Merge pull request #2 from anton164/master

Added more tests for conv1d and tiling

tests/test_conv.py

@@ -16,13 +16,51 @@ def test_conv1d_simple():
     assert out[0, 0, 2] == 2 * 1 + 3 * 2
     assert out[0, 0, 3] == 3 * 1
 
+@pytest.mark.task4_1
+def test_conv1d_simple_backward():
+    input_tensor = minitorch.tensor_fromlist([0, 1, 2, 3]).view(1, 1, 4)
+    weight = minitorch.tensor_fromlist([[1, 2, 3]]).view(1, 1, 3)
+    grad_output = minitorch.tensor_fromlist([0, 1, 2, 3]).view(1, 1, 4)
+    ctx = minitorch.Context()
+    ctx.save_for_backward(input_tensor, weight)
+    grad_input, grad_weight = minitorch.Conv1dFun.backward(ctx, grad_output)
+
+    assert grad_input[0, 0, 0] == weight[0, 0, 0] * grad_output[0, 0, 0]
+    assert (
+        grad_input[0, 0, 1]
+        == weight[0, 0, 0] * grad_output[0, 0, 1]
+        + weight[0, 0, 1] * grad_output[0, 0, 0]
+    )
+    assert (
+        grad_input[0, 0, 2]
+        == weight[0, 0, 0] * grad_output[0, 0, 2]
+        + weight[0, 0, 1] * grad_output[0, 0, 1]
+        + weight[0, 0, 2] * grad_output[0, 0, 0]
+    )
+    assert (
+        grad_input[0, 0, 3]
+        == weight[0, 0, 0] * grad_output[0, 0, 3]
+        + weight[0, 0, 1] * grad_output[0, 0, 2]
+        + weight[0, 0, 2] * grad_output[0, 0, 1]
+    )
 
 @pytest.mark.task4_1
 @given(tensors(shape=(1, 1, 6)), tensors(shape=(1, 1, 4)))
 def test_conv1d(input, weight):
     print(input, weight)
     minitorch.grad_check(minitorch.Conv1dFun.apply, input, weight)
 
+@pytest.mark.task4_1
+def test_conv1d_in_channel():
+    t = minitorch.tensor_fromlist([[0, 1, 2, 3], [0, 1, 2, 3]]).view(1, 2, 4)
+    t.requires_grad_(True)
+    t2 = minitorch.tensor_fromlist([[1, 2, 3], [1, 2, 3]]).view(1, 2, 3)
+    out = minitorch.Conv1dFun.apply(t, t2)
+
+    assert out[0, 0, 0] == (0 * 1 + 1 * 2 + 2 * 3) * 2
+    assert out[0, 0, 1] == (1 * 1 + 2 * 2 + 3 * 3) * 2
+    assert out[0, 0, 2] == (2 * 1 + 3 * 2) * 2
+    assert out[0, 0, 3] == (3 * 1) * 2
 
 @pytest.mark.task4_1
 @given(tensors(shape=(2, 2, 6)), tensors(shape=(3, 2, 2)))

tests/test_nn.py

@@ -3,6 +3,27 @@
 from .strategies import tensors, assert_close
 import pytest
 
+@pytest.mark.task4_3
+def test_tile():
+    t = minitorch.tensor_fromlist(
+        [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
+    ).view(1, 1, 4, 4)
+    tiled, _, _ = minitorch.tile(t, (2, 2))
+    assert tiled[0, 0, 0, 0, 0] == 1
+    assert tiled[0, 0, 0, 0, 1] == 2
+    assert tiled[0, 0, 0, 0, 2] == 5
+    assert tiled[0, 0, 0, 0, 3] == 6
+
+@pytest.mark.task4_3
+def test_tile_2():
+    t = minitorch.tensor_fromlist(
+        [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
+    ).view(1, 1, 4, 4)
+    tiled, _, _ = minitorch.tile(t, (1, 2))
+    assert tiled[0, 0, 0, 0, 0] == 1
+    assert tiled[0, 0, 0, 0, 1] == 2
+    assert tiled[0, 0, 0, 1, 0] == 3
+    assert tiled[0, 0, 0, 1, 1] == 4
 
 @pytest.mark.task4_3
 @given(tensors(shape=(1, 1, 4, 4)))