wehub-resource-sync
538 lines
17 KiB
Python
Executable File
538 lines
17 KiB
Python
Executable File
# 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 (
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OpTest,
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convert_float_to_uint16,
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get_device_place,
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is_custom_device,
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)
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import paddle
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from paddle.base import core
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np.random.seed(100)
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paddle.seed(100)
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def ref_copysign(x, y):
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out_dtype = x.dtype
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return np.copysign(x, y).astype(out_dtype)
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def ref_grad_copysign(x, y, dout):
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out = np.copysign(x, y)
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return dout * out / x
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class TestCopySignOp(OpTest):
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def setUp(self):
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self.op_type = "copysign"
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self.python_api = paddle.copysign
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self.init_config()
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self.inputs = {'x': self.x, 'y': self.y}
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self.target = ref_copysign(self.inputs['x'], self.inputs['y'])
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self.outputs = {'out': self.target}
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def test_check_output(self):
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self.check_output(check_pir=True, check_symbol_infer=False)
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def test_check_grad(self):
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self.check_grad(['x', 'y'], ['out'], check_pir=True)
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def test_check_grad_ignore_x(self):
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self.check_grad(['y'], ['out'], check_pir=True)
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def test_check_grad_ignore_y(self):
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self.check_grad(['x'], ['out'], check_pir=True)
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def init_config(self):
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self.x = np.random.randn(20, 6).astype('float64')
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self.y = np.random.randn(20, 6).astype('float64')
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@unittest.skipIf(
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not (core.is_compiled_with_cuda() or is_custom_device())
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or not core.is_bfloat16_supported(get_device_place()),
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"core is not compiled with CUDA or not support the bfloat16",
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)
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class TestCopySignBF16(OpTest):
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def setUp(self):
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self.op_type = "copysign"
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self.python_api = paddle.copysign
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self.init_dtype()
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np.random.seed(1024)
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x = np.random.randn(20, 6).astype(np.float32)
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y = np.random.randn(20, 6).astype(np.float32)
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out = ref_copysign(x, y)
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self.inputs = {
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'x': convert_float_to_uint16(x),
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'y': convert_float_to_uint16(y),
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}
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self.outputs = {'out': convert_float_to_uint16(out)}
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self.place = get_device_place()
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def init_dtype(self):
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self.dtype = np.uint16
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def test_check_output(self):
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place = get_device_place()
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self.check_output_with_place(
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place, check_pir=True, check_symbol_infer=False
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)
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def test_check_grad(self):
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self.check_grad_with_place(
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self.place, ['x', 'y'], ['out'], check_pir=True
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)
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def test_check_grad_ignore_x(self):
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self.check_grad_with_place(
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self.place, ['y'], ['out'], no_grad_set=set('x'), check_pir=True
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)
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def test_check_grad_ignore_y(self):
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self.check_grad_with_place(
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self.place, ['x'], ['out'], no_grad_set=set('y'), check_pir=True
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)
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class TestCopySignAPI(unittest.TestCase):
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def setUp(self):
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self.input_init()
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self.place_init()
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def input_init(self):
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self.x = np.random.randn(20, 6).astype('float64')
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self.y = np.random.randn(20, 6).astype('float64')
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def place_init(self):
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self.place = get_device_place()
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def test_static_api(self):
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paddle.enable_static()
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with paddle.static.program_guard(paddle.static.Program()):
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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 isinstance(self.y, (float, int)):
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y = self.y
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else:
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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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out = paddle.copysign(x, y)
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exe = paddle.static.Executor(self.place)
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if isinstance(self.y, (float, int)):
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res = exe.run(
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paddle.static.default_main_program(),
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feed={"x": self.x},
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fetch_list=[out],
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)
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else:
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res = exe.run(
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paddle.static.default_main_program(),
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feed={"x": self.x, "y": self.y},
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fetch_list=[out],
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)
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out_ref = ref_copysign(self.x, self.y)
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np.testing.assert_allclose(out_ref, res[0])
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out_ref_dtype = out_ref.dtype
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np.testing.assert_equal((out_ref_dtype == res[0].dtype), True)
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paddle.disable_static()
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def test_dygraph_api(self):
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paddle.disable_static()
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x = paddle.to_tensor(self.x)
