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148 lines
4.1 KiB
Python
148 lines
4.1 KiB
Python
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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t = Tensor(42.0)
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assert t.values() == 42.0
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def test_tensor_can_be_constructed_from_list():
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t = Tensor([3.0, 1, 4, 1, 5, 9, 2, 6])
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assert t.values() == [3.0, 1, 4, 1, 5, 9, 2, 6]
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def test_tensor_can_be_constructed_from_list_of_lists():
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t = Tensor([[3.0, 1, 4, 1], [5, 9, 2, 6]])
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assert t.values() == [[3.0, 1, 4, 1], [5, 9, 2, 6]]
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def test_tensor_can_be_quantized():
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t = candle.randn((16, 256))
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for format in [
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"q4_0",
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"q4_1",
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"q5_0",
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"q5_1",
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"q8_0",
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"q2k",
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"q3k",
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"q4k",
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"q5k",
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"q8k",
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]:
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for formatted_format in [format.upper(), format.lower()]:
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quant_t = t.quantize(formatted_format)
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assert quant_t.ggml_dtype.lower() == format.lower()
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assert quant_t.shape == t.shape
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def test_tensor_can_be_indexed():
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t = Tensor([[3.0, 1, 4, 1], [5, 9, 2, 6]])
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assert t[0].values() == [3.0, 1.0, 4.0, 1.0]
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assert t[1].values() == [5.0, 9.0, 2.0, 6.0]
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assert t[-1].values() == [5.0, 9.0, 2.0, 6.0]
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assert t[-2].values() == [3.0, 1.0, 4.0, 1.0]
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def test_tensor_can_be_sliced():
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t = Tensor([3.0, 1, 4, 10, 5, 9, 2, 6])
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assert t[0:4].values() == [3.0, 1.0, 4.0, 10.0]
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assert t[4:8].values() == [5.0, 9.0, 2.0, 6.0]
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assert t[-4:].values() == [5.0, 9.0, 2.0, 6.0]
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assert t[:-4].values() == [3.0, 1.0, 4.0, 10.0]
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assert t[-4:-2].values() == [5.0, 9.0]
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def test_tensor_can_be_sliced_2d():
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t = Tensor([[3.0, 1, 4, 1], [5, 9, 2, 6]])
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assert t[:, 0].values() == [3.0, 5]
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assert t[:, 1].values() == [1.0, 9.0]
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assert t[0, 0].values() == 3.0
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assert t[:, -1].values() == [1.0, 6.0]
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assert t[:, -4].values() == [3.0, 5]
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assert t[..., 0].values() == [3.0, 5]
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def test_tensor_can_be_scliced_3d():
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t = Tensor([[[1, 2, 3, 4], [5, 6, 7, 8]], [[9, 10, 11, 12], [13, 14, 15, 16]]])
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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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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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