def test_reproducibility(self, xor_trial_controller: Callable) -> None: def controller_fn(workloads: workload.Stream) -> det.TrialController: return xor_trial_controller(self.hparams, workloads, batches_per_step=100) utils.reproducibility_test( controller_fn=controller_fn, steps=3, validation_freq=1, batches_per_step=100 )
def test_reproducibility(self, xor_trial_controller: Callable) -> None: def controller_fn(workloads: workload.Stream) -> det.TrialController: return xor_trial_controller( self.hparams, workloads, scheduling_unit=100, trial_seed=self.trial_seed ) utils.reproducibility_test( controller_fn=controller_fn, steps=3, validation_freq=1, scheduling_unit=100 )
def test_reproducibility(self) -> None: def controller_fn(workloads: workload.Stream) -> det.TrialController: return utils.make_trial_controller_from_trial_implementation( trial_class=pytorch_xor_model.XORTrial, hparams=self.hparams, workloads=workloads, trial_seed=self.trial_seed, ) utils.reproducibility_test(controller_fn, steps=1000, validation_freq=100)
def test_reproducibility(self) -> None: def controller_fn(workloads: workload.Stream) -> determined.TrialController: return utils.make_trial_controller_from_trial_implementation( trial_class=deepspeed_linear_model.LinearPipelineEngineTrial, hparams=self.hparams, workloads=workloads, trial_seed=self.trial_seed, expose_gpus=True, ) utils.reproducibility_test(controller_fn, steps=1000, validation_freq=100)