class_docstr: Models a simple one variable(y = wx) neural network, and a MSE loss function.
class_docstr_tok: ["Models","a","simple","one","variable","(","y","=","wx",")","neural","network",",","and","a","MSE","loss","function","."]
code: def __init__(self, context) -> None:
      self.context = context
      self.my_batch_size = (
          self.context.get_per_slot_batch_size()
      )  # type: int
      self.my_lr = self.context.get_hparams()["learning_rate"]
      self.context.env.container_gpus = []
  
file_path: determined/harness/tests/experiment/fixtures/ancient-checkpoints/0.17.6-keras/code/model_def.py
imports: import numpy
  import tensorflow
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.losses import mean_squared_error
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.optimizers.legacy import SGD
  from tensorflow.keras.utils import Sequence
  from determined.keras import TFKerasTrial
label_desc: Use image node_id 1 to create a new OneVarTrial object from inherited base classes: TFKerasTrial with example: obj = OneVarTrial(context)