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Always broadcast magic methods (#1101)
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@ -1,5 +1,6 @@
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import candle
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from candle import Tensor
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import pytest
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def test_tensor_can_be_constructed():
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@ -72,3 +73,75 @@ def test_tensor_can_be_scliced_3d():
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assert t[:, 0, 0].values() == [1, 9]
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assert t[..., 0].values() == [[1, 5], [9, 13]]
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assert t[..., 0:2].values() == [[[1, 2], [5, 6]], [[9, 10], [13, 14]]]
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def test_tensor_can_be_added():
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t = Tensor(42.0)
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result = t + t
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assert result.values() == 84.0
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result = t + 2.0
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assert result.values() == 44.0
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a = candle.rand((3, 1, 4))
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b = candle.rand((2, 1))
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c_native = a.broadcast_add(b)
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c = a + b
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assert c.shape == (3, 2, 4)
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assert c.values() == c_native.values()
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with pytest.raises(ValueError):
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d = candle.rand((3, 4, 5))
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e = candle.rand((4, 6))
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f = d + e
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def test_tensor_can_be_subtracted():
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t = Tensor(42.0)
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result = t - t
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assert result.values() == 0
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result = t - 2.0
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assert result.values() == 40.0
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a = candle.rand((3, 1, 4))
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b = candle.rand((2, 1))
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c_native = a.broadcast_sub(b)
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c = a - b
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assert c.shape == (3, 2, 4)
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assert c.values() == c_native.values()
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with pytest.raises(ValueError):
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d = candle.rand((3, 4, 5))
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e = candle.rand((4, 6))
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f = d - e
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def test_tensor_can_be_multiplied():
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t = Tensor(42.0)
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result = t * t
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assert result.values() == 1764.0
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result = t * 2.0
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assert result.values() == 84.0
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a = candle.rand((3, 1, 4))
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b = candle.rand((2, 1))
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c_native = a.broadcast_mul(b)
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c = a * b
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assert c.shape == (3, 2, 4)
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assert c.values() == c_native.values()
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with pytest.raises(ValueError):
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d = candle.rand((3, 4, 5))
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e = candle.rand((4, 6))
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f = d * e
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def test_tensor_can_be_divided():
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t = Tensor(42.0)
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result = t / t
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assert result.values() == 1.0
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result = t / 2.0
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assert result.values() == 21.0
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a = candle.rand((3, 1, 4))
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b = candle.rand((2, 1))
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c_native = a.broadcast_div(b)
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c = a / b
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assert c.shape == (3, 2, 4)
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assert c.values() == c_native.values()
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with pytest.raises(ValueError):
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d = candle.rand((3, 4, 5))
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e = candle.rand((4, 6))
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f = d / e
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