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Test min (#932)

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* fix __neg__ defaulting to float32 due to 0.0

* fixed __neg__ always defaulting to float32

* fixed openpilot (OpenCL) Test
This commit is contained in:
Steven Anderson
2023-06-05 00:03:30 -07:00
committed by GitHub
parent 00360da05b
commit 79613eb83e
2 changed files with 4 additions and 4 deletions
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6
tinygrad/tensor.py
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@@ -3,7 +3,7 @@ from __future__ import annotations
import math, functools, itertools, operator
import numpy as np
from typing import List, Tuple, Callable, Optional, ClassVar, Type, Union, Sequence
from tinygrad.helpers import prod, argfix, make_pair, getenv, IMAGE, DEBUG, flatten, DType, dtypes
from tinygrad.helpers import prod, argfix, make_pair, getenv, IMAGE, DEBUG, flatten, DType, dtypes, ImageDType
from tinygrad.lazy import Device, LazyBuffer
from tinygrad.ops import LoadOps
@@ -503,9 +503,9 @@ class Tensor:
def softsign(self): return self / (1 + self.abs())
# ***** broadcasted binary mlops *****
def _broadcasted(self, fxn:Type[Function], other:Union[Tensor, float], reverse:bool=False) -> Tensor:
x,y = [Tensor(t, device=self.device, requires_grad=False) if not isinstance(t, Tensor) else t for t in ([other,self] if reverse else [self,other])]
dtype = self.dtype if self.dtype != dtypes.bool and not isinstance(self.dtype,ImageDType) else dtypes.float32
x,y = [Tensor(t, device=self.device, requires_grad=False, dtype=dtype) if not isinstance(t, Tensor) else t for t in ([other,self] if reverse else [self,other])]
x,y = [t.reshape([1]*(max(len(x.shape), len(y.shape))-len(t.shape)) + list(t.shape)) for t in [x,y]]
shape_ret = tuple(max(sx, sy) for sx,sy in zip(x.shape, y.shape))
return fxn.apply(x.expand(shape_ret), y.expand(shape_ret))