more data
This commit is contained in:
+37
-36
@@ -1,38 +1,39 @@
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[
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[
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[[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0, 1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0, 1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0 ,0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0 ,0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0, 1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0], [1, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0], [1, 0, 0, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0], [0, 0, 1]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1], [0, 0, 1]]
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0], [0, 0, 1, 0]],
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[[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1], [0, 0, 0, 1]]
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]
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]
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@@ -3,7 +3,7 @@ from network import Network
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from trainer import Trainer
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from trainer import Trainer
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network = Network()
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network = Network()
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network.build_layers(3, 36, 3, 12)
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network.build_layers(3, 37, 4, 12)
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network.connect_layers()
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network.connect_layers()
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trainer = Trainer(network, "./data.train")
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trainer = Trainer(network, "./data.train")
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@@ -13,16 +13,23 @@ print("Erkenne die Art eines zeichens (Konsontant, Vokal oder Zahl).")
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while True:
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while True:
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inpt = input("Dein Zeichen: ").lower()
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inpt = input("Dein Zeichen: ").lower()
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vec = [0 for _ in range(0, 36)]
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vec = [0 for _ in range(0, 37)]
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refrence = string.ascii_lowercase + string.digits
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refrence = string.ascii_lowercase + string.digits
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vec[refrence.index(inpt)] = 1
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try:
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index = refrence.index(inpt)
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except Exception:
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index = 36
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vec[index] = 1
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output = network.fire(vec)
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output = network.fire(vec)
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print(f"Konsontant: {round(output[0], 2)} | Vokal: {round(output[1], 2)} | Zahl: {round(output[2], 2)}")
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print(f"Konsontant: {round(output[0], 2)} | Vokal: {round(output[1], 2)} | Zahl: {round(output[2], 2)} | Unbekannt: {round(output[3], 2)}")
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if max(output) == output[0]:
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if max(output) == output[0]:
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print("AI Denkt: Konsontant")
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print("AI Denkt: Konsontant")
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elif max(output) == output[1]:
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elif max(output) == output[1]:
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print("AI Denkt: Vokal")
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print("AI Denkt: Vokal")
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else:
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elif max(output) == output[2]:
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print("AI Denkt: Zahl")
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print("AI Denkt: Zahl")
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else:
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print("AI Denkt: Unbekannt")
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+2
-1
@@ -19,7 +19,8 @@ class Trainer:
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def train(self, iters):
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def train(self, iters):
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for i in range(0, iters):
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for i in range(0, iters):
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print(f"Train {(i / iters) * 100}%")
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if i % 100 == 0:
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print(f"Train {round((i / iters) * 100)}%")
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sample = random.choice(self.data)
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sample = random.choice(self.data)
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in_vec = sample[0]
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in_vec = sample[0]
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check_vec = sample[1]
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check_vec = sample[1]
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Reference in New Issue
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