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parameterize multitensor tests for reduce (#3181)

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uneven shards reduce is incorrect now
This commit is contained in:
chenyu
2024-01-19 14:03:01 -05:00
committed by GitHub
parent 5097d5b808
commit cb4cfc078a
3 changed files with 20 additions and 33 deletions
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5
test/test_dtype.py
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@@ -9,6 +9,9 @@ from tinygrad.tensor import Tensor, dtypes
from typing import Any, List
from hypothesis import given, settings, strategies as strat
settings.register_profile("my_profile", max_examples=200, deadline=None)
settings.load_profile("my_profile")
core_dtypes = list(DTYPES_DICT.values())
floats = [dt for dt in core_dtypes if dtypes.is_float(dt)]
def is_dtype_supported(dtype: DType, device: str = Device.DEFAULT):
@@ -377,7 +380,6 @@ class TestAutoCastType(unittest.TestCase):
dtypes.default_int, dtypes.default_float = self.old_default_int, self.old_default_float
@given(strat.sampled_from([d for d in DTYPES_DICT.values() if dtypes.is_int(d) and is_dtype_supported(d)]))
@settings(deadline=None)
def test_int_to_float_unary_func(self, dtype):
for func in [
lambda t: t.exp(),
@@ -461,7 +463,6 @@ class TestAutoCastType(unittest.TestCase):
assert (Tensor([0, 1], dtype=dtypes.float64)).cumsum(0).dtype == dtypes.float64
@given(strat.sampled_from(core_dtypes), strat.sampled_from(core_dtypes))
@settings(deadline=None)
def test_matmul(self, dt1, dt2):
assert (Tensor([0, 1], dtype=dt1) @ Tensor([0, 1], dtype=dt2)).dtype == least_upper_dtype(dt1, dt2)