paddlepaddle--paddle
wehub-resource-sync
535 行
20 KiB
Python
535 行
20 KiB
Python
# 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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import unittest
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import numpy as np
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from op_test import OpTest, get_device_place, is_custom_device
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from utils import dygraph_guard, static_guard
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import paddle
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from paddle.base import core
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class TestAllcloseOp(OpTest):
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def set_args(self):
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self.input = np.array([10000.0, 1e-07]).astype("float32")
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self.other = np.array([10000.1, 1e-08]).astype("float32")
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self.rtol = np.array([1e-05]).astype("float64")
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self.atol = np.array([1e-08]).astype("float64")
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self.equal_nan = False
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def setUp(self):
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self.set_args()
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self.op_type = "allclose"
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self.python_api = paddle.allclose
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self.inputs = {
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'Input': self.input,
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'Other': self.other,
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"Rtol": self.rtol,
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"Atol": self.atol,
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}
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self.attrs = {'equal_nan': self.equal_nan}
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self.outputs = {
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'Out': np.array(
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np.allclose(
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self.inputs['Input'],
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self.inputs['Other'],
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rtol=self.rtol,
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atol=self.atol,
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equal_nan=self.equal_nan,
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)
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)
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}
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def test_check_output(self):
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self.check_output(check_pir=True)
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class TestAllcloseOpException(TestAllcloseOp):
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def test_check_output(self):
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def test_rtol_num():
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self.inputs['Rtol'] = np.array([1e-05, 1e-05]).astype("float64")
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self.inputs['Atol'] = np.array([1e-08]).astype("float64")
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self.check_output(check_pir=True)
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self.assertRaises(ValueError, test_rtol_num)
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def test_rtol_type():
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self.inputs['Rtol'] = np.array([5]).astype("int32")
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self.inputs['Atol'] = np.array([1e-08]).astype("float64")
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self.check_output(check_pir=True)
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self.assertRaises(ValueError, test_rtol_type)
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def test_atol_num():
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self.inputs['Rtol'] = np.array([1e-05]).astype("float64")
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self.inputs['Atol'] = np.array([1e-08, 1e-08]).astype("float64")
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self.check_output(check_pir=True)
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self.assertRaises(ValueError, test_atol_num)
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def test_atol_type():
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self.inputs['Rtol'] = np.array([1e-05]).astype("float64")
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self.inputs['Atol'] = np.array([8]).astype("int32")
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self.check_output(check_pir=True)
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self.assertRaises(ValueError, test_atol_type)
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class TestAllcloseOpSmallNum(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([10000.0, 1e-08]).astype("float32")
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self.other = np.array([10000.1, 1e-09]).astype("float32")
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self.rtol = np.array([1e-05]).astype("float64")
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self.atol = np.array([1e-08]).astype("float64")
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self.equal_nan = False
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class TestAllcloseOpNanFalse(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([1.0, float('nan')]).astype("float32")
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self.other = np.array([1.0, float('nan')]).astype("float32")
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self.rtol = np.array([1e-05]).astype("float64")
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self.atol = np.array([1e-08]).astype("float64")
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self.equal_nan = False
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class TestAllcloseOpNanTrue(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([1.0, float('nan')]).astype("float32")
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self.other = np.array([1.0, float('nan')]).astype("float32")
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self.rtol = np.array([1e-05]).astype("float64")
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self.atol = np.array([1e-08]).astype("float64")
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self.equal_nan = True
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class TestAllcloseDygraph(unittest.TestCase):
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def test_api_case(self):
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paddle.disable_static()
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x_data = np.random.rand(10, 10)
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y_data = np.random.rand(10, 10)
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x = paddle.to_tensor(x_data)
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y = paddle.to_tensor(y_data)
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out = paddle.allclose(x, y, rtol=1e-05, atol=1e-08)
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expected_out = np.allclose(x_data, y_data, rtol=1e-05, atol=1e-08)
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self.assertTrue((out.numpy() == expected_out).all(), True)
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paddle.enable_static()
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class TestAllcloseError(unittest.TestCase):
