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120 lines
4.4 KiB
Python
120 lines
4.4 KiB
Python
# Copyright © 2023 Apple Inc.
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import unittest
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from itertools import combinations, permutations
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import mlx.core as mx
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import mlx_tests
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import numpy as np
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class TestReduce(mlx_tests.MLXTestCase):
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def test_axis_permutation_sums(self):
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x_npy = np.random.randn(5, 5, 5, 5, 5).astype(np.float32)
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x_mlx = mx.array(x_npy)
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for t in permutations(range(5)):
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with self.subTest(t=t):
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y_npy = np.transpose(x_npy, t)
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y_mlx = mx.transpose(x_mlx, t)
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for n in range(1, 6):
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for a in combinations(range(5), n):
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with self.subTest(a=a):
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z_npy = np.sum(y_npy, axis=a)
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z_mlx = mx.sum(y_mlx, axis=a)
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mx.eval(z_mlx)
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self.assertTrue(
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np.allclose(z_npy, np.array(z_mlx), atol=1e-4)
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)
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def test_expand_sums(self):
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x_npy = np.random.randn(5, 1, 5, 1, 5, 1).astype(np.float32)
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x_mlx = mx.array(x_npy)
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for m in range(1, 4):
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for ax in combinations([1, 3, 5], m):
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shape = np.array([5, 1, 5, 1, 5, 1])
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shape[list(ax)] = 5
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shape = shape.tolist()
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with self.subTest(shape=shape):
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y_npy = np.broadcast_to(x_npy, shape)
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y_mlx = mx.broadcast_to(x_mlx, shape)
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for n in range(1, 7):
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for a in combinations(range(6), n):
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with self.subTest(a=a):
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z_npy = np.sum(y_npy, axis=a) / 1000
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z_mlx = mx.sum(y_mlx, axis=a) / 1000
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mx.eval(z_mlx)
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self.assertTrue(
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np.allclose(z_npy, np.array(z_mlx), atol=1e-4)
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)
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def test_dtypes(self):
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int_dtypes = [
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"int8",
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"int16",
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"int32",
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"uint8",
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"uint16",
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"uint32",
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]
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float_dtypes = ["float32"]
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for dtype in int_dtypes + float_dtypes:
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with self.subTest(dtype=dtype):
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x = np.random.uniform(0, 2, size=(3, 3, 3)).astype(getattr(np, dtype))
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y = mx.array(x)
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for op in ("sum", "prod", "min", "max"):
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with self.subTest(op=op):
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np_op = getattr(np, op)
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mlx_op = getattr(mx, op)
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for axes in (None, 0, 1, 2, (0, 1), (0, 2), (1, 2), (0, 1, 2)):
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with self.subTest(axes=axes):
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if op in ("sum", "prod"):
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r_np = np_op(
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x, axis=axes, dtype=(getattr(np, dtype))
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)
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else:
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r_np = np_op(x, axis=axes)
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r_mlx = mlx_op(y, axis=axes)
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mx.eval(r_mlx)
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self.assertTrue(np.allclose(r_np, r_mlx, atol=1e-4))
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def test_arg_reduce(self):
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dtypes = [
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"uint8",
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"uint16",
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"uint32",
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"uint64",
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"int8",
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"int16",
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"int32",
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"int64",
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"float16",
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"float32",
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]
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for dtype in dtypes:
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with self.subTest(dtype=dtype):
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data = np.random.rand(10, 12, 13).astype(getattr(np, dtype))
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x = mx.array(data)
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for op in ["argmin", "argmax"]:
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for axis in range(3):
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for kd in [True, False]:
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a = getattr(mx, op)(x, axis, kd)
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b = getattr(np, op)(data, axis, keepdims=kd)
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self.assertEqual(a.tolist(), b.tolist())
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for op in ["argmin", "argmax"]:
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a = getattr(mx, op)(x, keepdims=True)
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b = getattr(np, op)(data, keepdims=True)
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self.assertEqual(a.tolist(), b.tolist())
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a = getattr(mx, op)(x)
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b = getattr(np, op)(data)
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self.assertEqual(a.item(), b)
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if __name__ == "__main__":
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unittest.main(failfast=True)
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