48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
import ctypes
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import numpy as np
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from typing import TypeVar, Type
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from tinygrad.helpers import DType, dtypes, prod, GlobalCounters
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_T = TypeVar("_T")
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class RawBuffer: # pylint: disable=abstract-method
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def __init__(self, size:int, dtype:DType):
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self.size: int = size
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self.dtype: DType = dtype
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self._memsz: int = size*dtype.itemsize
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GlobalCounters.mem_used += self._memsz
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def __del__(self): GlobalCounters.mem_used -= self._memsz
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# NOTE: this interface allows for 0 copy
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@classmethod
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def fromCPU(cls:Type[_T], x:np.ndarray) -> _T: raise NotImplementedError("must be implemented")
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def toCPU(self) -> np.ndarray: raise NotImplementedError("must be implemented")
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class RawBufferCopyIn(RawBuffer):
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def _copyin(self, x:np.ndarray) -> None: raise NotImplementedError("must be implemented")
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@classmethod
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def fromCPU(cls, x:np.ndarray):
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ret = cls(prod(x.shape), dtypes.from_np(x))
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ret._copyin(x)
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return ret
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class RawBufferMapped(RawBufferCopyIn):
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def _buffer(self) -> memoryview: raise NotImplementedError("must be implemented")
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def toCPU(self) -> np.ndarray: return np.frombuffer(self._buffer(), dtype=self.dtype.np)
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def _copyin(self, x:np.ndarray) -> None: np.copyto(self.toCPU(), x.reshape(-1))
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# this one is simple enough that i moved it out of the runtimes
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class RawMallocBuffer(RawBufferMapped):
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def __init__(self, size, dtype: DType):
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super().__init__(size, dtype)
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self._buf = ({dtypes.float32: ctypes.c_float, dtypes.float16: ctypes.c_int16}[dtype] * size)()
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def _buffer(self): return memoryview(self._buf)
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class RawBufferCopyInOut(RawBufferCopyIn):
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def _copyout(self, x:np.ndarray) -> None: raise NotImplementedError("must be implemented")
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def toCPU(self) -> np.ndarray:
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x: np.ndarray = np.empty(self.size, dtype=self.dtype.np)
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self._copyout(x)
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return x
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