def _plan_PresentInput(self, ops): ps = [op.process for op in ops] Y = self.all_data[[self.sidx[op.output] for op in ops]] t = self.all_data[[self.sidx[self._step] for _ in ops]] inputs = self.RaggedArray([p.inputs.reshape(p.inputs.shape[0], -1) for p in ps], dtype=np.float32) pres_t = self.Array([p.presentation_time for p in ps]) dt = self.model.dt return [plan_presentinput(self.queue, Y, t, inputs, dt, pres_t=pres_t)]
def _plan_PresentInput(self, ops): ps = [op.process for op in ops] Y = self.all_data[[self.sidx[op.output] for op in ops]] t = self.all_data[[self.sidx[self.model.step] for _ in ops]] inputs = self.RaggedArray( [p.inputs.reshape(p.inputs.shape[0], -1) for p in ps], dtype=np.float32) pres_t = self.Array([p.presentation_time for p in ps]) dt = self.model.dt return [plan_presentinput(self.queue, Y, t, inputs, dt, pres_t=pres_t)]
def _plan_WhiteSignal(self, ops): Y = self.all_data[[self.sidx[op.output] for op in ops]] t = self.all_data[[self.sidx[self._step] for _ in ops]] dt = self.model.dt signals = [] for op in ops: assert op.input is None and op.output is not None f = op.process.make_step(0, op.output.size, dt, self.rng) signals.append(get_closures(f)['signal']) signals = self.RaggedArray(signals, dtype=np.float32) return [plan_presentinput(self.queue, Y, t, signals, dt)]