def cached_solver(solver, neuron_type, gain, bias, x, targets,
rng=None, E=None):
try:
args, _, _, defaults = inspect.getargspec(solver)
except TypeError:
args, _, _, defaults = inspect.getargspec(solver.__call__)
args = args[-len(defaults):]
if rng is None and 'rng' in args:
rng = defaults[args.index('rng')]
if E is None and 'E' in args:
E = defaults[args.index('E')]
key = self._get_cache_key(
solver_fn, solver, neuron_type, gain, bias, x, targets, rng, E)
path = self._key2path(key)
try:
with open(path, 'rb') as f:
solver_info, decoders = nco.read(f)
except:
logger.info("Cache miss [{0}].".format(key))
decoders, solver_info = solver_fn(
solver, neuron_type, gain, bias, x, targets, rng=rng, E=E)
if not self.read_only:
with open(path, 'wb') as f:
nco.write(f, solver_info, decoders)
else:
logger.info(
"Cache hit [{0}]: Loaded stored decoders.".format(key))
return decoders, solver_info
def cached_solver(conn,
gain,
bias,
x,
targets,
rng=np.random,
**uncached_kwargs):
if not self._in_context:
warnings.warn("Cannot use cached solver outside of "
"`with cache` block.")
return solver_fn(conn,
gain,
bias,
x,
targets,
rng=rng,
**uncached_kwargs)
try:
key = self._get_cache_key(conn.solver,
conn.pre_obj.neuron_type, gain, bias,
x, targets, rng)
except FingerprintError as e:
logger.debug("Failed to generate cache key: %s", e)
return solver_fn(conn,
gain,
bias,
x,
targets,
rng=rng,
**uncached_kwargs)
try:
path, start, end = self._index[key]
if self._fd is not None:
self._fd.flush()
with open(path, 'rb') as f:
f.seek(start)
info, decoders = nco.read(f)
except Exception as err:
if isinstance(err, KeyError):
logger.debug("Cache miss [%s].", key)
else:
logger.exception("Corrupted cache entry [%s].", key)
decoders, info = solver_fn(conn,
gain,
bias,
x,
targets,
rng=rng,
**uncached_kwargs)
if not self.readonly:
fd = self._get_fd()
start = fd.tell()
nco.write(fd, info, decoders)
end = fd.tell()
self._index[key] = (fd.name, start, end)
else:
logger.debug("Cache hit [%s]: Loaded stored decoders.", key)
return decoders, info
def cached_solver(solver, neuron_type, gain, bias, x, targets,
rng=None, E=None):
try:
args, _, _, defaults = inspect.getargspec(solver)
except TypeError:
args, _, _, defaults = inspect.getargspec(solver.__call__)
args = args[-len(defaults):]
if rng is None and 'rng' in args:
rng = defaults[args.index('rng')]
if E is None and 'E' in args:
E = defaults[args.index('E')]
key = self._get_cache_key(
solver_fn, solver, neuron_type, gain, bias, x, targets, rng, E)
try:
path, start, end = self._index[key]
if self._fd is not None:
self._fd.flush()
with open(path, 'rb') as f:
f.seek(start)
solver_info, decoders = nco.read(f)
except:
logger.debug("Cache miss [%s].", key)
decoders, solver_info = solver_fn(
solver, neuron_type, gain, bias, x, targets, rng=rng, E=E)
if not self.readonly:
fd = self._get_fd()
start = fd.tell()
nco.write(fd, solver_info, decoders)
end = fd.tell()
self._index[key] = (fd.name, start, end)
else:
logger.debug("Cache hit [%s]: Loaded stored decoders.", key)
return decoders, solver_info
def cached_solver(solver, neuron_type, gain, bias, x, targets,
rng=None, E=None):
try:
args, _, _, defaults = inspect.getargspec(solver)
except TypeError:
args, _, _, defaults = inspect.getargspec(solver.__call__)
args = args[-len(defaults):]
if rng is None and 'rng' in args:
rng = defaults[args.index('rng')]
if E is None and 'E' in args:
E = defaults[args.index('E')]
key = self._get_cache_key(
solver_fn, solver, neuron_type, gain, bias, x, targets, rng, E)
path = self._key2path(key)
try:
with open(path, 'rb') as f:
solver_info, decoders = nco.read(f)
except:
logger.debug("Cache miss [{0}].".format(key))
decoders, solver_info = solver_fn(
solver, neuron_type, gain, bias, x, targets, rng=rng, E=E)
if not self.read_only:
with open(path, 'wb') as f:
nco.write(f, solver_info, decoders)
else:
logger.debug(
"Cache hit [{0}]: Loaded stored decoders.".format(key))
return decoders, solver_info
def cached_solver(conn, gain, bias, x, targets,
rng=None, E=None, **uncached_kwargs):
if not self._in_context:
warnings.warn("Cannot use cached solver outside of "
"`with cache` block.")
