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92f14e0
1
Parent(s):
f9522cf
better organization for generalization once we add other methods and such
Browse files- main.py +0 -5
- neural_network/main.py +6 -8
main.py
CHANGED
@@ -22,12 +22,7 @@ if __name__ == "__main__":
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raise ValueError(f"Invalid method '{method}'. Choose 'nn' instead.")
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X, y = random_dataset()
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args = nn.get_args()
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nn.main(
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X=X,
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y=y,
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epochs=args["epochs"],
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hidden_size=args["hidden_size"],
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learning_rate=args["learning_rate"],
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activation_func=args["activation_func"],
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)
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raise ValueError(f"Invalid method '{method}'. Choose 'nn' instead.")
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X, y = random_dataset()
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nn.main(
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X=X,
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y=y,
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)
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neural_network/main.py
CHANGED
@@ -4,7 +4,7 @@ from neural_network.forwardprop import fp
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from neural_network.backprop import bp
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def get_args():
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"""
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returns a dictionary containing
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the arguments to be passed to
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@@ -34,16 +34,14 @@ def init(X: np.array, y: np.array, hidden_size: int) -> dict:
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def main(
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X: np.array,
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y: np.array,
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epochs: int,
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hidden_size: int,
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learning_rate: float,
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activation_func: str,
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) -> None:
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-
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for e in range(epochs):
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fp()
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bp()
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# update weights and biases
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from neural_network.backprop import bp
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+
def get_args() -> dict:
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"""
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returns a dictionary containing
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the arguments to be passed to
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def main(
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X: np.array,
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y: np.array,
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) -> None:
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args = get_args()
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wb = init(X, y, args["hidden_size"])
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for e in range(args["epochs"]):
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fp()
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bp()
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# update weights and biases
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+
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# print results
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