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# Copyright (c) 2021 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.
from auto_scan_test import OPConvertAutoScanTest, BaseNet
import hypothesis.strategies as st
import unittest
import paddle
from onnxbase import _test_with_pir
class Net(BaseNet):
def forward(self):
start = self.config["start"]
stop = self.config["stop"]
num = self.config["num"]
dtype = self.config["dtype"]
x = paddle.linspace(start=start, stop=stop, num=num, dtype=dtype)
return x
class TestLinspaceConvert(OPConvertAutoScanTest):
"""
api: linspace
OPset version:
"""
def sample_convert_config(self, draw):
start = draw(st.integers(min_value=1, max_value=10))
stop = draw(st.integers(min_value=20, max_value=30))
num = draw(st.integers(min_value=2, max_value=40))
if draw(st.booleans()):
dtype = draw(st.sampled_from(["float32", "float64", "int32", "int64"]))
else:
dtype = None
config = {
"op_names": ["linspace"],
"test_data_shapes": [],
"test_data_types": [],
"opset_version": [9, 15],
"input_spec_shape": [],
"start": start,
"stop": stop,
"num": num,
"dtype": dtype,
}
model = Net(config)
return (config, model)
@_test_with_pir
def test(self):
self.run_and_statis(max_examples=30, max_duration=-1)
if __name__ == "__main__":
unittest.main()