return solver_fn(conn, gain, bias, x, targets,
rng=rng, E=E, **uncached_kwargs)
try:
args, _, _, defaults = inspect.getargspec(conn.solver)
except TypeError:
args, _, _, defaults = inspect.getargspec(conn.solver.__call__)
args = args[-len(defaults):]
if rng is None and 'rng' in args:
rng = defaults[args.index('rng')]
if E is None and 'E' in args:
E = defaults[args.index('E')]
try:
key = self._get_cache_key(conn.solver,
conn.pre_obj.neuron_type,
gain,
bias,
x,
targets,
rng,
E)
except FingerprintError as e:
logger.debug("Failed to generate cache key: %s", e)
return solver_fn(conn, gain, bias, x, targets,
rng=rng, E=E, **uncached_kwargs)
try:
path, start, end = self._index[key]
if self._fd is not None:
self._fd.flush()
with open(path, 'rb') as f:
f.seek(start)
info, decoders = nco.read(f)
except Exception as err:
if isinstance(err, KeyError):
logger.debug("Cache miss [%s].", key)
else:
logger.exception("Corrupted cache entry [%s].", key)
decoders, info = solver_fn(conn, gain, bias, x, targets,
rng=rng, E=E, **uncached_kwargs)
if not self.readonly:
fd = self._get_fd()
start = fd.tell()
nco.write(fd, info, decoders)
end = fd.tell()
self._index[key] = (fd.name, start, end)
else:
logger.debug("Cache hit [%s]: Loaded stored decoders.", key)
return decoders, info
def test_nco_roundtrip(tmpdir):
tmpfile = tmpdir.join("test.nco")
pickle_data = {"0": 237, "str": "foobar"}
array = np.array([[4, 3], [2, 1]])
with tmpfile.open("wb") as f:
nco.write(f, pickle_data, array)
with tmpfile.open("rb") as f:
pickle_data2, array2 = nco.read(f)
assert pickle_data == pickle_data2
assert_equal(array, array2)
def test_nco_roundtrip(tmpdir):
tmpfile = tmpdir.join('test.nco')
pickle_data = {'0': 237, 'str': 'foobar'}
array = np.array([[4, 3], [2, 1]])
with tmpfile.open('wb') as f:
nco.write(f, pickle_data, array)
with tmpfile.open('rb') as f:
pickle_data2, array2 = nco.read(f)
assert pickle_data == pickle_data2
assert_equal(array, array2)
def cached_solver(solver,
neuron_type,
gain,
bias,
x,
targets,
rng=None,
E=None):
try:
args, _, _, defaults = inspect.getargspec(solver)
except TypeError:
args, _, _, defaults = inspect.getargspec(solver.__call__)
args = args[-len(defaults):]
if rng is None and 'rng' in args:
rng = defaults[args.index('rng')]
if E is None and 'E' in args:
E = defaults[args.index('E')]
key = self._get_cache_key(solver_fn, solver, neuron_type, gain,
bias, x, targets, rng, E)
try:
path, start, end = self._index[key]
if self._fd is not None:
self._fd.flush()
with open(path, 'rb') as f:
f.seek(start)
solver_info, decoders = nco.read(f)
except:
logger.debug("Cache miss [%s].", key)
decoders, solver_info = solver_fn(solver,
neuron_type,
gain,
bias,
x,
targets,
rng=rng,
E=E)
if not self.readonly:
fd = self._get_fd()
start = fd.tell()
nco.write(fd, solver_info, decoders)
end = fd.tell()
self._index[key] = (fd.name, start, end)
else:
logger.debug("Cache hit [%s]: Loaded stored decoders.", key)
return decoders, solver_info
def cached_solver(conn, gain, bias, x, targets,
rng=np.random, **uncached_kwargs):
if not self._in_context:
warnings.warn("Cannot use cached solver outside of "
"`with cache` block.")
return solver_fn(conn, gain, bias, x, targets,
rng=rng, **uncached_kwargs)
try:
key = self._get_cache_key(conn.solver,
conn.pre_obj.neuron_type,
gain,
bias,
x,
targets,
rng)
except FingerprintError as e:
logger.debug("Failed to generate cache key: %s", e)
return solver_fn(conn, gain, bias, x, targets,
rng=rng, **uncached_kwargs)
try:
path, start, end = self._index[key]
if self._fd is not None:
self._fd.flush()
with open(path, 'rb') as f:
f.seek(start)
info, decoders = nco.read(f)
except Exception as err:
if isinstance(err, KeyError):
logger.debug("Cache miss [%s].", key)
else:
logger.exception("Corrupted cache entry [%s].", key)
decoders, info = solver_fn(conn, gain, bias, x, targets,
rng=rng, **uncached_kwargs)
if not self.readonly:
fd = self._get_fd()
start = fd.tell()
nco.write(fd, info, decoders)
end = fd.tell()
self._index[key] = (fd.name, start, end)
else:
logger.debug("Cache hit [%s]: Loaded stored decoders.", key)
return decoders, info
