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Paddle/python/paddle/fluid/tests/unittests/test_full_like_op.py

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3.1 KiB

# Copyright (c) 2019 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.
from __future__ import print_function
import paddle
import paddle.fluid.core as core
from paddle.static import program_guard, Program
import paddle.compat as cpt
import unittest
import numpy as np
from op_test import OpTest
class TestFullOp(unittest.TestCase):
""" Test fill_any_like op(whose API is full_like) for attr out. """
def test_attr_tensor_API(self):
startup_program = Program()
train_program = Program()
with program_guard(train_program, startup_program):
fill_value = 2.0
input = paddle.fluid.data(name='input', dtype='float32', shape=[2, 3])
output = paddle.full_like(input, fill_value)
output_dtype = paddle.full_like(input, fill_value, dtype='float32')
place = paddle.CPUPlace()
if core.is_compiled_with_cuda():
place = paddle.CUDAPlace(0)
exe = paddle.static.Executor(place)
exe.run(startup_program)
img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
res = exe.run(train_program,
feed={'input': img},
fetch_list=[output])
out_np = np.array(res[0])
self.assertTrue(
not (out_np - np.full_like(img, fill_value)).any(),
msg="full_like output is wrong, out = " + str(out_np))
def test_full_like_imperative(self):
paddle.disable_static()
input = paddle.arange(6, 10, dtype='float32')
out = paddle.full_like(input, fill_value=888.88, dtype='float32')
out_numpy = np.random.random((4)).astype("float32")
out_numpy.fill(888.88)
self.assertTrue((out.numpy() == out_numpy).all(), True)
paddle.enable_static()
class TestFullOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
#for ci coverage
input_data = paddle.fluid.data(
name='input', dtype='float32', shape=[2, 3])
output = paddle.full_like(input_data, 2.0)
def test_input_dtype():
paddle.full_like
self.assertRaises(
TypeError,
paddle.full_like,
x=input_data,
fill_value=2,
dtype='uint4')
self.assertRaises(
TypeError,
paddle.full_like,
x=input_data,
fill_value=2,
dtype='int16')
if __name__ == "__main__":
unittest.main()