wehub-resource-sync
454 lines
16 KiB
Python
454 lines
16 KiB
Python
# Copyright (c) 2021 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, get_places, is_custom_device
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import paddle
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from paddle import base
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from paddle.base import core
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class TestIscloseOp(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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paddle.enable_static()
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self.set_args()
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self.op_type = "isclose"
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self.python_api = paddle.isclose
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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.isclose(
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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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def test_check_output(self):
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self.check_output(check_pir=True)
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class TestIscloseOpException(TestIscloseOp):
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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()
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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()
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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()
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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()
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self.assertRaises(ValueError, test_atol_type)
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class TestIscloseOpSmallNum(TestIscloseOp):
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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 TestIscloseOpNanFalse(TestIscloseOp):
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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 TestIscloseOpNanTrue(TestIscloseOp):
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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 TestIscloseStatic(unittest.TestCase):
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def test_api_case(self):
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paddle.enable_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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for place in get_places():
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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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='float64'
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)
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result = paddle.isclose(x, y)
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exe = paddle.base.Executor(place)
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fetches = exe.run(
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main,
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feed={"x": x_data, "y": y_data},
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fetch_list=[result],
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)
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expected_out = np.isclose(x_data, y_data)
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self.assertTrue((fetches[0] == expected_out).all(), True)
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class TestIscloseDygraph(unittest.TestCase):
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def test_api_case(self):
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for place in get_places():
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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, place=place)
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y = paddle.to_tensor(y_data, place=place)
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out = paddle.isclose(x, y, rtol=1e-05, atol=1e-08)
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expected_out = np.isclose(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 TestIscloseError(unittest.TestCase):
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def test_input_dtype(self):
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paddle.enable_static()
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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(name='x', shape=[10, 10], dtype='int32')
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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.isclose(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(name='y', shape=[10, 10], dtype='int32')
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result = paddle.isclose(x, y)
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self.assertRaises(TypeError, test_y_dtype)
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def test_attr(self):
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paddle.enable_static()
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x = paddle.static.data(name='x', shape=[10, 10], dtype='float64')
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y = paddle.static.data(name='y', shape=[10, 10], dtype='float64')
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def test_rtol():
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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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result = paddle.isclose(x, y, rtol="True")
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self.assertRaises(TypeError, test_rtol)
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def test_atol():
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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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result = paddle.isclose(x, y, atol="True")
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self.assertRaises(TypeError, test_atol)
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def test_equal_nan():
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result = paddle.isclose(x, y, equal_nan=1)
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self.assertRaises(TypeError, test_equal_nan)
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class TestIscloseOpFp16(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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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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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.isclose(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(startup)
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out = exe.run(feed={'x': x_data, 'y': y_data}, fetch_list=[out])
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class TestIscloseOpFloat16(TestIscloseOp):
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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 TestIscloseOpFloat32(TestIscloseOp):
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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 TestIscloseOpFloat64(TestIscloseOp):
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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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def test_check_output(self):
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self.check_output(check_pir=True)
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class TestIscloseOpCp64(unittest.TestCase):
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def test_cp64(self):
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x_data = (
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np.random.rand(10, 10) + 1.0j * np.random.rand(10, 10)
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).astype(np.complex64)
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y_data = (
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np.random.rand(10, 10) + 1.0j * np.random.rand(10, 10)
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).astype(np.complex64)
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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x = paddle.static.data(shape=[10, 10], name='x', dtype=np.complex64)
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y = paddle.static.data(shape=[10, 10], name='y', dtype=np.complex64)
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out = paddle.isclose(x, y, rtol=1e-05, atol=1e-08)
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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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exe = paddle.static.Executor(place)
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exe.run(startup)
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out = exe.run(feed={'x': x_data, 'y': y_data}, fetch_list=[out])
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class TestIscloseOpCp128(unittest.TestCase):
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def test_cp128(self):
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x_data = (
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np.random.rand(10, 10) + 1.0j * np.random.rand(10, 10)
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).astype(np.complex128)
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y_data = (
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np.random.rand(10, 10) + 1.0j * np.random.rand(10, 10)
