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

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4.5 KiB

# Copyright (c) 2020 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 unittest
import numpy as np
from op_test import OpTest
import paddle.fluid.core as core
from paddle import rand
import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard
import paddle
class TestRandOpError(unittest.TestCase):
"""
This class test the input type check.
"""
def test_errors(self):
main_prog = Program()
start_prog = Program()
with program_guard(main_prog, start_prog):
def test_Variable():
x1 = fluid.create_lod_tensor(
np.zeros((4, 784)), [[1, 1, 1, 1]], fluid.CPUPlace())
rand(x1)
self.assertRaises(TypeError, test_Variable)
def test_dtype():
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
rand(shape=[dim_1, dim_2], dtype='int32')
self.assertRaises(TypeError, test_dtype)
class TestRandOp(unittest.TestCase):
"""
This class test the common usages of randop.
"""
def run_net(self, use_cuda=False):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
exe = fluid.Executor(place)
train_program = fluid.Program()
startup_program = fluid.Program()
with fluid.program_guard(train_program, startup_program):
result_0 = rand([3, 4])
result_1 = rand([3, 4], 'float64')
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
result_2 = rand(shape=[dim_1, dim_2])
var_shape = fluid.data(name='var_shape', shape=[2], dtype="int64")
result_3 = rand(var_shape)
var_shape_int32 = fluid.data(
name='var_shape_int32', shape=[2], dtype="int32")
result_4 = rand(var_shape_int32)
exe.run(startup_program)
x1 = np.array([3, 2]).astype('int64')
x2 = np.array([4, 3]).astype('int32')
ret = exe.run(
train_program,
feed={"var_shape": x1,
"var_shape_int32": x2},
fetch_list=[result_1, result_1, result_2, result_3, result_4])
def test_run(self):
self.run_net(False)
if core.is_compiled_with_cuda():
self.run_net(True)
class TestRandOpForDygraph(unittest.TestCase):
"""
This class test the common usages of randop.
"""
def run_net(self, use_cuda=False):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
with fluid.dygraph.guard(place):
rand([3, 4])
rand([3, 4], 'float64')
dim_1 = fluid.layers.fill_constant([1], "int64", 3)
dim_2 = fluid.layers.fill_constant([1], "int32", 5)
rand(shape=[dim_1, dim_2])
var_shape = fluid.dygraph.to_variable(np.array([3, 4]))
rand(var_shape)
def test_run(self):
self.run_net(False)
if core.is_compiled_with_cuda():
self.run_net(True)
class TestRandDtype(unittest.TestCase):
def test_default_dtype(self):
paddle.disable_static()
def test_default_fp16():
paddle.framework.set_default_dtype('float16')
paddle.tensor.random.rand([2, 3])
self.assertRaises(TypeError, test_default_fp16)
def test_default_fp32():
paddle.framework.set_default_dtype('float32')
out = paddle.tensor.random.rand([2, 3])
self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP32)
def test_default_fp64():
paddle.framework.set_default_dtype('float64')
out = paddle.tensor.random.rand([2, 3])
self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP64)
test_default_fp64()
test_default_fp32()
paddle.enable_static()
if __name__ == "__main__":
unittest.main()