code: def __post_init__(self):
      super().__post_init__()
      self._possible_values["gpus"] = possible_values.String(
          values=tuple(
              [
                  (str(x), f"GPU #{x+1}")
                  for x in range(torch.cuda.device_count())
              ]
          ),
          allow_custom=False,
      )
  
      self._possible_values["number_of_workers"] = (
          1,
          multiprocessing.cpu_count(),
          1,
      )
      self._possible_values["seed"] = possible_values.Number(
          step=1, min=-1
      )
      self._possible_values[
          "deepspeed_reduce_bucket_size"
      ] = possible_values.Number(step=1, min=1e6)
      self._possible_values[
          "deepspeed_stage3_prefetch_bucket_size"
      ] = possible_values.Number(step=1, min=1e6)
      self._possible_values[
          "deepspeed_stage3_param_persistence_threshold"
      ] = possible_values.Number(step=1, min=1e6)
      self._possible_values[
          "deepspeed_stage3_max_live_parameters"
      ] = possible_values.Number(step=1, min=1e6)
      self._possible_values[
          "deepspeed_stage3_max_reuse_distance"
      ] = possible_values.Number(step=1, min=1e6)
      self._nesting.add(
          [
              "deepspeed_reduce_bucket_size",
              "deepspeed_stage3_prefetch_bucket_size",
              "deepspeed_stage3_param_persistence_threshold",
              # "deepspeed_offload_optimizer",
          ],
          [Dependency(key="use_deepspeed", value=False, is_set=False)],
      )
  
imports: import multiprocessing
  import os
  from dataclasses import dataclass, field
  from typing import Any, Dict, List, Tuple
  import torch
  import llm_studio.src.datasets.text_causal_language_modeling_ds
  from llm_studio.python_configs.base import DefaultConfig, DefaultConfigProblemBase
  from llm_studio.src import possible_values
  from llm_studio.src.augmentations.nlp_aug import BaseNLPAug
  from llm_studio.src.loggers import Loggers
  from llm_studio.src.losses import text_causal_language_modeling_losses
  from llm_studio.src.metrics import text_causal_language_modeling_metrics
  from llm_studio.src.models import text_causal_language_modeling_model
  from llm_studio.src.nesting import Dependency
  from llm_studio.src.optimizers import Optimizers
  from llm_studio.src.plots import text_causal_language_modeling_plots
  from llm_studio.src.schedulers import Schedulers
  from llm_studio.src.utils.modeling_utils import generate_experiment_name
label_desc: Use image node_id 1 for calling the ConfigNLPCausalLMEnvironment obj's underlying member method code with example usage: obj.__post_init__() without return types