wehub-resource-sync
276 lines
8.7 KiB
Python
276 lines
8.7 KiB
Python
# Copyright (c) 2023 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 get_device_place, get_places, is_custom_device
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import paddle
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def get_ref_api():
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return (
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np.trapezoid
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if np.lib.NumpyVersion(np.__version__) >= "2.0.0"
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else np.trapz # noqa: NPY201
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)
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class TestTrapezoidAPI(unittest.TestCase):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float32')
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self.x = None
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self.dx = None
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self.axis = -1
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def get_output(self):
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if self.x is None and self.dx is None:
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self.output = self.ref_api(
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y=self.y, x=self.x, dx=1.0, axis=self.axis
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)
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else:
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self.output = self.ref_api(
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y=self.y, x=self.x, dx=self.dx, axis=self.axis
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)
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def set_api(self):
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self.ref_api = get_ref_api()
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self.paddle_api = paddle.trapezoid
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def setUp(self):
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self.set_api()
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self.set_args()
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self.get_output()
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self.places = get_places()
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def func_dygraph(self):
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for place in self.places:
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paddle.disable_static()
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y = paddle.to_tensor(self.y, place=place)
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if self.x is not None:
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self.x = paddle.to_tensor(self.x, place=place)
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if self.dx is not None:
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self.dx = paddle.to_tensor(self.dx, place=place)
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out = self.paddle_api(y=y, x=self.x, dx=self.dx, axis=self.axis)
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np.testing.assert_allclose(out, self.output, rtol=1e-05)
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def test_dygraph(self):
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self.setUp()
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self.func_dygraph()
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def test_static(self):
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paddle.enable_static()
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for place in get_places():
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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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y = paddle.static.data(
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name="y", shape=self.y.shape, dtype=self.y.dtype
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)
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x = None
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dx = None
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if self.x is not None:
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x = paddle.static.data(
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name="x", shape=self.x.shape, dtype=self.x.dtype
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)
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if self.dx is not None:
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dx = paddle.static.data(
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name="dx", shape=[], dtype='float32'
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)
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exe = paddle.static.Executor(place)
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out = self.paddle_api(y=y, x=x, dx=dx, axis=self.axis)
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fetches = exe.run(
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paddle.static.default_main_program(),
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feed={
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"y": self.y,
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"x": self.x,
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"dx": self.dx,
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"axis": self.axis,
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},
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fetch_list=[out],
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)
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np.testing.assert_allclose(fetches[0], self.output, rtol=1e-05)
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class TestTrapezoidWithX(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float32')
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self.x = np.array([[1, 2, 3], [3, 4, 5]]).astype('float32')
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self.dx = None
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self.axis = -1
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class TestTrapezoidAxis(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float32')
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self.x = None
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self.dx = 1.0
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self.axis = 0
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class TestTrapezoidWithDx(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float32')
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self.x = None
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self.dx = 3.0
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self.axis = -1
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class TestTrapezoidfloat64(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float64')
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self.x = np.array([[1, 2, 3], [3, 4, 5]]).astype('float64')
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self.dx = None
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self.axis = -1
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class TestTrapezoidWithOutDxX(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.array([[2, 4, 8], [3, 5, 9]]).astype('float64')
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self.x = None
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self.dx = None
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self.axis = -1
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class TestTrapezoidBroadcast(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.random.random((3, 3, 4)).astype('float32')
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self.x = np.random.random(3).astype('float32')
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self.dx = None
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self.axis = 1
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class TestTrapezoidAxis1(TestTrapezoidAPI):
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def set_args(self):
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self.y = np.random.random((3, 3, 4)).astype('float32')
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self.x = None
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self.dx = 1.0
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self.axis = 1
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class TestTrapezoidError(unittest.TestCase):
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# test error
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def set_api(self):
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self.paddle_api = paddle.trapezoid
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def test_errors(self):
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self.set_api()
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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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def test_y_dtype():
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y = paddle.static.data(
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name='y',
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shape=[4, 4],
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dtype="int64",
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)
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x = paddle.static.data(name='x', shape=[4, 4], dtype="float32")
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dx = None
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self.paddle_api(y, x, dx)
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self.assertRaises(TypeError, test_y_dtype)
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def test_x_dtype():
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y1 = paddle.static.data(
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name='y1',
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shape=[4, 4],
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dtype="float32",
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)
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x1 = paddle.static.data(name='x1', shape=[4, 4], dtype="int64")
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dx1 = None
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self.paddle_api(y1, x1, dx1)
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self.assertRaises(TypeError, test_x_dtype)
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def test_dx_dim():
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y2 = paddle.static.data(
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name='y2',
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shape=[4, 4],
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dtype="float32",
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)
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x2 = None
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dx2 = paddle.static.data(
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name='dx2', shape=[4, 4], dtype="float32"
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)
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self.paddle_api(y2, x2, dx2)
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self.assertRaises(ValueError, test_dx_dim)
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def test_xwithdx():
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y3 = paddle.static.data(
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name='y3',
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shape=[4, 4],
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dtype="float32",
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)
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x3 = paddle.static.data(
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name='x3', shape=[4, 4], dtype="float32"
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)
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dx3 = 1.0
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self.paddle_api(y3, x3, dx3)
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self.assertRaises(ValueError, test_xwithdx)
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class Testfp16Trapezoid(TestTrapezoidAPI):
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def set_api(self):
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self.paddle_api = paddle.trapezoid
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self.ref_api = get_ref_api()
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def test_fp16_with_gpu(self):
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paddle.enable_static()
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if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
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place = get_device_place()
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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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input_y = np.random.random([4, 4]).astype("float16")
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y = paddle.static.data(name="y", shape=[4, 4], dtype="float16")
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input_x = np.random.random([4, 4]).astype("float16")
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x = paddle.static.data(name="x", shape=[4, 4], dtype="float16")
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exe = paddle.static.Executor(place)
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out = self.paddle_api(y=y, x=x, dx=self.dx, axis=self.axis)
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res = exe.run(
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paddle.static.default_main_program(),
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feed={
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"y": input_y,
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"x": input_x,
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"dx": self.dx,
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"axis": self.axis,
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},
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fetch_list=[out],
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)
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def test_fp16_func_dygraph(self):
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if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
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place = get_device_place()
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paddle.disable_static()
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input_y = np.random.random([4, 4])
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y = paddle.to_tensor(input_y, dtype='float16', place=place)
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input_x = np.random.random([4, 4])
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x = paddle.to_tensor(input_x, dtype='float16', place=place)
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out = self.paddle_api(y=y, x=x)
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def test_fp16_dygraph(self):
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self.func_dygraph()
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if __name__ == '__main__':
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paddle.enable_static()
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unittest.main()
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