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).astype(np.complex128)
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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x = paddle.static.data(
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shape=[10, 10], name='x', dtype=np.complex128
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)
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y = paddle.static.data(
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shape=[10, 10], name='y', dtype=np.complex128
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)
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out = paddle.isclose(x, y, rtol=1e-05, atol=1e-08)
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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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exe = paddle.static.Executor(place)
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exe.run(startup)
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out = exe.run(feed={'x': x_data, 'y': y_data}, fetch_list=[out])
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class TestIscloseOpComplex64(TestIscloseOp):
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def set_args(self):
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self.input = np.array([10.1 + 0.1j]).astype(np.complex64)
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self.other = np.array([10 + 0j]).astype(np.complex64)
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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 TestIscloseOpComplex128(TestIscloseOp):
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def set_args(self):
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self.input = np.array([10.1 + 0.1j]).astype(np.complex128)
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self.other = np.array([10 + 0j]).astype(np.complex128)
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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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self.check_output(check_pir=True)
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class TestIscloseOpLargeDimInput(TestIscloseOp):
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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 TestIscloseOpDoubleTol(TestIscloseOp):
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def set_args(self):
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self.input = np.array([1.0, 1e-9]).astype("float64")
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self.other = np.array([1.0, 1e-10]).astype("float64")
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self.rtol = np.array([1e-13]).astype("float64")
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self.atol = np.array([1e-14]).astype("float64")
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self.equal_nan = False
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class TestIscloseZeroSize(TestIscloseOp):
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def set_args(self):
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self.input = np.zeros([3, 0, 5]).astype("float64")
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self.other = np.zeros([3, 0, 5]).astype("float64")
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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 TestIscloseCompatibility:
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def setUp(self):
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np.random.seed(123)
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paddle.enable_static()
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self.shape = [5, 6]
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self.dtype = 'float32'
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self.init_data()
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def init_data(self):
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self.np_input = np.random.randint(0, 8, self.shape).astype(self.dtype)
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def test_dygraph_Compatibility(self):
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paddle.disable_static()
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x = paddle.to_tensor(self.np_input)
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y = paddle.to_tensor(self.np_input)
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paddle_dygraph_out = []
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# Position args (args)
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out1 = paddle.isclose(x, y)
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paddle_dygraph_out.append(out1)
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# Keywords args (kwargs) for paddle
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out2 = paddle.isclose(x=x, y=y)
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paddle_dygraph_out.append(out2)
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# Keywords args for torch
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out3 = paddle.isclose(input=x, other=y)
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paddle_dygraph_out.append(out3)
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# Tensor method args
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out5 = x.isclose(y)
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paddle_dygraph_out.append(out5)
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# Tensor method kwargs
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out6 = x.isclose(other=y)
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paddle_dygraph_out.append(out6)
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# Numpy reference out
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ref_out = np.isclose(self.np_input, self.np_input)
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# Check
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for out in paddle_dygraph_out:
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np.testing.assert_allclose(ref_out, out.numpy())
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paddle.enable_static()
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def test_static_Compatibility(self):
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with base.program_guard(main, startup):
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x = paddle.static.data(name="x", shape=self.shape, dtype=self.dtype)
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y = paddle.static.data(name="y", shape=self.shape, dtype=self.dtype)
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# Position args (args)
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out1 = paddle.isclose(x, y)
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# Keywords args (kwargs) for paddle
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out2 = paddle.isclose(x=x, y=y)
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# Keywords args for torch
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out3 = paddle.isclose(input=x, other=y)
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# Tensor method args
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out4 = x.isclose(y)
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exe = base.Executor(paddle.CPUPlace())
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fetches = exe.run(
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main,
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feed={"x": self.np_input, "y": self.np_input},
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fetch_list=[out1, out2, out3, out4],
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)
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ref_out = np.isclose(self.np_input, self.np_input)
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for out in fetches:
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np.testing.assert_allclose(out, ref_out)
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def test_rol_dtype_error(self):
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with base.program_guard(main, startup):
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x = paddle.static.data(name="x", shape=self.shape, dtype=self.dtype)
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y = paddle.static.data(name="y", shape=self.shape, dtype=self.dtype)
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rol = paddle.static.data(name="rol", shape=[1], dtype="float32")
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# Position args (args)
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out1 = paddle.isclose(x, y, rol=rol)
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exe = base.Executor(paddle.CPUPlace())
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fetches = exe.run(
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main,
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feed={"x": self.np_input, "y": self.np_input, "rol": 0.1},
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fetch_list=[out1],
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)
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ref_out = np.isclose(self.np_input, self.np_input)
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for out in fetches:
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np.testing.assert_allclose(out, ref_out)
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if __name__ == "__main__":
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paddle.enable_static()
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unittest.main()
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