wehub-resource-sync
221 lines
7.3 KiB
Python
221 lines
7.3 KiB
Python
# Copyright (c) 2022 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 get_test_cover_info import (
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XPUOpTestWrapper,
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create_test_class,
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get_xpu_op_support_types,
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)
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from op_test import convert_uint16_to_float
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from op_test_xpu import XPUOpTest
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import paddle
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from paddle import base, tensor
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from paddle.base import Program, program_guard
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paddle.enable_static()
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class XPUTestUnbindOP(XPUOpTestWrapper):
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def __init__(self):
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self.op_name = 'unbind'
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self.use_dynamic_create_class = False
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class TestUnbind(unittest.TestCase):
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def test_unbind(self):
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with program_guard(Program(), Program()):
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self.dtype = self.in_type
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self.place = paddle.XPUPlace(0)
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x_1 = paddle.static.data(
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shape=[2, 3], dtype=self.dtype, name='x_1'
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)
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[out_0, out_1] = tensor.unbind(input=x_1, axis=0)
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input_1 = np.random.random([2, 3]).astype(self.dtype)
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axis = paddle.static.data(shape=[], dtype='int32', name='axis')
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exe = base.Executor(place=self.place)
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[res_1, res_2] = exe.run(
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base.default_main_program(),
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feed={"x_1": input_1, "axis": 0},
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fetch_list=[out_0, out_1],
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)
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np.testing.assert_array_equal(res_1, input_1[0, 0:100])
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np.testing.assert_array_equal(res_2, input_1[1, 0:100])
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def test_unbind_dygraph(self):
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with base.dygraph.guard():
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self.dtype = self.in_type
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self.place = paddle.XPUPlace(0)
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np_x = np.random.random([2, 3]).astype(self.dtype)
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if self.dtype == np.uint16:
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np_x = convert_uint16_to_float(np_x)
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x = paddle.to_tensor(np_x)
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x.stop_gradient = False
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[res_1, res_2] = paddle.unbind(x, 0)
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np.testing.assert_array_equal(res_1, np_x[0, 0:100])
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np.testing.assert_array_equal(res_2, np_x[1, 0:100])
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out = paddle.add_n([res_1, res_2])
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np_grad = np.ones(x.shape, np.float32)
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out.backward()
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np.testing.assert_array_equal(x.grad.numpy(), np_grad)
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def test_unbind_dygraph_final_state(self):
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self.test_unbind_dygraph()
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class TestLayersUnbind(unittest.TestCase):
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def test_layers_unbind(self):
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with program_guard(Program(), Program()):
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self.dtype = self.in_type
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self.place = paddle.XPUPlace(0)
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x_1 = paddle.static.data(
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shape=[2, 3], dtype=self.dtype, name='x_1'
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)
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[out_0, out_1] = paddle.unbind(input=x_1, axis=0)
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input_1 = np.random.random([2, 3]).astype(self.dtype)
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axis = paddle.static.data(shape=[], dtype='int32', name='axis')
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exe = base.Executor(place=self.place)
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[res_1, res_2] = exe.run(
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base.default_main_program(),
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feed={"x_1": input_1, "axis": 0},
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fetch_list=[out_0, out_1],
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)
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np.testing.assert_array_equal(res_1, input_1[0, 0:100])
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np.testing.assert_array_equal(res_2, input_1[1, 0:100])
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class TestUnbindOp(XPUOpTest):
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def initParameters(self):
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pass
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def outReshape(self):
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self.out[0] = self.out[0].reshape((2, 2))
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self.out[1] = self.out[1].reshape((2, 2))
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self.out[2] = self.out[2].reshape((2, 2))
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def setAxis(self):
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pass
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def setUp(self):
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self._set_op_type()
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self.dtype = self.in_type
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self.place = paddle.XPUPlace(0)
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self.axis = 0
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self.num = 3
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self.initParameters()
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x = np.arange(12).reshape(3, 2, 2).astype(self.dtype)
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self.out = np.split(x, self.num, self.axis)
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self.outReshape()
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self.inputs = {'X': x}
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self.attrs = {'axis': self.axis}
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self.setAxis()
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self.outputs = {
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'Out': [(f'out{i}', self.out[i]) for i in range(len(self.out))]
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}
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def _set_op_type(self):
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self.op_type = "unbind"
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def test_check_output(self):
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self.check_output()
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def test_check_grad(self):
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self.check_grad(['X'], ['out0', 'out1', 'out2'])
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class TestUnbindOp1(TestUnbindOp):
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def initParameters(self):
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self.axis = 1
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self.num = 2
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def test_check_grad(self):
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self.check_grad(['X'], ['out0', 'out1'])
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def outReshape(self):
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self.out[0] = self.out[0].reshape((3, 2))
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self.out[1] = self.out[1].reshape((3, 2))
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class TestUnbindOp2(TestUnbindOp):
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def initParameters(self):
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self.axis = 2
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self.num = 2
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def test_check_grad(self):
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self.check_grad(['X'], ['out0', 'out1'])
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def outReshape(self):
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self.out[0] = self.out[0].reshape((3, 2))
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self.out[1] = self.out[1].reshape((3, 2))
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class TestUnbindOp3(TestUnbindOp):
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def initParameters(self):
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self.axis = 2
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self.num = 2
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def setAxis(self):
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self.attrs = {'axis': -1}
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def test_check_grad(self):
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self.check_grad(['X'], ['out0', 'out1'])
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def outReshape(self):
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self.out[0] = self.out[0].reshape((3, 2))
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self.out[1] = self.out[1].reshape((3, 2))
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class TestUnbindOp4(TestUnbindOp):
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def initParameters(self):
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self.axis = 1
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self.num = 2
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def setAxis(self):
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self.attrs = {'axis': -2}
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def test_check_grad(self):
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self.check_grad(['X'], ['out0', 'out1'])
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def outReshape(self):
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self.out[0] = self.out[0].reshape((3, 2))
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self.out[1] = self.out[1].reshape((3, 2))
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class TestUnbindAxisError(unittest.TestCase):
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def test_errors(self):
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with program_guard(Program(), Program()):
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self.dtype = self.in_type
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self.place = paddle.XPUPlace(0)
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x = paddle.static.data(shape=[2, 3], dtype=self.dtype, name='x')
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def test_table_Variable():
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tensor.unbind(input=x, axis=2.0)
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self.assertRaises(TypeError, test_table_Variable)
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def test_invalid_axis():
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tensor.unbind(input=x, axis=2)
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self.assertRaises(ValueError, test_invalid_axis)
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support_types = get_xpu_op_support_types('unbind')
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for stype in support_types:
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create_test_class(globals(), XPUTestUnbindOP, stype)
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if __name__ == '__main__':
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unittest.main()
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