len, model, params.cab_beam_size, params.cab_width,
params.cab_width_growth, timeout, max_beam_size=max_beam_size)
elif method == 'dfs':
solution = dfs(env, max_program_len, model, params.dfs_max_width, timeout)
counter.value += 1
print("\rSolving problems... %d (failed: %d)" % (counter.value, fail_counter.value), end="")
if solution['result'] is False:
solution['result'] = "Failed"
fail_counter.value += 1
else:
values = [Value.construct(x) for x in data['examples'][0]['inputs']]
value_types = [x.type for x in values]
solution['result'] = Program(value_types, solution['result']).encode()
return solution
def solve_problem_worker(args):
line, input, input_lens, output, output_lens, input_masks, output_masks = args
examples = Example.from_line(line)
sol = Program.parse(line['program'])
env = ProgramEnv(examples)
res = robustfill_cab(env, program_len, model, 100, 48, timeout, input,
input_lens, output, output_lens, input_masks,
output_masks)
counter.value += 1
print("\rSolving problems... %d (failed: %d)" %
(counter.value, fail_counter.value),
end="")
if res['result'] is None:
res['result'] = "Failed"
fail_counter.value += 1
return res
else:
res['result'] = str(Program(sol.input_types, res['result']))
return res