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- # Copyright (c) 2022 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 unittest
-
- import numpy as np
- from get_test_cover_info import (
- XPUOpTestWrapper,
- create_test_class,
- get_xpu_op_support_types,
- )
- from op_test_xpu import XPUOpTest
-
- import paddle
-
- paddle.enable_static()
-
-
- class XPUTestUnsqueeze2Op(XPUOpTestWrapper):
- def __init__(self):
- self.op_name = "unsqueeze2"
- self.use_dynamic_create_class = False
-
- class TestUnsqueeze2Op(XPUOpTest):
- def setUp(self):
- self.op_type = "unsqueeze2"
- self.__class__.op_type = "unsqueeze2"
- self.use_mkldnn = False
- self.init_dtype()
- self.init_test_case()
- self.inputs = {
- "X": np.random.random(self.ori_shape).astype(self.dtype)
- }
- self.outputs = {
- "Out": self.inputs["X"].reshape(self.new_shape),
- "XShape": np.random.random(self.ori_shape).astype(self.dtype),
- }
- self.init_attrs()
-
- def init_dtype(self):
- self.dtype = self.in_type
-
- def init_attrs(self):
- self.attrs = {"axes": self.axes}
-
- def init_test_case(self):
- self.ori_shape = (3, 40)
- self.axes = (1, 2)
- self.new_shape = (3, 1, 1, 40)
-
- def test_check_output(self):
- place = paddle.XPUPlace(0)
- self.check_output_with_place(place, no_check_set=['XShape'])
-
- def test_check_grad(self):
- place = paddle.XPUPlace(0)
- if self.dtype == np.bool_:
- return
- else:
- self.check_grad_with_place(place, ['X'], 'Out')
-
- # Correct: Single input index.
- class TestUnsqueeze2Op1(TestUnsqueeze2Op):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (-1,)
- self.new_shape = (20, 5, 1)
-
- # Correct: Mixed input axis.
- class TestUnsqueeze2Op2(TestUnsqueeze2Op):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (0, -1)
- self.new_shape = (1, 20, 5, 1)
-
- # Correct: There is duplicated axis.
- class TestUnsqueeze2Op3(TestUnsqueeze2Op):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (0, 3, 3)
- self.new_shape = (1, 10, 2, 1, 1, 5)
-
- # Correct: Reversed axes.
- class TestUnsqueeze2Op4(TestUnsqueeze2Op):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (3, 1, 1)
- self.new_shape = (10, 1, 1, 2, 5, 1)
-
- # axes is a list(with tensor)
- class TestUnsqueeze2Op_AxesTensorList(XPUOpTest):
- def setUp(self):
- self.op_type = "unsqueeze2"
- self.__class__.op_type = "unsqueeze2"
- self.use_mkldnn = False
- self.init_dtype()
- self.init_test_case()
-
- axes_tensor_list = []
- for index, ele in enumerate(self.axes):
- axes_tensor_list.append(
- ("axes" + str(index), np.ones(1).astype('int32') * ele)
- )
-
- self.inputs = {
- "X": np.random.random(self.ori_shape).astype(self.dtype),
- "AxesTensorList": axes_tensor_list,
- }
- self.init_attrs()
- self.outputs = {
- "Out": self.inputs["X"].reshape(self.new_shape),
- "XShape": np.random.random(self.ori_shape).astype(self.dtype),
- }
-
- def init_dtype(self):
- self.dtype = self.in_type
-
- def test_check_output(self):
- place = paddle.XPUPlace(0)
- self.check_output_with_place(place, no_check_set=['XShape'])
-
- def test_check_grad(self):
- place = paddle.XPUPlace(0)
- if self.dtype in [np.float32, np.float64, np.float16]:
- self.check_grad_with_place(place, ['X'], 'Out')
- else:
- return
-
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (1, 2)
- self.new_shape = (20, 1, 1, 5)
-
- def init_attrs(self):
- self.attrs = {}
-
- class TestUnsqueeze2Op1_AxesTensorList(TestUnsqueeze2Op_AxesTensorList):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (-1,)
- self.new_shape = (20, 5, 1)
-
- class TestUnsqueeze2Op2_AxesTensorList(TestUnsqueeze2Op_AxesTensorList):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (0, -1)
- self.new_shape = (1, 20, 5, 1)
-
- class TestUnsqueeze2Op3_AxesTensorList(TestUnsqueeze2Op_AxesTensorList):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (0, 3, 3)
- self.new_shape = (1, 10, 2, 1, 1, 5)
-
- class TestUnsqueeze2Op4_AxesTensorList(TestUnsqueeze2Op_AxesTensorList):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (3, 1, 1)
- self.new_shape = (10, 1, 1, 2, 5, 1)
-
- # axes is a Tensor
- class TestUnsqueeze2Op_AxesTensor(XPUOpTest):
- def setUp(self):
- self.op_type = "unsqueeze2"
- self.__class__.op_type = "unsqueeze2"
- self.use_mkldnn = False
- self.init_test_case()
- self.init_dtype()
-
- self.inputs = {
- "X": np.random.random(self.ori_shape).astype(self.dtype),
- "AxesTensor": np.array(self.axes).astype("int32"),
- }
- self.init_attrs()
- self.outputs = {
- "Out": self.inputs["X"].reshape(self.new_shape),
- "XShape": np.random.random(self.ori_shape).astype(self.dtype),
- }
-
- def init_dtype(self):
- self.dtype = self.in_type
-
- def test_check_output(self):
- place = paddle.XPUPlace(0)
- self.check_output_with_place(place, no_check_set=['XShape'])
-
- def test_check_grad(self):
- place = paddle.XPUPlace(0)
- if self.dtype in [np.float32, np.float64, np.float16]:
- self.check_grad_with_place(place, ['X'], 'Out')
- else:
- return
-
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (1, 2)
- self.new_shape = (20, 1, 1, 5)
-
- def init_attrs(self):
- self.attrs = {}
-
- class TestUnsqueeze2Op1_AxesTensor(TestUnsqueeze2Op_AxesTensor):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (-1,)
- self.new_shape = (20, 5, 1)
-
- class TestUnsqueeze2Op2_AxesTensor(TestUnsqueeze2Op_AxesTensor):
- def init_test_case(self):
- self.ori_shape = (20, 5)
- self.axes = (0, -1)
- self.new_shape = (1, 20, 5, 1)
-
- class TestUnsqueeze2Op3_AxesTensor(TestUnsqueeze2Op_AxesTensor):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (0, 3, 3)
- self.new_shape = (1, 10, 2, 1, 1, 5)
-
- class TestUnsqueeze2Op4_AxesTensor(TestUnsqueeze2Op_AxesTensor):
- def init_test_case(self):
- self.ori_shape = (10, 2, 5)
- self.axes = (3, 1, 1)
- self.new_shape = (10, 1, 1, 2, 5, 1)
-
-
- support_types = get_xpu_op_support_types("unsqueeze2")
- for stype in support_types:
- create_test_class(globals(), XPUTestUnsqueeze2Op, stype)
-
- if __name__ == "__main__":
- unittest.main()
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