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205 lines
8.4 KiB
205 lines
8.4 KiB
# Copyright (c) 2018 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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from __future__ import print_function
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import op_test
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import unittest
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import numpy
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import numpy as np
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import paddle
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid import Program, program_guard
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def create_test_class(op_type, typename, callback):
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class Cls(op_test.OpTest):
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def setUp(self):
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a = numpy.random.random(size=(10, 7)).astype(typename)
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b = numpy.random.random(size=(10, 7)).astype(typename)
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c = callback(a, b)
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self.inputs = {'X': a, 'Y': b}
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self.outputs = {'Out': c}
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self.op_type = op_type
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def test_output(self):
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self.check_output()
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def test_errors(self):
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paddle.enable_static()
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with program_guard(Program(), Program()):
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x = fluid.layers.data(name='x', shape=[2], dtype='int32')
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y = fluid.layers.data(name='y', shape=[2], dtype='int32')
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a = fluid.layers.data(name='a', shape=[2], dtype='int16')
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if self.op_type == "less_than":
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self.assertRaises(
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TypeError,
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fluid.layers.less_than,
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x=x,
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y=y,
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force_cpu=1)
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op = eval("fluid.layers.%s" % self.op_type)
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self.assertRaises(TypeError, op, x=x, y=y, cond=1)
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self.assertRaises(TypeError, op, x=x, y=a)
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self.assertRaises(TypeError, op, x=a, y=y)
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cls_name = "{0}_{1}".format(op_type, typename)
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Cls.__name__ = cls_name
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globals()[cls_name] = Cls
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for _type_name in {'float32', 'float64', 'int32', 'int64'}:
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create_test_class('less_than', _type_name, lambda _a, _b: _a < _b)
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create_test_class('less_equal', _type_name, lambda _a, _b: _a <= _b)
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create_test_class('greater_than', _type_name, lambda _a, _b: _a > _b)
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create_test_class('greater_equal', _type_name, lambda _a, _b: _a >= _b)
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create_test_class('equal', _type_name, lambda _a, _b: _a == _b)
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create_test_class('not_equal', _type_name, lambda _a, _b: _a != _b)
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def create_paddle_case(op_type, callback):
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class PaddleCls(unittest.TestCase):
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def setUp(self):
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self.op_type = op_type
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self.input_x = np.array([1, 2, 3, 4]).astype(np.int64)
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self.input_y = np.array([1, 3, 2, 4]).astype(np.int64)
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self.real_result = callback(self.input_x, self.input_y)
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self.place = fluid.CPUPlace()
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if core.is_compiled_with_cuda():
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self.place = paddle.CUDAPlace(0)
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def test_api(self):
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paddle.enable_static()
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with program_guard(Program(), Program()):
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x = fluid.data(name='x', shape=[4], dtype='int64')
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y = fluid.data(name='y', shape=[4], dtype='int64')
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op = eval("paddle.%s" % (self.op_type))
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out = op(x, y)
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exe = fluid.Executor(self.place)
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res, = exe.run(feed={"x": self.input_x,
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"y": self.input_y},
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fetch_list=[out])
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self.assertEqual((res == self.real_result).all(), True)
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def test_dynamic_api(self):
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paddle.disable_static()
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x = paddle.to_tensor(self.input_x)
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y = paddle.to_tensor(self.input_y)
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op = eval("paddle.%s" % (self.op_type))
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out = op(x, y)
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self.assertEqual((out.numpy() == self.real_result).all(), True)
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paddle.enable_static()
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def test_broadcast_api_1(self):
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paddle.enable_static()
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with program_guard(Program(), Program()):
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x = paddle.static.data(
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name='x', shape=[1, 2, 1, 3], dtype='int32')
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y = paddle.static.data(name='y', shape=[1, 2, 3], dtype='int32')
