diff options
Diffstat (limited to 'config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java')
| -rw-r--r-- | config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java | 40 |
1 files changed, 20 insertions, 20 deletions
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java index 4693ac5cf4d..1e376824b7b 100644 --- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java +++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java @@ -42,7 +42,7 @@ import static org.junit.Assert.*; public class RankingExpressionWithTensorFlowTestCase { private final Path applicationDir = Path.fromString("src/test/integration/tensorflow/"); - private final String vespaExpression = "join(rename(reduce(join(Placeholder, rename(constant(\"layer_Variable\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"layer_Variable_1\"), d0, d1), f(a,b)(a + b))"; + private final String vespaExpression = "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(\"layer_Variable_read\"), f(a,b)(a * b)), sum, d2), constant(\"layer_Variable_1_read\"), f(a,b)(a + b))"; @After public void removeGeneratedConstantTensorFiles() { @@ -54,8 +54,8 @@ public class RankingExpressionWithTensorFlowTestCase { RankProfileSearchFixture search = fixtureWith("tensor(d0[2],d1[784])(0.0)", "tensorflow('mnist_softmax/saved')"); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test @@ -65,15 +65,15 @@ public class RankingExpressionWithTensorFlowTestCase { "constant mytensor { file: ignored\ntype: tensor(d0[7],d1[784]) }", null); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test public void testTensorFlowReferenceWithQueryFeature() { String queryProfile = "<query-profile id='default' type='root'/>"; String queryProfileType = "<query-profile-type id='root'>" + - " <field name='mytensor' type='tensor(d0[3],d1[784])'/>" + + " <field name='query(mytensor)' type='tensor(d0[3],d1[784])'/>" + "</query-profile-type>"; StoringApplicationPackage application = new StoringApplicationPackage(applicationDir, queryProfile, @@ -85,8 +85,8 @@ public class RankingExpressionWithTensorFlowTestCase { "Placeholder", application); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test @@ -99,15 +99,15 @@ public class RankingExpressionWithTensorFlowTestCase { "Placeholder", application); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test public void testTensorFlowReferenceWithFeatureCombination() { String queryProfile = "<query-profile id='default' type='root'/>"; String queryProfileType = "<query-profile-type id='root'>" + - " <field name='mytensor' type='tensor(d0[3],d1[784],d2[10])'/>" + + " <field name='query(mytensor)' type='tensor(d0[3],d1[784],d2[10])'/>" + "</query-profile-type>"; StoringApplicationPackage application = new StoringApplicationPackage(applicationDir, queryProfile, @@ -119,8 +119,8 @@ public class RankingExpressionWithTensorFlowTestCase { "Placeholder", application); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test @@ -128,8 +128,8 @@ public class RankingExpressionWithTensorFlowTestCase { RankProfileSearchFixture search = fixtureWith("tensor(d0[2],d1[784])(0.0)", "5 + sum(tensorflow('mnist_softmax/saved'))"); search.assertFirstPhaseExpression("5 + reduce(" + vespaExpression + ", sum)", "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); } @Test @@ -224,8 +224,8 @@ public class RankingExpressionWithTensorFlowTestCase { "tensorflow('mnist_softmax/saved')"); search.assertFirstPhaseExpression(vespaExpression, "my_profile"); - assertLargeConstant("layer_Variable_1", search, Optional.of(10L)); - assertLargeConstant("layer_Variable", search, Optional.of(7840L)); + assertLargeConstant("layer_Variable_1_read", search, Optional.of(10L)); + assertLargeConstant("layer_Variable_read", search, Optional.of(7840L)); // At this point the expression is stored - copy application to another location which do not have a models dir Path storedApplicationDirectory = applicationDir.getParentPath().append("copy"); @@ -243,8 +243,8 @@ public class RankingExpressionWithTensorFlowTestCase { searchFromStored.assertFirstPhaseExpression(vespaExpression, "my_profile"); // Verify that the constants exists, but don't verify the content as we are not // simulating file distribution in this test - assertLargeConstant("layer_Variable_1", searchFromStored, Optional.empty()); - assertLargeConstant("layer_Variable", searchFromStored, Optional.empty()); + assertLargeConstant("layer_Variable_1_read", searchFromStored, Optional.empty()); + assertLargeConstant("layer_Variable_read", searchFromStored, Optional.empty()); } finally { IOUtils.recursiveDeleteDir(storedApplicationDirectory.toFile()); @@ -253,7 +253,7 @@ public class RankingExpressionWithTensorFlowTestCase { @Test public void testImportingFromStoredExpressionsWithSmallConstants() throws IOException { - final String expression = "join(rename(reduce(join(join(join(rename(constant(\"dnn_hidden2_Const\"), d0, d1), join(rename(reduce(join(join(join(0.009999999776482582, join(rename(reduce(join(input, rename(constant(\"dnn_hidden1_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden1_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(a * b)), join(rename(reduce(join(input, rename(constant(\"dnn_hidden1_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden1_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(max(a,b))), rename(constant(\"dnn_hidden2_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden2_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(a * b)), join(rename(reduce(join(join(join(0.009999999776482582, join(rename(reduce(join(input, rename(constant(\"dnn_hidden1_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden1_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(a * b)), join(rename(reduce(join(input, rename(constant(\"dnn_hidden1_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden1_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(max(a,b))), rename(constant(\"dnn_hidden2_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_hidden2_bias\"), d0, d1), f(a,b)(a + b)), f(a,b)(max(a,b))), rename(constant(\"dnn_outputs_weights\"), (d0, d1), (d1, d3)), f(a,b)(a * b)), sum, d1), d3, d1), rename(constant(\"dnn_outputs_bias\"), d0, d1), f(a,b)(a + b))"; + final String expression = "join(reduce(join(join(join(constant(\"dnn_hidden2_Const\"), join(reduce(join(join(join(0.009999999776482582, join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(\"dnn_hidden1_weights_read\"), f(a,b)(a * b)), sum, d4), constant(\"dnn_hidden1_bias_read\"), f(a,b)(a + b)), f(a,b)(a * b)), join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(\"dnn_hidden1_weights_read\"), f(a,b)(a * b)), sum, d4), constant(\"dnn_hidden1_bias_read\"), f(a,b)(a + b)), f(a,b)(max(a,b))), constant(\"dnn_hidden2_weights_read\"), f(a,b)(a * b)), sum, d3), constant(\"dnn_hidden2_bias_read\"), f(a,b)(a + b)), f(a,b)(a * b)), join(reduce(join(join(join(0.009999999776482582, join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(\"dnn_hidden1_weights_read\"), f(a,b)(a * b)), sum, d4), constant(\"dnn_hidden1_bias_read\"), f(a,b)(a + b)), f(a,b)(a * b)), join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(\"dnn_hidden1_weights_read\"), f(a,b)(a * b)), sum, d4), constant(\"dnn_hidden1_bias_read\"), f(a,b)(a + b)), f(a,b)(max(a,b))), constant(\"dnn_hidden2_weights_read\"), f(a,b)(a * b)), sum, d3), constant(\"dnn_hidden2_bias_read\"), f(a,b)(a + b)), f(a,b)(max(a,b))), constant(\"dnn_outputs_weights_read\"), f(a,b)(a * b)), sum, d2), constant(\"dnn_outputs_bias_read\"), f(a,b)(a + b))"; StoringApplicationPackage application = new StoringApplicationPackage(applicationDir); RankProfileSearchFixture search = fixtureWith("tensor(d0[2],d1[784])(0.0)", "tensorflow('mnist/saved')", |