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def test_input_dtype(self):
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def test_x_dtype():
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with paddle.static.program_guard(
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paddle.static.Program(), paddle.static.Program()
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):
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x = paddle.static.data(
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name='x', shape=[10, 10], dtype='complex32'
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)
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y = paddle.static.data(
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name='y', shape=[10, 10], dtype='float64'
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)
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result = paddle.allclose(x, y)
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self.assertRaises(TypeError, test_x_dtype)
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def test_y_dtype():
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with paddle.static.program_guard(
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paddle.static.Program(), paddle.static.Program()
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):
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x = paddle.static.data(
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name='x', shape=[10, 10], dtype='float64'
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)
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y = paddle.static.data(
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name='y', shape=[10, 10], dtype='complex32'
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)
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result = paddle.allclose(x, y)
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self.assertRaises(TypeError, test_y_dtype)
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class TestAllcloseOpFp16(unittest.TestCase):
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def test_fp16(self):
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if core.is_compiled_with_cuda() or is_custom_device():
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x_data = np.random.rand(10, 10).astype('float16')
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y_data = np.random.rand(10, 10).astype('float16')
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with paddle.static.program_guard(paddle.static.Program()):
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x = paddle.static.data(
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shape=[10, 10], name='x', dtype='float16'
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)
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y = paddle.static.data(
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shape=[10, 10], name='y', dtype='float16'
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)
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out = paddle.allclose(x, y, rtol=1e-05, atol=1e-08)
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place = get_device_place()
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(feed={'x': x_data, 'y': y_data}, fetch_list=[out])
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class TestAllcloseOpFloat16(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([10.1]).astype("float16")
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self.other = np.array([10]).astype("float16")
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self.rtol = np.array([0.01]).astype("float64")
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self.atol = np.array([0]).astype("float64")
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self.equal_nan = False
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def test_check_output(self):
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if core.is_compiled_with_cuda() or is_custom_device():
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place = get_device_place()
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if core.is_float16_supported(place):
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self.check_output_with_place(place, check_pir=True)
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class TestAllcloseOpFloat32(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([10.1]).astype("float32")
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self.other = np.array([10]).astype("float32")
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self.rtol = np.array([0.01]).astype("float64")
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self.atol = np.array([0]).astype("float64")
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self.equal_nan = False
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class TestAllcloseOpFloat64(TestAllcloseOp):
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def set_args(self):
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self.input = np.array([10.1]).astype("float64")
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self.other = np.array([10]).astype("float64")
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self.rtol = np.array([0.01]).astype("float64")
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self.atol = np.array([0]).astype("float64")
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self.equal_nan = False
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class TestAllcloseOpBool(unittest.TestCase):
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def test_close_True(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([1]).astype("bool")
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self.other = np.array([1]).astype("bool")
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self.rtol = np.array([0.0]).astype("float32")
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self.atol = np.array([0.0]).astype("float32")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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True,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='bool')
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y = paddle.static.data(shape=[1], name='y', dtype='bool')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], True)
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def test_close_False(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([0]).astype("bool")
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self.other = np.array([1]).astype("bool")
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self.rtol = np.array([0.0]).astype("float32")
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self.atol = np.array([0.0]).astype("float32")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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False,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='bool')
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y = paddle.static.data(shape=[1], name='y', dtype='bool')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], False)
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class TestAllcloseOpInt32(unittest.TestCase):
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def test_close_True(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([100]).astype("int32")
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self.other = np.array([1]).astype("int32")
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self.rtol = np.array([50.0]).astype("float32")
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self.atol = np.array([49]).astype("float32")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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True,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='int32')
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y = paddle.static.data(shape=[1], name='y', dtype='int32')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], True)
