Merge pull request #245 from Pushover-1/main

AI IS HERE GUYSSS!!!

README.md

@@ -146,6 +146,7 @@ A: Thecoderunsfasterwhentherearenouselessspacesandnewlines.
 - Processing
 - Prolog
 - Python
+- Python AI/ML/DL
 - q
 - Q#
 - R

implementations/main_ml.py

@@ -0,0 +1,33 @@
+import torch 
+import torch.nn as nn 
+
+class Prime(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.linear = nn.Linear(1,1)
+        self.linear.apply(self.init_weights_biases)
+
+    def init_weights_biases(self,m):
+        if isinstance(m, nn.Linear):
+            nn.init.constant_(m.weight, 1)
+            nn.init.constant_(m.bias,0)
+
+    def forward(self, number):
+        out = self.linear(number)
+        out = nn.functional.relu(out)
+        return out 
+
+def is_prime(number):
+    if number<=0:
+        raise ValueError("Don't you even know the definition of Prime Numbers, doofus!!")
+    is_prime_model = Prime()
+    input_tensor = torch.tensor([float(number)])
+    output = is_prime_model(input_tensor)
+    if output:
+        return False
+
+if __name__ == "__main__":
+    is_prime(1)
+
+
+

optimized_implementations/main_ml.py

@@ -0,0 +1,33 @@
+import torch 
+import torch.nn as nn 
+
+class Prime(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.linear = nn.Linear(1,1)
+        self.linear.apply(self.init_weights_biases)
+
+    def init_weights_biases(self,m):
+        if isinstance(m, nn.Linear):
+            nn.init.constant_(m.weight, 1)
+            nn.init.constant_(m.bias,0)
+
+    def forward(self, number):
+        out = self.linear(number)
+        out = nn.functional.relu(out)
+        return out 
+
+def is_prime(number):
+    if number<=0:
+        raise ValueError("Don't you even know the definition of Prime Numbers, doofus!!")
+    is_prime_model = Prime()
+    input_tensor = torch.tensor([float(number)])
+    output = is_prime_model(input_tensor)
+    if output:
+        return False
+
+if __name__ == "__main__":
+    is_prime(1)
+
+
+