Commit ca705888 authored by Julian Dierkes's avatar Julian Dierkes

adjusted images in ci

parent bf33e3d4
Pipeline #269160 passed with stage
in 5 minutes and 35 seconds
......@@ -19,7 +19,7 @@ git masterJobLinux:
integrationMXNetJobLinux:
stage: linux
image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/generators/emadl2cpp/integrationtests/mxnet:v0.0.4
image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/applications/gans/mnist-infogan/gans_mxnet:latest
script:
- mvn -Dorg.slf4j.simpleLogger.log.org.apache.maven.cli.transfer.Slf4jMavenTransferListener=warn -B -U clean install --settings settings.xml -Dtest=IntegrationMXNetTest
......@@ -33,7 +33,7 @@ integrationCaffe2JobLinux:
integrationGluonJobLinux:
stage: linux
image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/generators/emadl2cpp/integrationtests/mxnet:v0.0.4
image: registry.git.rwth-aachen.de/monticore/embeddedmontiarc/applications/gans/mnist-infogan/gans_mxnet:latest
script:
- mvn -Dorg.slf4j.simpleLogger.log.org.apache.maven.cli.transfer.Slf4jMavenTransferListener=warn -B -U clean install --settings settings.xml -Dtest=IntegrationGluonTest
......
......@@ -27,7 +27,7 @@ public class IntegrationGluonTest extends IntegrationTest {
deleteHashFile(Paths.get("./target/generated-sources-emadl/MultipleStreams.training_hash"));
String[] args = {"-m", "src/test/resources/models/", "-r", "MultipleStreams", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().isEmpty());
}
......@@ -40,7 +40,7 @@ public class IntegrationGluonTest extends IntegrationTest {
deleteHashFile(Paths.get("./target/generated-sources-emadl/rnnencdec/Network.training_hash"));
String[] args = {"-m", "src/test/resources/models", "-r", "rnnencdec.Main", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().isEmpty());
}
......@@ -53,7 +53,7 @@ public class IntegrationGluonTest extends IntegrationTest {
deleteHashFile(Paths.get("./target/generated-sources-emadl/rnnsearch/Network.training_hash"));
String[] args = {"-m", "src/test/resources/models", "-r", "rnnsearch.Main", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().isEmpty());
}
......@@ -65,7 +65,7 @@ public class IntegrationGluonTest extends IntegrationTest {
deleteHashFile(Paths.get("./target/generated-sources-emadl/showAttendTell/Show_attend_tell.training_hash"));
String[] args = {"-m", "src/test/resources/models", "-r", "showAttendTell.Main", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().isEmpty());
}
......@@ -75,7 +75,7 @@ public class IntegrationGluonTest extends IntegrationTest {
Log.getFindings().clear();
deleteHashFile(Paths.get("./target/generated-sources-emadl/PreprocessingNetwork.training_hash"));
String[] args = {"-m", "src/test/resources/models/", "-r", "PreprocessingNetwork", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().toString(),Log.getFindings().size() == 0);
}
......@@ -84,7 +84,7 @@ public class IntegrationGluonTest extends IntegrationTest {
Log.getFindings().clear();
deleteHashFile(Paths.get("./target/generated-sources-emadl/defaultGANPreprocessing/GeneratorWithPreprocessing.training_hash"));
String[] args = {"-m", "src/test/resources/models/ganModel", "-r", "defaultGANPreprocessing.GeneratorWithPreprocessing", "-b", "GLUON"};
//EMADLGeneratorCli.main(args);
EMADLGeneratorCli.main(args);
assertTrue(Log.getFindings().toString(), Log.getFindings().size() == 0);
}
......
......@@ -2,7 +2,7 @@
package defaultGANPreprocessing;
component DiscriminatorWithPreprocessing{
ports in Q(-1:1)^{3, 32, 32} data,
ports in Q(-1:1)^{3, 64, 64} data,
out Q(-oo:oo)^{1} dis;
implementation CNN {
......@@ -16,6 +16,9 @@ component DiscriminatorWithPreprocessing{
Convolution(kernel=(4,4),channels=256, stride=(2,2)) ->
BatchNorm() ->
LeakyRelu(alpha=0.2) ->
Convolution(kernel=(4,4),channels=512, stride=(2,2)) ->
BatchNorm() ->
LeakyRelu(alpha=0.2) ->
Convolution(kernel=(4,4),channels=1, stride=(1,1)) ->
Sigmoid() ->
dis;
......
......@@ -3,12 +3,15 @@ package defaultGANPreprocessing;
component GeneratorWithPreprocessing{
ports in Q(0:1)^{100} noise,
out Q(-1:1)^{3, 32, 32} data;
out Q(-1:1)^{3, 64, 64} data;
implementation CNN {
noise ->
Reshape(shape=(100,1,1)) ->
UpConvolution(kernel=(4,4), channels=512, stride=(1,1), padding="valid", no_bias=true) ->
BatchNorm() ->
Relu() ->
UpConvolution(kernel=(4,4), channels=256, stride=(2,2), no_bias=true) ->
BatchNorm() ->
Relu() ->
......
package defaultGANPreprocessing;
component Main{
ports in Z(-oo:oo)^{100} noise,
out Z(-00:00)^{3,32,64} data;
instance GeneratorWithPreprocessing net;
connect noise -> net.noise;
connect net.data -> data;
}
......@@ -5,13 +5,14 @@ component ProcessingWithPreprocessing
{
ports in Q(-oo:oo)^{3,32,32} data,
in Q(0:1) softmax_label,
out Q(-1:1)^{3,32,32} data_out,
out Q(-1:1)^{3,64,64} data_out,
out Q(0:1) softmax_label_out;
implementation Math
{
data = data * 2;
data_out = data - 1;
data = data - 1;
data_out = scaleCube(data, 0, 64, 64);
softmax_label_out = softmax_label;
}
}
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