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: keras.TFKerasTrialContext):
      self.context = context
      self.my_batch_size = self.context.get_per_slot_batch_size()
      self.my_learning_rate = self.context.get_hparam("learning_rate")
  
file_path: determined/harness/tests/experiment/fixtures/tf_keras_one_var_model.py
imports: from typing import Any, Dict, List, cast
  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 determined import keras
  from tests.experiment.fixtures import keras_cb_checker
label_desc: Use image node_id 1 to create a new OneVarTrial object from inherited base classes: keras with example: obj = OneVarTrial(context)