24 """Send the `value` - currently just a scalar - formatted as per `spec`."""
27 assert spec.element_type == ctypes.c_int64
28 to_send = ctypes.c_int64(int(value))
29 assert f.write(bytes(to_send)) == ctypes.sizeof(spec.element_type) * math.prod(
38 process_and_args: List[str],
42 temp_rootname: the base file name from which to construct the 2 pipes for
43 communicating with the compiler.
44 make_response: a function that, given the current tensor values, provides a
46 process_and_args: the full commandline for the compiler. It it assumed it
47 contains a flag poiting to `temp_rootname` so that the InteractiveModeRunner
48 would attempt communication on the same pair as this function opens.
50 This function sets up the communication with the compiler - via 2 files named
51 `temp_rootname`.in and `temp_rootname`.out - prints out the received features,
52 and sends back to the compiler an advice (which it gets from `make_response`).
53 It's used for testing, and also to showcase how to set up communication in an
54 interactive ML ("gym") environment.
56 to_compiler = temp_rootname +
".in"
57 from_compiler = temp_rootname +
".out"
59 os.mkfifo(to_compiler, 0o666)
60 os.mkfifo(from_compiler, 0o666)
61 compiler_proc = subprocess.Popen(
62 process_and_args, stderr=subprocess.PIPE, stdout=subprocess.DEVNULL
64 with io.BufferedWriter(io.FileIO(to_compiler,
"wb"))
as tc:
65 with io.BufferedReader(io.FileIO(from_compiler,
"rb"))
as fc:
68 while compiler_proc.poll()
is None:
69 next_event = fc.readline()
78 context, next_event, fc, tensor_specs,
None
80 if last_context != context:
81 print(f
"context: {last_context}")
82 context = last_context
83 print(f
"observation: {observation_id}")
87 tensor_values.append(fv)
88 send(tc, make_response(tensor_values), advice_spec)
89 _, err = compiler_proc.communicate()
90 print(err.decode(
"utf-8"))
94 os.unlink(to_compiler)
95 os.unlink(from_compiler)