375 lines
10 KiB
Python
375 lines
10 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import OpTest, get_places
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import paddle
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from paddle.framework import core
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def pow_grad(x, y, dout):
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dx = dout * y * np.power(x, (y - 1))
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dy = dout * np.log(x) * np.power(x, y)
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return dx, dy
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class TestPowOp(OpTest):
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def setUp(self):
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self.op_type = "pow"
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self.python_api = paddle.pow
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self.public_python_api = paddle.pow
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self.prim_op_type = "comp"
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self.outputs = None
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self.custom_setting()
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if not self.outputs:
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self.outputs = {
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'Out': np.power(self.inputs['X'], self.attrs["factor"])
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}
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self.places = get_places()
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def custom_setting(self):
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self.inputs = {
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'X': np.random.uniform(1, 2, [20, 5]).astype("float64"),
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}
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self.attrs = {"factor": 2.0}
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def test_check_output(self):
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self.check_output(check_pir=True, check_symbol_infer=False)
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def test_check_grad(self):
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self.check_grad(
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['X'],
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'Out',
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check_prim_pir=True,
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check_pir=True,
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)
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class TestPowOp_ZeroDim1(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': np.random.uniform(1, 2, []).astype("float64"),
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}
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self.attrs = {
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"factor": float(np.random.uniform(1, 2, []).astype(np.float32))
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}
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class TestPowOp_big_shape_1(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': np.random.uniform(1, 2, [10, 10]).astype("float64"),
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}
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self.attrs = {
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"factor": float(np.random.uniform(0, 10, []).astype(np.float32))
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}
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class TestPowOp_big_shape_2(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': np.random.uniform(1, 2, [4, 6, 8]).astype("float64"),
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}
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self.attrs = {
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"factor": float(np.random.uniform(0, 10, []).astype(np.float32))
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}
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class TestPowOpInt(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': np.asarray([1, 3, 6]),
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}
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self.attrs = {"factor": 2.0}
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def test_check_grad(self):
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pass
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": 2.0}
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def test_check_output(self):
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for place in self.places:
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self.check_output_with_place(
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place, check_pir=True, check_symbol_infer=False
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)
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def test_check_grad(self):
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for place in self.places:
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self.check_grad_with_place(
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place,
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['X'],
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'Out',
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check_pir=True,
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)
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_1(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": -3.4}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_2(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": -2}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_3(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": -0.1}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_4(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": 0}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_5(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": 0.7}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_6(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": 1}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex64_7(TestPowOp_Complex64):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex64),
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}
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self.attrs = {"factor": 5.4}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128(TestPowOp):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": 2.0}
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def test_check_output(self):
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for place in self.places:
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self.check_output_with_place(
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place, check_pir=True, check_symbol_infer=False
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)
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def test_check_grad(self):
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for place in self.places:
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self.check_grad_with_place(
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place,
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['X'],
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'Out',
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check_pir=True,
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)
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_1(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": -3.4}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_2(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": -2}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_3(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": -0.1}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_4(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": 0}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_5(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": 0.7}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_6(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": 1}
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@unittest.skipIf(
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core.is_compiled_with_xpu(),
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"Skip XPU for complex dtype is not fully supported",
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)
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class TestPowOp_Complex128_7(TestPowOp_Complex128):
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def custom_setting(self):
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self.inputs = {
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'X': (
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np.random.uniform(0.1, 1, [1, 3, 6])
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+ 1j * np.random.uniform(0.1, 1, [1, 3, 6])
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).astype(np.complex128),
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}
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self.attrs = {"factor": 5.4}
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if __name__ == '__main__':
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unittest.main()
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