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def test_close_False(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([100]).astype("int32")
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self.other = np.array([1]).astype("int32")
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self.rtol = np.array([50.0]).astype("float32")
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self.atol = np.array([48]).astype("float32")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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False,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='int32')
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y = paddle.static.data(shape=[1], name='y', dtype='int32')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], False)
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class TestAllcloseOpInt64(unittest.TestCase):
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def test_close_True(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([100]).astype("int64")
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self.other = np.array([1]).astype("int64")
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self.rtol = np.array([50.0]).astype("float64")
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self.atol = np.array([49]).astype("float64")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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True,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='int64')
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y = paddle.static.data(shape=[1], name='y', dtype='int64')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], True)
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def test_close_False(self):
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places = [paddle.CPUPlace()]
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if core.is_compiled_with_cuda() or is_custom_device():
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places.append(get_device_place())
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for place in places:
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with dygraph_guard():
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# absolute(a−b)≤(atol+rtol×absolute(b))
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self.input = np.array([100]).astype("int64")
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self.other = np.array([1]).astype("int64")
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self.rtol = np.array([50.0]).astype("float64")
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self.atol = np.array([48]).astype("float64")
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self.equal_nan = False
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input = paddle.to_tensor(self.input, place=place)
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other = paddle.to_tensor(self.other, place=place)
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self.assertEqual(
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paddle.allclose(
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input, other, self.rtol, self.atol, self.equal_nan
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).item(),
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False,
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)
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with (
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static_guard(),
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paddle.static.program_guard(paddle.static.Program()),
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):
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x = paddle.static.data(shape=[1], name='x', dtype='int64')
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y = paddle.static.data(shape=[1], name='y', dtype='int64')
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out = paddle.allclose(
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x, y, self.rtol.item(), self.atol.item(), self.equal_nan
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)
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exe = paddle.static.Executor(place)
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exe.run(paddle.static.default_startup_program())
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out = exe.run(
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feed={'x': self.input, 'y': self.other},
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fetch_list=[out],
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)
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self.assertEqual(out[0], False)
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class TestAllcloseOpLargeDimInput(TestAllcloseOp):
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def set_args(self):
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self.input = np.array(np.zeros([2048, 1024])).astype("float64")
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self.other = np.array(np.zeros([2048, 1024])).astype("float64")
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self.input[-1][-1] = 100
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self.rtol = np.array([1e-05]).astype("float64")
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self.atol = np.array([1e-08]).astype("float64")
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self.equal_nan = False
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class TestAllcloseOp_ZeroSize(OpTest):
|
||
def set_args(self):
|
||
self.input = np.random.random((2, 0)).astype("float32")
|
||
self.other = np.random.random((2, 0)).astype("float32")
|
||
self.rtol = np.array([1e-05]).astype("float64")
|
||
self.atol = np.array([1e-08]).astype("float64")
|
||
self.equal_nan = False
|
||
|
||
def setUp(self):
|
||
self.set_args()
|
||
self.op_type = "allclose"
|
||
self.python_api = paddle.allclose
|
||
self.inputs = {
|
||
'Input': self.input,
|
||
'Other': self.other,
|
||
"Rtol": self.rtol,
|
||
"Atol": self.atol,
|
||
}
|
||
self.attrs = {'equal_nan': self.equal_nan}
|
||
self.outputs = {
|
||
'Out': np.array(
|
||
np.allclose(
|
||
self.inputs['Input'],
|
||
self.inputs['Other'],
|
||
rtol=self.rtol,
|
||
atol=self.atol,
|
||
equal_nan=self.equal_nan,
|
||
)
|
||
)
|
||
}
|
||
|
||
def test_check_output(self):
|
||
self.check_output(check_pir=True)
|
||
|
||
|
||
class TestAllcloseAlias(unittest.TestCase):
|
||
def test_alias(self):
|
||
paddle.disable_static()
|
||
x_np = np.array([10000.0, 1e-07]).astype("float32")
|
||
y_np = np.array([10000.1, 1e-08]).astype("float32")
|
||
x = paddle.to_tensor(x_np)
|
||
y = paddle.to_tensor(y_np)
|
||
|
||
# Test with input and other
|
||
res1 = paddle.allclose(input=x, other=y, rtol=1e-05, atol=1e-08)
|
||
res2 = paddle.allclose(x, y, rtol=1e-05, atol=1e-08)
|
||
|
||
# Test with input and y
|
||
res3 = paddle.allclose(input=x, y=y, rtol=1e-05, atol=1e-08)
|
||
|
||
# Test with x and other
|
||
res4 = paddle.allclose(x=x, other=y, rtol=1e-05, atol=1e-08)
|
||
|
||
self.assertEqual(res1.item(), res2.item())
|
||
self.assertEqual(res1.item(), res3.item())
|
||
self.assertEqual(res1.item(), res4.item())
|
||
self.assertFalse(res1.item())
|
||
|
||
# Test with equal_nan
|
||
x_nan = paddle.to_tensor([1.0, float('nan')])
|
||
y_nan = paddle.to_tensor([1.0, float('nan')])
|
||
|
||
res_nan = paddle.allclose(input=x_nan, other=y_nan, equal_nan=True)
|
||
self.assertTrue(res_nan.item())
|
||
|
||
def test_tensor_method_alias(self):
|
||
paddle.disable_static()
|
||
x = paddle.to_tensor([10000.0, 1e-07])
|
||
y = paddle.to_tensor([10000.1, 1e-08])
|
||
|
||
# Test with other alias for y
|
||
res = x.allclose(other=y, rtol=1e-05, atol=1e-08)
|
||
self.assertFalse(res.item())
|
||
|
||
|
||
if __name__ == "__main__":
|
||
unittest.main()
|