nanotorch implementation

tests/test_activations.py

@@ -0,0 +1,37 @@
+from nanotorch.tensor import Tensor
+
+# Test 1: ReLU
+print("Test 1 - ReLU:")
+x = Tensor([-2.0, -1.0, 0.0, 1.0, 2.0])
+y = x.relu()
+
+y.backward()
+
+print(f"x.data: {x.data}")
+print(f"y.data: {y.data}")      # Should be [0, 0, 0, 1, 2]
+print(f"x.grad: {x.grad}")      # Should be [0, 0, 0, 1, 1]
+
+# Test 2: Tanh
+print("\nTest 2 - Tanh:")
+x = Tensor([0.0, 1.0, 2.0])
+y = x.tanh()
+
+y.backward()
+
+print(f"x.data: {x.data}")
+print(f"y.data: {y.data}")      # Should be [0, 0.76, 0.96] approx
+print(f"x.grad: {x.grad}")      # Should be [1, 0.42, 0.07] approx (1 - tanh²)
+
+# Test 3: ReLU in a computation graph
+print("\nTest 3 - ReLU in computation:")
+x = Tensor([[-1.0, 2.0],
+            [3.0, -4.0]])
+w = Tensor([[0.5, 0.5],
+            [0.5, 0.5]])
+z = (x @ w).relu()  # Linear layer + ReLU
+
+z.backward()
+
+print(f"z.data:\n{z.data}")
+print(f"x.grad:\n{x.grad}")
+print(f"w.grad:\n{w.grad}")