提交 350b268b 编写于 作者: X xuwei06

Adding simple operators for v2 API

上级 0ef86cbd
......@@ -27,6 +27,7 @@ from . import dataset
from . import reader
from . import plot
import attr
import op
import pooling
import inference
import networks
......
......@@ -36,9 +36,9 @@ def __map_docstr__(doc, name):
# xxx_layer to xxx
doc = re.sub(r"(?P<name>[a-z]+)_layer", r"\g<name>", doc)
# XxxxActivation to paddle.v2.Activation.Xxxx
# XxxxActivation to paddle.v2.activation.Xxxx
doc = re.sub(r"(?P<name>[A-Z][a-zA-Z]+)Activation",
r"paddle.v2.Activation.\g<name>", doc)
r"paddle.v2.activation.\g<name>", doc)
# xxx_evaluator to paddle.v2.evaluator.xxx
doc = re.sub(r"(?P<name>[a-z]+)_evaluator", r"evaluator.\g<name>", doc)
......
# Copyright (c) 2016 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 layer
import activation as act
from config_base import Layer
from paddle.trainer_config_helpers.attrs import is_compatible_with
from paddle.trainer_config_helpers.default_decorators import wrap_name_default
__all__ = []
def __register_unary_math_op__(op_name, act):
def op(input, name=None):
return layer.mixed(
input=[layer.identity_projection(input=input)], name=name, act=act)
op = wrap_name_default(op_name)(op)
op.__doc__ = type(act).__doc__
globals()[op_name] = op
__all__.append(op_name)
__register_unary_math_op__('exp', act.Exp())
__register_unary_math_op__('log', act.Log())
__register_unary_math_op__('abs', act.Abs())
__register_unary_math_op__('sigmoid', act.Sigmoid())
__register_unary_math_op__('tanh', act.Tanh())
__register_unary_math_op__('square', act.Square())
__register_unary_math_op__('relu', act.Relu())
__register_unary_math_op__('sqrt', act.Sqrt())
__register_unary_math_op__('reciprocal', act.Reciprocal())
__register_unary_math_op__('softmax', act.Softmax())
def __add__(layeroutput, other):
if is_compatible_with(other, float):
return layer.slope_intercept(input=layeroutput, intercept=other)
if not isinstance(other, Layer):
raise TypeError("Layer can only be added with"
" another Layer or a number")
if layeroutput.size == other.size:
return layer.mixed(input=[
layer.identity_projection(input=layeroutput),
layer.identity_projection(input=other)
])
if other.size != 1 and layeroutput.size != 1:
raise TypeError("Two Layer can be added only if they have equal size"
" or one of their sizes is 1. sizes are %s and %s" %
(layeroutput.size, other.size))
elif layeroutput.size == 1:
tmp = layeroutput
layeroutput = other
other = tmp
other = layer.repeat(other, layeroutput.size)
return layer.mixed(input=[
layer.identity_projection(input=layeroutput),
layer.identity_projection(input=other)
])
Layer.__radd__ = __add__
Layer.__add__ = __add__
def __neg__(layeroutput):
return layer.slope_intercept(input=layeroutput, slope=-1.0)
Layer.__neg__ = __neg__
def __sub__(layeroutput, other):
if is_compatible_with(other, float):
return layer.slope_intercept(input=layeroutput, intercept=other)
if not isinstance(other, Layer):
raise TypeError("Layer can only be subtracted with"
" another Layeroutput or a number")
return __add__(layeroutput, -other)
Layer.__sub__ = __sub__
def __rsub__(layeroutput, other):
neg = layer.slope_intercept(input=layeroutput, slope=-1.0)
return __add__(neg, other)
Layer.__rsub__ = __rsub__
def __mul__(layeroutput, other):
if is_compatible_with(other, float):
return layer.slope_intercept(input=layeroutput, slope=other)
if not isinstance(other, Layer):
raise TypeError("Layer can only be multiplied with"
" another Layer or a number")
elif layeroutput.size == 1:
return layer.scaling(input=other, weight=layeroutput)
elif other.size == 1:
return layer.scaling(input=layeroutput, weight=other)
else:
raise TypeError("At least one of the operand of '*' must be a number"
" or a Layer with size=1")
Layer.__mul__ = __mul__
Layer.__rmul__ = __mul__
add_python_test(test_v2_api test_data_feeder.py test_parameters.py
add_python_test(test_v2_api test_data_feeder.py test_op.py test_parameters.py
test_layer.py test_rnn_layer.py test_topology.py test_image.py)
# Copyright PaddlePaddle contributors. 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 paddle.v2.data_type as data_type
import paddle.v2.layer as layer
import paddle.v2.op as op
class OpTest(unittest.TestCase):
def test_op(self):
x = layer.data(name='data', type=data_type.dense_vector(128))
x = op.exp(x)
x = op.sqrt(x)
x = op.reciprocal(x)
x = op.log(x)
x = op.abs(x)
x = op.sigmoid(x)
x = op.tanh(x)
x = op.square(x)
x = op.relu(x)
y = 1 + x
y = y + 1
y = x + y
y = y - x
y = y - 2
y = 2 - y
y = 2 * y
y = y * 3
z = layer.data(name='data_2', type=data_type.dense_vector(1))
y = y * z
y = z * y
y = y + z
y = z + y
print layer.parse_network(y)
if __name__ == '__main__':
unittest.main()
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