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* Fixing random.normal for half-precision dtype #642 * Update python/tests/test_random.py Co-authored-by: Awni Hannun <awni.hannun@gmail.com> --------- Co-authored-by: Awni Hannun <awni.hannun@gmail.com>
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@ -90,6 +90,16 @@ T below_one() {
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return f;
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}
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// Get the next representable value above -1.0 for half precision
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// floating point types (fp16, bf16)
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template <typename T>
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T above_minus_one() {
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T f = T(-1.0);
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uint16_t* m = (uint16_t*)&f;
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*m -= 1;
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return f;
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}
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array uniform(
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const array& low,
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const array& high,
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@ -158,7 +168,17 @@ array normal(
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const std::optional<array>& key /*= nullopt */,
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StreamOrDevice s /* = {} */) {
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auto stream = to_stream(s);
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auto low = array(std::nextafter(-1.0f, 0.0f), dtype);
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auto get_low = [&dtype]() {
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switch (dtype) {
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case float16:
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return array(above_minus_one<float16_t>(), dtype);
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case bfloat16:
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return array(above_minus_one<bfloat16_t>(), dtype);
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default:
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return array(std::nextafter(-1.0f, 0.0f), dtype);
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}
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};
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auto low = get_low();
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auto high = array(1.0f, dtype);
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auto samples = uniform(low, high, shape, dtype, key, stream);
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samples =
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@ -96,6 +96,11 @@ class TestRandom(mlx_tests.MLXTestCase):
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self.assertEqual(mx.random.normal().dtype, mx.random.normal(dtype=None).dtype)
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# Test not getting -inf or inf with half precison
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for hp in [mx.float16, mx.bfloat16]:
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a = abs(mx.random.normal(shape=(10000,), loc=0, scale=1, dtype=hp))
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self.assertTrue(mx.all(a < mx.inf))
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def test_randint(self):
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a = mx.random.randint(0, 1, [])
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self.assertEqual(a.shape, ())
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