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fix googlenet

pull/275/head
littletomatodonkey 2020-09-13 09:21:20 +00:00
parent 8200c7ba18
commit edd7382dd3
2 changed files with 41 additions and 36 deletions
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67
ppcls/modeling/architectures/googlenet.py
View File

@ -1,7 +1,10 @@
import paddle
import paddle.fluid as fluid
from paddle.fluid.param_attr import ParamAttr
from paddle.fluid.dygraph.nn import Conv2D, Pool2D, BatchNorm, Linear
from paddle import ParamAttr
import paddle.nn as nn
import paddle.nn.functional as F
from paddle.nn import Conv2d, Pool2D, BatchNorm, Linear, Dropout
from paddle.nn.initializer import Uniform
import math
__all__ = ['GoogLeNet']
@ -10,12 +13,11 @@ __all__ = ['GoogLeNet']
def xavier(channels, filter_size, name):
stdv = (3.0 / (filter_size**2 * channels))**0.5
param_attr = ParamAttr(
initializer=fluid.initializer.Uniform(-stdv, stdv),
name=name + "_weights")
initializer=Uniform(-stdv, stdv), name=name + "_weights")
return param_attr
class ConvLayer(fluid.dygraph.Layer):
class ConvLayer(nn.Layer):
def __init__(self,
num_channels,
num_filters,
@ -26,15 +28,14 @@ class ConvLayer(fluid.dygraph.Layer):
name=None):
super(ConvLayer, self).__init__()
self._conv = Conv2D(
num_channels=num_channels,
num_filters=num_filters,
filter_size=filter_size,
self._conv = Conv2d(
in_channels=num_channels,
out_channels=num_filters,
kernel_size=filter_size,
stride=stride,
padding=(filter_size - 1) // 2,
groups=groups,
act=None,
param_attr=ParamAttr(name=name + "_weights"),
weight_attr=ParamAttr(name=name + "_weights"),
bias_attr=False)
def forward(self, inputs):
@ -42,7 +43,7 @@ class ConvLayer(fluid.dygraph.Layer):
return y
class Inception(fluid.dygraph.Layer):
class Inception(nn.Layer):
def __init__(self,
input_channels,
output_channels,
@ -88,12 +89,12 @@ class Inception(fluid.dygraph.Layer):
pool = self._pool(inputs)
convprj = self._convprj(pool)
cat = fluid.layers.concat([conv1, conv3, conv5, convprj], axis=1)
cat = fluid.layers.relu(cat)
cat = paddle.concat([conv1, conv3, conv5, convprj], axis=1)
cat = F.relu(cat)
return cat
class GoogleNetDY(fluid.dygraph.Layer):
class GoogleNetDY(nn.Layer):
def __init__(self, class_dim=1000):
super(GoogleNetDY, self).__init__()
self._conv = ConvLayer(3, 64, 7, 2, name="conv1")
@ -124,40 +125,37 @@ class GoogleNetDY(fluid.dygraph.Layer):
self._pool_5 = Pool2D(pool_size=7, pool_type='avg', pool_stride=7)
self._drop = fluid.dygraph.Dropout(p=0.4)
self._drop = Dropout(p=0.4)
self._fc_out = Linear(
1024,
class_dim,
param_attr=xavier(1024, 1, "out"),
bias_attr=ParamAttr(name="out_offset"),
act="softmax")
weight_attr=xavier(1024, 1, "out"),
bias_attr=ParamAttr(name="out_offset"))
self._pool_o1 = Pool2D(pool_size=5, pool_stride=3, pool_type="avg")
self._conv_o1 = ConvLayer(512, 128, 1, name="conv_o1")
self._fc_o1 = Linear(
1152,
1024,
param_attr=xavier(2048, 1, "fc_o1"),
bias_attr=ParamAttr(name="fc_o1_offset"),
act="relu")
self._drop_o1 = fluid.dygraph.Dropout(p=0.7)
weight_attr=xavier(2048, 1, "fc_o1"),
bias_attr=ParamAttr(name="fc_o1_offset"))
self._drop_o1 = Dropout(p=0.7)
self._out1 = Linear(
1024,
class_dim,
param_attr=xavier(1024, 1, "out1"),
bias_attr=ParamAttr(name="out1_offset"),
act="softmax")
weight_attr=xavier(1024, 1, "out1"),
bias_attr=ParamAttr(name="out1_offset"))
self._pool_o2 = Pool2D(pool_size=5, pool_stride=3, pool_type='avg')
self._conv_o2 = ConvLayer(528, 128, 1, name="conv_o2")
self._fc_o2 = Linear(
1152,
1024,
param_attr=xavier(2048, 1, "fc_o2"),
weight_attr=xavier(2048, 1, "fc_o2"),
bias_attr=ParamAttr(name="fc_o2_offset"))
self._drop_o2 = fluid.dygraph.Dropout(p=0.7)
self._drop_o2 = Dropout(p=0.7)
self._out2 = Linear(
1024,
class_dim,
param_attr=xavier(1024, 1, "out2"),
weight_attr=xavier(1024, 1, "out2"),
bias_attr=ParamAttr(name="out2_offset"))
def forward(self, inputs):
@ -183,19 +181,22 @@ class GoogleNetDY(fluid.dygraph.Layer):
x = self._pool_5(ince5b)
x = self._drop(x)
x = fluid.layers.squeeze(x, axes=[2, 3])
x = paddle.squeeze(x, axis=[2, 3])
out = self._fc_out(x)
out = F.softmax(out)
x = self._pool_o1(ince4a)
x = self._conv_o1(x)
x = fluid.layers.flatten(x)
x = paddle.flatten(x, start_axis=1, stop_axis=-1)
x = self._fc_o1(x)
x = F.relu(x)
x = self._drop_o1(x)
out1 = self._out1(x)
out1 = F.softmax(out1)
x = self._pool_o2(ince4d)
x = self._conv_o2(x)
x = fluid.layers.flatten(x)
x = paddle.flatten(x, start_axis=1, stop_axis=-1)
x = self._fc_o2(x)
x = self._drop_o2(x)
out2 = self._out2(x)

10
tools/infer/infer.py
View File

@ -12,8 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from ppcls.utils.save_load import load_dygraph_pretrain
from ppcls.modeling import architectures
import paddle.fluid as fluid
import numpy as np
import argparse
@ -24,6 +22,9 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
from ppcls.modeling import architectures
from ppcls.utils.save_load import load_dygraph_pretrain
def parse_args():
def str2bool(v):
@ -108,7 +109,10 @@ def main():
data = fluid.dygraph.to_variable(data)
net.eval()
outputs = net(data)
outputs = fluid.layers.softmax(outputs)
if args.model == "GoogLeNet":
outputs = outputs[0]
else:
outputs = fluid.layers.softmax(outputs)
outputs = outputs.numpy()
probs = postprocess(outputs)