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from typing import Callable
import pandas as pd
import numpy as np
class NN:
def __init__(
self,
epochs: int,
hidden_size: int,
learning_rate: float,
test_size: float,
activation: str,
features: list[str],
target: str,
data: str,
wh: np.array,
wo: np.array,
bh: np.array,
bo: np.array,
):
self.epochs = epochs
self.hidden_size = hidden_size
self.learning_rate = learning_rate
self.test_size = test_size
self.activation = activation
self.features = features
self.target = target
self.data = data
self.wh: np.array = wh
self.wo: np.array = wo
self.bh: np.array = bh
self.bo: np.array = bo
self.func_prime: Callable = None
self.func: Callable = None
self.df: pd.DataFrame = None
self.X: pd.DataFrame = None
self.y: pd.DataFrame = None
def read_csv(self) -> dict[str, str]:
self.df = pd.read_csv(self.data)
self.X = self.df[self.features]
self.y = self.df[self.target]
def set_func(self, f: Callable) -> None:
assert isinstance(f, Callable)
self.func = f
def set_func_prime(self, f: Callable) -> None:
assert isinstance(f, Callable)
self.func_prime = f
@classmethod
def from_dict(cls, dct):
""" Creates an instance of NN given a dictionary
we can use this to make sure that the arguments are right
"""
return cls(**dct)
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