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It must have compatible shape and dtype with those of ``a``'s. blocking (bool): If set to ``False``, the copy runs asynchronously on the given (if given) or current stream, and users are responsible for ensuring the stream order. Default is ``True``, so the copy is synchronous (with respect to the host). Returns: numpy.ndarray: Converted array on the host memory. )streamorderoutr__cuda_array_interface__)rN.)rrgethasattrrOrrQ)rrrrrtemps r asnumpyrs0!W uuF%S8uLLL . / / Qxx||C(DD D~au--- ?CHHC r c|D]V}t|ttjjjt jjt j j fr tcSWtS)aReturns the array module for arguments. This function is used to implement CPU/GPU generic code. If at least one of the arguments is a :class:`cupy.ndarray` object, the :mod:`cupy` module is returned. Args: args: Values to determine whether NumPy or CuPy should be used. Returns: module: :mod:`cupy` or :mod:`numpy` is returned based on the types of the arguments. .. admonition:: Example A NumPy/CuPy generic function can be written as follows >>> def softplus(x): ... xp = cupy.get_array_module(x) ... return xp.maximum(0, x) + xp.log1p(xp.exp(-abs(x))) ) rr_cupyxscipyrspmatrixrfusion_FusionVarArray new_fusion _ArrayProxy_cupyr)argsargs r get_array_moduler7s`. cGV\%8%A!L8!,8: ; ; LLL  Mr FctS)zReturns CuPy default memory pool for GPU memory. Returns: cupy.cuda.MemoryPool: The memory pool object. .. note:: If you want to disable memory pool, please use the following code. >>> cupy.cuda.set_allocator(None) )_default_memory_poolr r r get_default_memory_poolrcs  r ctS)aReturns CuPy default memory pool for pinned memory. 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