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

67 lines
2.4 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 unittest
import paddle.fluid as fluid
import numpy as np
from test_imperative_base import new_program_scope
class MLP(fluid.Layer):
def __init__(self, name_scope):
super(MLP, self).__init__(name_scope)
self._fc1 = fluid.dygraph.FC(
self.full_name(),
3,
param_attr=fluid.ParamAttr(
initializer=fluid.initializer.Constant(value=0.1)),
bias_attr=fluid.ParamAttr(
initializer=fluid.initializer.Constant(value=0.1)))
self._fc2 = fluid.dygraph.FC(
self.full_name(),
4,
param_attr=fluid.ParamAttr(
initializer=fluid.initializer.Constant(value=0.1)),
bias_attr=fluid.ParamAttr(
initializer=fluid.initializer.Constant(value=0.1)))
def forward(self, inputs):
x = self._fc1(inputs)
x = self._fc2(x)
x = fluid.layers.reduce_sum(x)
return x
class TestDygraphFramework(unittest.TestCase):
def test_dygraph_backward(self):
with new_program_scope():
mlp = MLP("mlp")
var_inp = fluid.layers.data(
"input", shape=[2, 2], dtype="float32", append_batch_size=False)
out = mlp(var_inp)
try:
out.backward()
raise AssertionError(
"backward should not be usable in static graph mode")
except ValueError as e:
self.assertTrue((e is not None))
def test_dygraph_to_string(self):
np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
with fluid.dygraph.guard():
var_inp = fluid.dygraph.base.to_variable(np_inp)
var_inp.to_string(throw_on_error=True)