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y = paddle.to_tensor(self.y)
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out = paddle.copysign(x, y)
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out_ref = ref_copysign(self.x, self.y)
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np.testing.assert_allclose(out_ref, out.numpy())
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out_ref_dtype = out_ref.dtype
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np.testing.assert_equal((out_ref_dtype == out.numpy().dtype), True)
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paddle.enable_static()
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class TestCopySignBool(TestCopySignAPI):
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def input_init(self):
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dtype = np.bool_
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignUint8(TestCopySignAPI):
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def input_init(self):
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dtype = np.uint8
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignInt8(TestCopySignAPI):
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def input_init(self):
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dtype = np.int8
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignInt16(TestCopySignAPI):
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def input_init(self):
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dtype = np.int16
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignInt32(TestCopySignAPI):
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def input_init(self):
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dtype = np.int32
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignInt64(TestCopySignAPI):
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def input_init(self):
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dtype = np.int64
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignFloat16(TestCopySignAPI):
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def input_init(self):
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dtype = np.float16
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignFloat32(TestCopySignAPI):
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def input_init(self):
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dtype = np.float32
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignFloat64(TestCopySignAPI):
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def input_init(self):
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dtype = np.float64
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = (np.random.randn(10, 20) * 10).astype(dtype)
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class TestCopySignNumberY(TestCopySignAPI):
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def input_init(self):
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dtype = np.float32
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self.x = (np.random.randn(10, 20) * 10).astype(dtype)
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self.y = -2.0
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class TestCopySignZeroCase1(TestCopySignAPI):
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def input_init(self):
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self.x = np.zeros(shape=(10, 20))
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self.y = np.zeros(shape=(10, 20))
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class TestCopySignZeroCase2(TestCopySignAPI):
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def input_init(self):
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self.x = np.zeros(shape=(10, 20))
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self.y = np.random.randn(10, 20)
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class TestCopySignZeroCase3(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(10, 20)
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self.y = np.zeros(shape=(10, 20))
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class TestCopySignZeroDimCase1(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(0, 0)
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self.y = np.random.randn(0, 0)
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class TestCopySignZeroDimCase2(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(0, 5, 10)
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self.y = np.random.randn(0, 5, 10)
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class TestCopySignSpecialZeroCase1(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([1, 2, 3]).astype(np.float32)
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self.y = np.array([0, +0, -0]).astype(np.float32)
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class TestCopySignSpecialZeroCase2(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([0, +0, -0]).astype(np.float32)
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self.y = np.array([1, 2, 3]).astype(np.float32)
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class TestCopySignBroadcastCase1(TestCopySignAPI):
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def input_init(self):
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dtype = np.float16
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self.x = (np.random.randn(3, 4, 5) * 10).astype(dtype)
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self.y = (np.random.randn(5) * 10).astype(dtype)
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class TestCopySignBroadcastCase2(TestCopySignAPI):
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def input_init(self):
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dtype = np.float16
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self.x = (np.random.randn(3, 4, 5) * 10).astype(dtype)
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self.y = (np.random.randn(4, 5) * 10).astype(dtype)
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class TestCopySignBroadcastCase3(TestCopySignAPI):
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def input_init(self):
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dtype = np.float16
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self.x = (np.random.randn(4, 5) * 10).astype(dtype)
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self.y = (np.random.randn(3, 4, 5) * 10).astype(dtype)
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class TestCopySignZeroSize1(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(0, 5)
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self.y = np.random.randn(0, 5)
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def place_init(self):
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self.place = paddle.CPUPlace()
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class TestCopySignZeroSize2(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(0, 5)
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self.y = np.random.randn(3, 0, 5)
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def place_init(self):
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self.place = paddle.CPUPlace()
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class TestCopySignZeroSize3(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(3, 0, 5)
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self.y = np.random.randn(0, 5)
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class TestCopySignZeroSize4(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(5, 0)
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self.y = np.random.randn(3, 5, 0)
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class TestCopySignZeroSize5(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(2, 5)
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self.y = np.random.randn(0, 2, 5)
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class TestCopySignZeroSize6(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(0)
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self.y = np.random.randn(0)
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class TestCopySignTypePromotion(TestCopySignAPI):
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def input_init(self):
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self.x = np.random.randn(2, 5).astype(np.float64)
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self.y = np.random.randn(2, 5).astype(np.float32)
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class TestCopySignNan1(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
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self.y = np.array(
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[[np.nan, np.nan], [np.nan, np.nan]], dtype=np.float64
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)
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self.y.view('uint64')[0, 0] |= np.uint64(0x8000000000000000)
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class TestCopySignNan2(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float64)
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self.y = np.array(
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[[np.nan, np.nan], [np.nan, np.nan]], dtype=np.float64