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op = eval("paddle.%s" % (self.op_type))
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out = op(x, y)
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exe = paddle.static.Executor(self.place)
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input_x = np.arange(1, 7).reshape((1, 2, 1, 3)).astype(np.int32)
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input_y = np.arange(0, 6).reshape((1, 2, 3)).astype(np.int32)
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real_result = callback(input_x, input_y)
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res, = exe.run(feed={"x": input_x,
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"y": input_y},
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fetch_list=[out])
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self.assertEqual((res == real_result).all(), True)
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def test_attr_name(self):
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paddle.enable_static()
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with program_guard(Program(), Program()):
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x = fluid.layers.data(name='x', shape=[4], dtype='int32')
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y = fluid.layers.data(name='y', shape=[4], dtype='int32')
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op = eval("paddle.%s" % (self.op_type))
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out = op(x=x, y=y, name="name_%s" % (self.op_type))
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self.assertEqual("name_%s" % (self.op_type) in out.name, True)
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cls_name = "TestCase_{}".format(op_type)
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PaddleCls.__name__ = cls_name
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globals()[cls_name] = PaddleCls
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create_paddle_case('less_than', lambda _a, _b: _a < _b)
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create_paddle_case('less_equal', lambda _a, _b: _a <= _b)
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create_paddle_case('greater_than', lambda _a, _b: _a > _b)
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create_paddle_case('greater_equal', lambda _a, _b: _a >= _b)
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create_paddle_case('equal', lambda _a, _b: _a == _b)
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create_paddle_case('not_equal', lambda _a, _b: _a != _b)
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class TestCompareOpError(unittest.TestCase):
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def test_errors(self):
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paddle.enable_static()
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with program_guard(Program(), Program()):
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# The input x and y of compare_op must be Variable.
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x = fluid.layers.data(name='x', shape=[1], dtype="float32")
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y = fluid.create_lod_tensor(
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numpy.array([[-1]]), [[1]], fluid.CPUPlace())
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self.assertRaises(TypeError, fluid.layers.greater_equal, x, y)
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class API_TestElementwise_Equal(unittest.TestCase):
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def test_api(self):
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paddle.enable_static()
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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label = fluid.layers.assign(np.array([3, 3], dtype="int32"))
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limit = fluid.layers.assign(np.array([3, 2], dtype="int32"))
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out = paddle.equal(x=label, y=limit)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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res, = exe.run(fetch_list=[out])
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self.assertEqual((res == np.array([True, False])).all(), True)
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with fluid.program_guard(fluid.Program(), fluid.Program()):
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label = fluid.layers.assign(np.array([3, 3], dtype="int32"))
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limit = fluid.layers.assign(np.array([3, 3], dtype="int32"))
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out = paddle.equal(x=label, y=limit)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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res, = exe.run(fetch_list=[out])
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self.assertEqual((res == np.array([True, True])).all(), True)
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class TestCompareOpPlace(unittest.TestCase):
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def test_place_1(self):
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paddle.enable_static()
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place = paddle.CPUPlace()
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if core.is_compiled_with_cuda():
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place = paddle.CUDAPlace(0)
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label = fluid.layers.assign(np.array([3, 3], dtype="int32"))
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limit = fluid.layers.assign(np.array([3, 2], dtype="int32"))
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out = fluid.layers.less_than(label, limit, force_cpu=True)
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exe = fluid.Executor(place)
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res, = exe.run(fetch_list=[out])
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self.assertEqual((res == np.array([False, False])).all(), True)
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def test_place_2(self):
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place = paddle.CPUPlace()
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data_place = place
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if core.is_compiled_with_cuda():
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place = paddle.CUDAPlace(0)
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data_place = paddle.CUDAPinnedPlace()
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paddle.disable_static(place)
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data = np.array([9], dtype="int64")
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data_tensor = paddle.to_tensor(data, place=data_place)
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result = data_tensor == 0
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self.assertEqual((result.numpy() == np.array([False])).all(), True)
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if __name__ == '__main__':
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unittest.main()
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