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Copy pathtest_Tensor___array__.py
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Copy pathtest_Tensor___array__.py
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65 lines (54 loc) · 1.63 KB
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed 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 textwrap
from apibase import APIBase
obj = APIBase("torch.Tensor.__array__")
def test_case_1():
pytorch_code = textwrap.dedent(
"""
import torch
x = torch.tensor([1.0, 2.0, 3.0])
result = x.__array__()
"""
)
obj.run(pytorch_code, ["result"])
def test_case_2():
pytorch_code = textwrap.dedent(
"""
import torch
x = torch.tensor([[1, 2], [3, 4]])
result = x.__array__()
"""
)
obj.run(pytorch_code, ["result"])
def test_case_3():
pytorch_code = textwrap.dedent(
"""
import torch
import numpy as np
x = torch.tensor([1.0, 2.0, 3.0], dtype=torch.float32)
result = np.asarray(x)
"""
)
obj.run(pytorch_code, ["result"])
def test_case_4():
pytorch_code = textwrap.dedent(
"""
import torch
import numpy as np
x = torch.tensor([1.0, 2.0, 3.0], dtype=torch.float32)
result = np.array(x)
"""
)
obj.run(pytorch_code, ["result"])