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)
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self.y.view('uint64')[0, 0] &= ~np.uint64(0x8000000000000000)
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class TestCopySignNan3(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]])
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self.y = np.array([[-1.0, np.nan], [np.nan, np.nan]])
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class TestCopySignNan4(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]])
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self.y = np.array([[-0.0, np.nan], [np.nan, np.nan]])
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class TestCopySignNan5(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]])
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self.y = np.array([[0.0, np.nan], [np.nan, np.nan]])
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class TestCopySignNan6(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]])
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self.y = np.array([[1.0, np.nan], [np.nan, np.nan]])
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class TestCopySignNan7(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]], dtype=np.float64)
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self.y = np.array(
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[[np.nan, np.nan], [np.nan, np.nan]], dtype=np.float64
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)
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self.y.view('uint64')[0, 0] |= np.uint64(0x8000000000000000)
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class TestCopySignNan8(TestCopySignAPI):
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def input_init(self):
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self.x = np.array([[np.nan, 2.0], [3.0, 4.0]], dtype=np.float64)
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self.y = np.array(
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[[np.nan, np.nan], [np.nan, np.nan]], dtype=np.float64
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)
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self.y.view('uint64')[0, 0] &= ~np.uint64(0x8000000000000000)
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@unittest.skipIf(
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not (core.is_compiled_with_cuda() or is_custom_device()),
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"core is not compiled with CUDA",
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)
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class TestCopySignOp_Stride(OpTest):
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no_need_check_grad = True
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def setUp(self):
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self.op_type = "copysign"
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self.python_api = paddle.copysign
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self.public_python_api = paddle.copysign
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self.transpose_api = paddle.transpose
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self.as_stride_api = paddle.as_strided
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self.init_dtype()
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self.init_input_output()
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self.inputs_stride = {
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'x': OpTest.np_dtype_to_base_dtype(self.x),
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'y': OpTest.np_dtype_to_base_dtype(self.y_trans),
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}
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self.inputs = {
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'x': OpTest.np_dtype_to_base_dtype(self.x),
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'y': OpTest.np_dtype_to_base_dtype(self.y),
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}
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self.outputs = {'out': self.out}
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def init_dtype(self):
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self.dtype = np.float64
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self.val_dtype = np.float64
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def test_check_output(self):
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place = get_device_place()
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self.check_strided_forward = True
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self.check_output(
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place,
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)
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, [13, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [13, 17]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [1, 0]
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self.y_trans = np.transpose(self.y, self.perm)
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def test_check_gradient(self):
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pass
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class TestCopySignOp_Stride1(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, [20, 2, 13, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [20, 2, 13, 17]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [0, 1, 3, 2]
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self.y_trans = np.transpose(self.y, self.perm)
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class TestCopySignOp_Stride2(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, [20, 2, 13, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [20, 2, 13, 17]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [0, 2, 1, 3]
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self.y_trans = np.transpose(self.y, self.perm)
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class TestCopySignOp_Stride3(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, [20, 2, 13, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [20, 2, 13, 1]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [0, 1, 3, 2]
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self.y_trans = np.transpose(self.y, self.perm)
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class TestCopySignOp_Stride4(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, [1, 2, 13, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [20, 2, 13, 1]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [1, 0, 2, 3]
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self.y_trans = np.transpose(self.y, self.perm)
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class TestCopySignOp_Stride5(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "as_stride"
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self.x = np.random.uniform(0.1, 1, [23, 10, 1, 17]).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [23, 2, 13, 20]).astype(self.dtype)
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self.y_trans = self.y
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self.y = self.y[:, 0:1, :, 0:1]
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self.out = ref_copysign(self.x, self.y)
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self.shape_param = [23, 1, 13, 1]
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self.stride_param = [520, 260, 20, 1]
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class TestCopySignOp_Stride_ZeroDim1(TestCopySignOp_Stride):
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def init_input_output(self):
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self.strided_input_type = "transpose"
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self.x = np.random.uniform(0.1, 1, []).astype(self.dtype)
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self.y = np.random.uniform(0.1, 1, [13, 17]).astype(self.dtype)
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self.out = ref_copysign(self.x, self.y)
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self.perm = [1, 0]
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self.y_trans = np.transpose(self.y, self.perm)
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class TestCopySignOp_Stride_ZeroSize1(TestCopySignOp_Stride):
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def init_data(self):
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self.strided_input_type = "transpose"
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self.x = np.random.rand(1, 0, 2).astype('float32')
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self.y = np.random.rand(3, 0, 1).astype('float32')
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self.out = ref_copysign(self.x, self.y)
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self.perm = [2, 1, 0]
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self.y_trans = np.transpose(self.y, self.perm)
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if __name__ == "__main__":
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paddle.enable_static()
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unittest.main()
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