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# 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__()
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