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test_atan2_op.py
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test_atan2_op.py
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import numpy as np
from eager_op_test import OpTest, convert_float_to_uint16
import paddle
from paddle.fluid import core
paddle.enable_static()
np.random.seed(0)
def atan2_grad(x1, x2, dout):
dx1 = dout * x2 / (x1 * x1 + x2 * x2)
dx2 = -dout * x1 / (x1 * x1 + x2 * x2)
return dx1, dx2
class TestAtan2(OpTest):
def setUp(self):
self.op_type = "atan2"
self.python_api = paddle.atan2
self.check_cinn = True
self.init_dtype()
x1 = np.random.uniform(-1, -0.1, [15, 17]).astype(self.dtype)
x2 = np.random.uniform(0.1, 1, [15, 17]).astype(self.dtype)
out = np.arctan2(x1, x2)
self.inputs = {'X1': x1, 'X2': x2}
self.outputs = {'Out': out}
def test_check_grad(self):
self.check_grad(['X1', 'X2'], 'Out', check_cinn=self.check_cinn)
def test_check_output(self):
self.check_output(check_cinn=self.check_cinn)
def init_dtype(self):
self.dtype = np.float64
class TestAtan2_float(TestAtan2):
def init_dtype(self):
self.dtype = np.float32
def test_check_grad(self):
if self.dtype not in [np.int32, np.int64]:
self.check_grad(
['X1', 'X2'],
'Out',
user_defined_grads=atan2_grad(
self.inputs['X1'],
self.inputs['X2'],
1 / self.inputs['X1'].size,
),
check_cinn=self.check_cinn,
)
class TestAtan2_float16(TestAtan2_float):
def init_dtype(self):
self.dtype = np.float16
class TestAtan2_int32(TestAtan2_float):
def init_dtype(self):
self.dtype = np.int32
class TestAtan2_int64(TestAtan2_float):
def init_dtype(self):
self.dtype = np.int64
class TestAtan2API(unittest.TestCase):
def init_dtype(self):
self.dtype = 'float64'
self.shape = [11, 17]
def setUp(self):
self.init_dtype()
self.x1 = np.random.uniform(0.1, 1, self.shape).astype(self.dtype)
self.x2 = np.random.uniform(-1, -0.1, self.shape).astype(self.dtype)
self.place = [paddle.CPUPlace()]
if core.is_compiled_with_cuda():
self.place.append(paddle.CUDAPlace(0))
def test_static_api(self):
paddle.enable_static()
def run(place):
with paddle.static.program_guard(paddle.static.Program()):
X1 = paddle.static.data('X1', self.shape, dtype=self.dtype)
X2 = paddle.static.data('X2', self.shape, dtype=self.dtype)
out = paddle.atan2(X1, X2)
exe = paddle.static.Executor(place)
res = exe.run(feed={'X1': self.x1, 'X2': self.x2})
out_ref = np.arctan2(self.x1, self.x2)
for r in res:
np.testing.assert_allclose(out_ref, r, rtol=1e-05)
for place in self.place:
run(place)
def test_dygraph_api(self):
def run(place):
paddle.disable_static(place)
X1 = paddle.to_tensor(self.x1)
X2 = paddle.to_tensor(self.x2)
out = paddle.atan2(X1, X2)
out_ref = np.arctan2(self.x1, self.x2)
np.testing.assert_allclose(out_ref, out.numpy(), rtol=1e-05)
paddle.enable_static()
for place in self.place:
run(place)
@unittest.skipIf(
not core.is_compiled_with_cuda()
or not core.is_bfloat16_supported(core.CUDAPlace(0)),
"core is not compiled with CUDA and not support the bfloat16",
)
class TestAtan2BF16OP(OpTest):
def setUp(self):
self.op_type = 'atan2'
self.python_api = paddle.atan2
self.dtype = np.uint16
self.check_cinn = True
x1 = np.random.uniform(-1, -0.1, [15, 17]).astype('float32')
x2 = np.random.uniform(0.1, 1, [15, 17]).astype('float32')
out = np.arctan2(x1, x2)
self.inputs = {
'X1': convert_float_to_uint16(x1),
'X2': convert_float_to_uint16(x2),
}
self.outputs = {'Out': convert_float_to_uint16(out)}
def test_check_output(self):
place = core.CUDAPlace(0)
self.check_output_with_place(place, check_cinn=self.check_cinn)
def test_check_grad(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place, ['X1', 'X2'], 'Out', check_cinn=self.check_cinn
)
class TestAtan2Error(unittest.TestCase):
def test_mismatch(self):
paddle.enable_static()
def test_mismatch_numel():
X = paddle.static.data('X', (1,), dtype=np.float64)
Y = paddle.static.data('Y', (0,), dtype=np.float64)
out = paddle.atan2(X, Y)
self.assertRaises(ValueError, test_mismatch_numel)
if __name__ == '__main__':
paddle.enable_static()
unittest.main()