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tensor == tensor should be bool (#2916)

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* return bool

* add tests to the type spec

* fix multinomial

* fix tril

* fix round

* fix NegativeLogLikelihoodLoss

* rm debug

* webgpu

* more webgpu

* bitwise or for adding two bools

* onnx ops dont need to cast anymore

* Revert "bitwise or for adding two bools"

This reverts commit b413babffa.

* workaround for metal neg

* just the tests in the type spec
This commit is contained in:
qazal
2023-12-25 19:38:47 +02:00
committed by GitHub
parent 8a8aed23d2
commit dca5e4fe74
1 changed files with 6 additions and 1 deletions
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7
test/test_dtype.py
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@@ -1,6 +1,7 @@
import unittest
import numpy as np
import torch
import operator
from tinygrad.helpers import CI, DTYPES_DICT, getenv, DType, DEBUG, ImageDType, PtrDType, OSX, least_upper_float, temp, least_upper_dtype
from tinygrad import Device
from tinygrad.tensor import Tensor, dtypes
@@ -9,7 +10,6 @@ from hypothesis import given, settings, strategies as st
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):
# for GPU, cl_khr_fp16 isn't supported
# for LLVM, it segfaults because it can't link to the casting function
@@ -308,6 +308,11 @@ class TestTypeSpec(unittest.TestCase):
assert Tensor.arange(3, 9, 0.7).dtype == dtypes.default_float
assert Tensor.arange(3, 8.5, 3).dtype == dtypes.default_float
@unittest.skipIf(Device.DEFAULT == "WEBGPU", "WEBGPU doesn't follow the bool ops spec")
@given(st.sampled_from(core_dtypes), st.sampled_from([operator.gt, operator.ge, operator.le, operator.lt, operator.eq, operator.ne]))
def test_bool_ops(self, dtype, op):
assert op(Tensor.rand(4, 4, dtype=dtype), Tensor.rand(4, 4, dtype=dtype)).dtype == dtypes.bool
@given(st.sampled_from(core_dtypes),
st.sampled_from([dtypes.int8,dtypes.int16,dtypes.int32,dtypes.int64]), st.sampled_from([dtypes.float16,dtypes.float32,dtypes.float64]))
def test_functions_return_index(self, dtype, default_int, default_float):