def run(self, shape):
init_sampler = self.make_sampler("bach", temperature=FLAGS.temperature)
pianorolls, masks = self.blank_slate(shape)
pianorolls = init_sampler(pianorolls, masks)
masks = lib_sampling.HarmonizationMasker()(shape)
gibbs = self.make_sampler(
"gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler("independent", temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = gibbs(pianorolls, masks)
with self.logger.section("result"):
self.logger.log(
pianorolls=pianorolls, masks=masks, predictions=pianorolls)
return pianorolls
def run(self, tuple_in):
shape, midi_in = tuple_in
pianorolls = self.decoder.encode_midi_to_pianoroll(midi_in, shape)
# fill in the silences
masks = lib_sampling.CompletionMasker()(pianorolls)
gibbs = self.make_sampler("gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler(
"independent",
temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context,
masks=masks,
predictions=context)
pianorolls = gibbs(pianorolls, masks)
with self.logger.section("result"):
self.logger.log(pianorolls=pianorolls,
masks=masks,
predictions=pianorolls)
return pianorolls
def run(self, shape):
init_sampler = self.make_sampler("bach", temperature=FLAGS.temperature)
pianorolls, masks = self.blank_slate(shape)
pianorolls = init_sampler(pianorolls, masks)
masks = lib_sampling.HarmonizationMasker()(shape)
gibbs = self.make_sampler("gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler(
"independent",
temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context,
masks=masks,
predictions=context)
pianorolls = gibbs(pianorolls, masks)
with self.logger.section("result"):
self.logger.log(pianorolls=pianorolls,
masks=masks,
predictions=pianorolls)
return pianorolls
def run(self, shape):
init_sampler = self.make_sampler("bach", temperature=FLAGS.temperature)
pianorolls, masks = self.blank_slate(shape)
pianorolls = init_sampler(pianorolls, masks)
sampler = self.make_sampler("gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler(
"independent",
temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
for i in range(shape[-1]):
masks = lib_sampling.InstrumentMasker(instrument=i)(shape)
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context,
masks=masks,
predictions=context)
pianorolls = sampler(pianorolls, masks)
return pianorolls
def run(self, tuple_in):
try:
shape, midi_in = tuple_in
mroll = self.load_midi_melody(midi_in)
except:
shape = tuple_in
mroll = self.load_midi_melody(None)
pianorolls = self.make_pianoroll_from_melody_roll(mroll, shape)
masks = lib_sampling.HarmonizationMasker()(pianorolls.shape)
gibbs = self.make_sampler("gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler(
"independent",
temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context,
masks=masks,
predictions=context)
pianorolls = gibbs(pianorolls, masks)
return pianorolls
def run(self, pianorolls):
# fill in the silences
masks = lib_sampling.CompletionMasker()(pianorolls)
gibbs = self.make_sampler(
"gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler("independent", temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = gibbs(pianorolls, masks)
with self.logger.section("result"):
self.logger.log(
pianorolls=pianorolls, masks=masks, predictions=pianorolls)
return pianorolls
def run(self, tuple_in):
shape, midi_in = tuple_in
mroll = self.load_midi_melody(midi_in)
pianorolls = self.make_pianoroll_from_melody_roll(mroll, shape)
masks = lib_sampling.HarmonizationMasker()(pianorolls.shape)
gibbs = self.make_sampler(
"gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler("independent", temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = gibbs(pianorolls, masks)
return pianorolls
def _run(self, pianorolls, masks=1.):
if not np.all(masks):
raise NotImplementedError()
masks = np.ones_like(pianorolls)
with self.logger.section("sequence"):
while pianorolls.shape[1] < self.desired_length:
# upsample by zero-order hold and mask out every second time step
pianorolls = np.repeat(pianorolls, 2, axis=1)
masks = np.repeat(masks, 2, axis=1)
masks[:, 1::2] = 1
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = self.sampler(pianorolls, masks)
masks = np.zeros_like(masks)
return pianorolls
def _run(self, pianorolls, masks=1.):
if not np.all(masks):
raise NotImplementedError()
masks = np.ones_like(pianorolls)
with self.logger.section("sequence"):
while pianorolls.shape[1] < self.desired_length:
# upsample by zero-order hold and mask out every second time step
pianorolls = np.repeat(pianorolls, 2, axis=1)
masks = np.repeat(masks, 2, axis=1)
masks[:, 1::2] = 1
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = self.sampler(pianorolls, masks)
masks = np.zeros_like(masks)
return pianorolls
def run(self, shape):
init_sampler = self.make_sampler("bach", temperature=FLAGS.temperature)
pianorolls, masks = self.blank_slate(shape)
pianorolls = init_sampler(pianorolls, masks)
sampler = self.make_sampler(
"gibbs",
masker=lib_sampling.BernoulliMasker(),
sampler=self.make_sampler("independent", temperature=FLAGS.temperature),
schedule=lib_sampling.YaoSchedule())
for i in range(shape[-1]):
masks = lib_sampling.InstrumentMasker(instrument=i)(shape)
with self.logger.section("context"):
context = np.array([
lib_mask.apply_mask(pianoroll, mask)
for pianoroll, mask in zip(pianorolls, masks)
])
self.logger.log(pianorolls=context, masks=masks, predictions=context)
pianorolls = sampler(pianorolls, masks)
return pianorolls
