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)
