ZihengJiang commented on a change in pull request #7488:
URL: https://github.com/apache/tvm/pull/7488#discussion_r583282138
##########
File path: python/tvm/runtime/ndarray.py
##########
@@ -253,42 +254,35 @@ def numpyasarray(np_data):
return arr, shape
-def empty(shape, dtype="float32", ctx=context(1, 0)):
+def empty(shape, dtype="float32", ctx=context(1, 0), mem_scope=None):
"""Create an empty array given shape and device
Parameters
----------
shape : tuple of int
- The shape of the array
+ The shape of the array.
dtype : type or str
The data type of the array.
ctx : TVMContext
- The context of the array
+ The context of the array.
+
+ mem_scope : str
+ The memory scope of the array.
Returns
-------
arr : tvm.nd.NDArray
The array tvm supported.
"""
- shape = c_array(tvm_shape_index_t, shape)
- ndim = ctypes.c_int(len(shape))
- handle = TVMArrayHandle()
+ arr = np.array(shape, 'int64')
+ ptr = arr.ctypes.data_as(ctypes.POINTER(ctypes.c_int64))
+ shape_ptr = ctypes.cast(ptr, ctypes.c_void_p)
+ ndim = len(shape)
dtype = DataType(dtype)
- check_call(
- _LIB.TVMArrayAlloc(
- shape,
- ndim,
- ctypes.c_int(dtype.type_code),
- ctypes.c_int(dtype.bits),
- ctypes.c_int(dtype.lanes),
- ctx.device_type,
- ctx.device_id,
- ctypes.byref(handle),
- )
- )
- return _make_array(handle, False, False)
+ arr = _ffi_api.TVMArrayAllocWithScope(shape_ptr, ndim, dtype, ctx,
mem_scope)
Review comment:
We can upgrade this to CAPI after it is stable
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