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https://github.com/ml-explore/mlx.git
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@@ -649,6 +649,58 @@ class TestArray(mlx_tests.MLXTestCase):
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self.assertEqual(y.tolist(), [3.0, 4.0])
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self.assertEqual(z.tolist(), [5.0, 6.0])
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def test_array_pickle(self):
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dtypes = [
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mx.int8,
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mx.int16,
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mx.int32,
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mx.int64,
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mx.uint8,
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mx.uint16,
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mx.uint32,
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mx.uint64,
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# mx.float16,
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mx.float32,
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# mx.bfloat16,
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mx.complex64,
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]
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import pickle
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for dtype in dtypes:
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x = mx.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], dtype=dtype)
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state = pickle.dumps(x)
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y = pickle.loads(state)
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self.assertEqualArray(x, y)
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self.assertEqual(x.dtype, y.dtype)
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def test_array_copy(self):
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dtypes = [
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mx.int8,
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mx.int16,
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mx.int32,
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mx.int64,
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mx.uint8,
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mx.uint16,
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mx.uint32,
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mx.uint64,
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# mx.float16,
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mx.float32,
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# mx.bfloat16,
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mx.complex64,
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]
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from copy import copy, deepcopy
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for copy_function in [copy, deepcopy]:
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for dtype in dtypes:
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x = mx.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], dtype=dtype)
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y = copy_function(x)
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self.assertEqualArray(x, y)
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y -= 1
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print(x, y)
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self.assertEqualArray(x - 1, y)
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def test_indexing(self):
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# Basic content check, slice indexing
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a_npy = np.arange(64, dtype=np.float32)
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