Commit 912f2fee authored by Nicola Gatto's avatar Nicola Gatto
Browse files

Remove license header on target test files

parent 7aeb41ef
Pipeline #188401 passed with stages
in 4 minutes and 2 seconds
/* (c) https://github.com/MontiCore/monticore */
#ifndef CNNBUFFERFILE_H
#define CNNBUFFERFILE_H
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import os
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import os
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import os
......
# (c) https://github.com/MontiCore/monticore
import os
import h5py
import mxnet as mx
......
# (c) https://github.com/MontiCore/monticore
import os
import h5py
import mxnet as mx
......
# (c) https://github.com/MontiCore/monticore
import os
import h5py
import mxnet as mx
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import numpy as np
from mxnet import gluon
......@@ -91,13 +90,14 @@ class Net_0(gluon.HybridBlock):
else:
self.input_normalization_data_ = NoNormalization()
self.conv1_padding = Padding(padding=(0,0,0,0,2,1,2,1))
self.conv1_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.conv1_ = gluon.nn.Conv2D(channels=96,
kernel_size=(11,11),
strides=(4,4),
use_bias=True)
# conv1_, output shape: {[96,55,55]}
self.pool1_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.pool1_ = gluon.nn.MaxPool2D(
pool_size=(3,3),
strides=(2,2))
......@@ -114,6 +114,7 @@ class Net_0(gluon.HybridBlock):
use_bias=True)
# conv2_1_, output shape: {[128,27,27]}
self.pool2_1_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.pool2_1_ = gluon.nn.MaxPool2D(
pool_size=(3,3),
strides=(2,2))
......@@ -127,6 +128,7 @@ class Net_0(gluon.HybridBlock):
use_bias=True)
# conv2_2_, output shape: {[128,27,27]}
self.pool2_2_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.pool2_2_ = gluon.nn.MaxPool2D(
pool_size=(3,3),
strides=(2,2))
......@@ -162,6 +164,7 @@ class Net_0(gluon.HybridBlock):
use_bias=True)
# conv5_1_, output shape: {[128,13,13]}
self.pool5_1_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.pool5_1_ = gluon.nn.MaxPool2D(
pool_size=(3,3),
strides=(2,2))
......@@ -183,6 +186,7 @@ class Net_0(gluon.HybridBlock):
use_bias=True)
# conv5_2_, output shape: {[128,13,13]}
self.pool5_2_padding = Padding(padding=(0,0,-1,0,0,0,0,0))
self.pool5_2_ = gluon.nn.MaxPool2D(
pool_size=(3,3),
strides=(2,2))
......@@ -217,7 +221,8 @@ class Net_0(gluon.HybridBlock):
beta=0.75,
knorm=2,
nsize=5)
pool1_ = self.pool1_(lrn1_)
pool1_padding = self.pool1_padding(lrn1_)
pool1_ = self.pool1_(pool1_padding)
relu1_ = self.relu1_(pool1_)
split1_ = self.split1_(relu1_)
get2_1_ = split1_[0]
......@@ -228,7 +233,8 @@ class Net_0(gluon.HybridBlock):
beta=0.75,
knorm=2,
nsize=5)
pool2_1_ = self.pool2_1_(lrn2_1_)
pool2_1_padding = self.pool2_1_padding(lrn2_1_)
pool2_1_ = self.pool2_1_(pool2_1_padding)
relu2_1_ = self.relu2_1_(pool2_1_)
get2_2_ = split1_[1]
conv2_2_padding = self.conv2_2_padding(get2_2_)
......@@ -238,7 +244,8 @@ class Net_0(gluon.HybridBlock):
beta=0.75,
knorm=2,
nsize=5)
pool2_2_ = self.pool2_2_(lrn2_2_)
pool2_2_padding = self.pool2_2_padding(lrn2_2_)
pool2_2_ = self.pool2_2_(pool2_2_padding)
relu2_2_ = self.relu2_2_(pool2_2_)
concatenate3_ = self.concatenate3_(relu2_1_, relu2_2_)
conv3_padding = self.conv3_padding(concatenate3_)
......@@ -251,7 +258,8 @@ class Net_0(gluon.HybridBlock):
relu4_1_ = self.relu4_1_(conv4_1_)
conv5_1_padding = self.conv5_1_padding(relu4_1_)
conv5_1_ = self.conv5_1_(conv5_1_padding)
pool5_1_ = self.pool5_1_(conv5_1_)
pool5_1_padding = self.pool5_1_padding(conv5_1_)
pool5_1_ = self.pool5_1_(pool5_1_padding)
relu5_1_ = self.relu5_1_(pool5_1_)
get4_2_ = split3_[1]
conv4_2_padding = self.conv4_2_padding(get4_2_)
......@@ -259,7 +267,8 @@ class Net_0(gluon.HybridBlock):
relu4_2_ = self.relu4_2_(conv4_2_)
conv5_2_padding = self.conv5_2_padding(relu4_2_)
conv5_2_ = self.conv5_2_(conv5_2_padding)
pool5_2_ = self.pool5_2_(conv5_2_)
pool5_2_padding = self.pool5_2_padding(conv5_2_)
pool5_2_ = self.pool5_2_(pool5_2_padding)
relu5_2_ = self.relu5_2_(pool5_2_)
concatenate6_ = self.concatenate6_(relu5_1_, relu5_2_)
fc6_ = self.fc6_(concatenate6_)
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import numpy as np
from mxnet import gluon
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import numpy as np
from mxnet import gluon
......
/* (c) https://github.com/MontiCore/monticore */
#ifndef CNNPREDICTOR_ALEXNET
#define CNNPREDICTOR_ALEXNET
......
/* (c) https://github.com/MontiCore/monticore */
#ifndef CNNPREDICTOR_CIFARCLASSIFIERNETWORK
#define CNNPREDICTOR_CIFARCLASSIFIERNETWORK
......
/* (c) https://github.com/MontiCore/monticore */
#ifndef CNNPREDICTOR_VGG16
#define CNNPREDICTOR_VGG16
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import numpy as np
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import numpy as np
......
# (c) https://github.com/MontiCore/monticore
import mxnet as mx
import logging
import numpy as np
......
# (c) https://github.com/MontiCore/monticore
import logging
import mxnet as mx
import CNNCreator_emptyConfig
......
# (c) https://github.com/MontiCore/monticore
import logging
import mxnet as mx
import CNNCreator_fullConfig
......
# (c) https://github.com/MontiCore/monticore
import logging
import mxnet as mx
import CNNCreator_simpleConfig
......
# (c) https://github.com/MontiCore/monticore
from reinforcement_learning.agent import DqnAgent
from reinforcement_learning.util import AgentSignalHandler
from reinforcement_learning.cnnarch_logger import ArchLogger
......
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