# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import ctypes from functools import wraps import pytest import numpy as np import pyarrow as pa from pyarrow.vendored.version import Version def PyCapsule_IsValid(capsule, name): return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1 def check_dlpack_export(arr, expected_arr): DLTensor = arr.__dlpack__() assert PyCapsule_IsValid(DLTensor, b"dltensor") is True result = np.from_dlpack(arr) np.testing.assert_array_equal(result, expected_arr, strict=True) assert arr.__dlpack_device__() == (1, 0) def check_bytes_allocated(f): @wraps(f) def wrapper(*args, **kwargs): allocated_bytes = pa.total_allocated_bytes() try: return f(*args, **kwargs) finally: assert pa.total_allocated_bytes() == allocated_bytes return wrapper @check_bytes_allocated @pytest.mark.parametrize( ('value_type', 'np_type'), [ (pa.uint8(), np.uint8), (pa.uint16(), np.uint16), (pa.uint32(), np.uint32), (pa.uint64(), np.uint64), (pa.int8(), np.int8), (pa.int16(), np.int16), (pa.int32(), np.int32), (pa.int64(), np.int64), (pa.float16(), np.float16), (pa.float32(), np.float32), (pa.float64(), np.float64), ] ) def test_dlpack(value_type, np_type): if Version(np.__version__) < Version("1.24.0"): pytest.skip("No dlpack support in numpy versions older than 1.22.0, " "strict keyword in assert_array_equal added in numpy version " "1.24.0") expected = np.array([1, 2, 3], dtype=np_type) arr = pa.array(expected, type=value_type) check_dlpack_export(arr, expected) arr_sliced = arr.slice(1, 1) expected = np.array([2], dtype=np_type) check_dlpack_export(arr_sliced, expected) arr_sliced = arr.slice(0, 1) expected = np.array([1], dtype=np_type) check_dlpack_export(arr_sliced, expected) arr_sliced = arr.slice(1) expected = np.array([2, 3], dtype=np_type) check_dlpack_export(arr_sliced, expected) arr_zero = pa.array([], type=value_type) expected = np.array([], dtype=np_type) check_dlpack_export(arr_zero, expected) def test_dlpack_not_supported(): if Version(np.__version__) < Version("1.22.0"): pytest.skip("No dlpack support in numpy versions older than 1.22.0.") arr = pa.array([1, None, 3]) with pytest.raises(TypeError, match="Can only use DLPack " "on arrays with no nulls."): np.from_dlpack(arr) arr = pa.array( [[0, 1], [3, 4]], type=pa.list_(pa.int32()) ) with pytest.raises(TypeError, match="DataType is not compatible with DLPack spec"): np.from_dlpack(arr) arr = pa.array([]) with pytest.raises(TypeError, match="DataType is not compatible with DLPack spec"): np.from_dlpack(arr) # DLPack doesn't support bit-packed boolean values arr = pa.array([True, False, True]) with pytest.raises(TypeError, match="Bit-packed boolean data type " "not supported by DLPack."): np.from_dlpack(arr) def test_dlpack_cuda_not_supported(): cuda = pytest.importorskip("pyarrow.cuda") schema = pa.schema([pa.field('f0', pa.int16())]) a0 = pa.array([1, 2, 3], type=pa.int16()) batch = pa.record_batch([a0], schema=schema) cbuf = cuda.serialize_record_batch(batch, cuda.Context(0)) cbatch = cuda.read_record_batch(cbuf, batch.schema) carr = cbatch["f0"] # CudaBuffers not yet supported with pytest.raises(NotImplementedError, match="DLPack support is implemented " "only for buffers on CPU device."): np.from_dlpack(carr) with pytest.raises(NotImplementedError, match="DLPack support is implemented " "only for buffers on CPU device."): carr.__dlpack_device__()