[NeMo-UX] Match nemo 1's default behavior for drop_last and pad_samples_to_global_batch_size

[ashors1]

This PR updates the default behavior of NeMo-UX's dataloader to match NeMo 1's. See

NeMo/nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py

Lines 1552 to 1579 in d4d0385

	def build_pretraining_data_loader(
	self, dataset, consumed_samples, dataset_type=None, drop_last=True, pad_samples_to_global_batch_size=False
	):
	"""Buld dataloader given an input dataset."""
	logging.info(f'Building dataloader with consumed samples: {consumed_samples}')
	# Megatron sampler
	if hasattr(self.cfg.data, 'dataloader_type') and self.cfg.data.dataloader_type is not None:
	if self.cfg.data.dataloader_type == 'single':
	batch_sampler = MegatronPretrainingSampler(
	total_samples=len(dataset),
	consumed_samples=consumed_samples,
	micro_batch_size=self.cfg.micro_batch_size,
	data_parallel_rank=parallel_state.get_data_parallel_rank(),
	data_parallel_size=parallel_state.get_data_parallel_world_size(),
	drop_last=drop_last,
	global_batch_size=self.cfg.global_batch_size,
	rampup_batch_size=self.cfg.get('rampup_batch_size', None),
	pad_samples_to_global_batch_size=pad_samples_to_global_batch_size,
	)
	elif self.cfg.data.dataloader_type == 'cyclic':
	batch_sampler = MegatronPretrainingRandomSampler(
	total_samples=len(dataset),
	consumed_samples=consumed_samples,
	micro_batch_size=self.cfg.micro_batch_size,
	data_parallel_rank=parallel_state.get_data_parallel_rank(),
	data_parallel_size=parallel_state.get_data_parallel_world_size(),
	drop_last=self.cfg.get('drop_last', True),

.

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[cuichenx]

LGTM Thanks!