def roi_compute(self, user_input: OpuUserInput):
# with automatic input roi, compute number of ones before
# This case is met only when input is provided to runner creation
# (i.e. opu.fit with an input)
#
# Count number of ones, and then compute ROI with "auto" strategy
roi = InputRoi(self.s.input_shape, self.s.ones_range)
n_ones = self._count_ones(user_input.reshape_input(), user_input.traits.packed)
n_features_s = self._traits.n_features_s
self._debug("Counted an average of"
" {:.2f} ones in input of size {} ({:.2f}%)."
.format(n_ones, n_features_s, 100 * n_ones / n_features_s))
return roi.compute_roi(self.t.input_roi_strategy,
self._traits.n_features, n_ones, self.ones_info)
def transform(self, input_vectors: OpuUserInput, linear=False):
"""Do the OPU transform of input
If batch transform, device acquisition must be started
"""
assert self.device.active and input_vectors.traits == self._traits
if not self.s.simulated:
input_vectors.binary_check()
else:
# In simulated mode, SimulatedDevice must whether the transform is linear or not
self.device._linear = linear
context = self._get_context()
self._pre_print(self.device, input_vectors.n_samples)
X = input_vectors.reshape_input()
if input_vectors.is_batch:
t0 = time.time()
nb_retries = 0
# Batch transform, allocate the result, progress bar, and start acquisition
# allocation of empty vector for iteration
n_samples = input_vectors.n_samples_s
Y = np.empty((n_samples, self._out_size),
dtype=self.device.output_dtype)
self._trace("Y allocated")
indices = self.indices(input_vectors.n_samples_s)
with Progress(n_samples, "OPU: transform", self.disable_pbar) as p:
# iterate over consecutive pairs of indices
# (https://stackoverflow.com/a/21303286)
for i, (start, end) in enumerate(zip(indices, indices[1:])):
c = self.__batch_transform(X[start:end], Y[start:end], i)
p.update(end - start)
nb_retries += c
t1 = time.time()
# Fill context from opu settings at the end of the transform
context.from_opu(self.device, dt.datetime.fromtimestamp(t0),
dt.datetime.fromtimestamp(t1))
else:
Y, nb_retries = self.__single_transform(X)
context.from_opu(self.device, dt.datetime.now())
if nb_retries:
self._print("OPU number of retries: ", nb_retries)
return ContextArray(Y, context)