diff options
author | Lester Solbakken <lesters@oath.com> | 2020-04-21 15:53:28 +0200 |
---|---|---|
committer | Lester Solbakken <lesters@oath.com> | 2020-04-21 15:53:28 +0200 |
commit | 2849cd22587b6b869debe84c3562eb91ccb50d9b (patch) | |
tree | b5712058836c3d517206843d363a9b922ea95442 | |
parent | aad5c7184f37e1441c928efa77b434620742ff88 (diff) |
Fix order of arguments in joins after fix there
3 files changed, 6 insertions, 6 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 cba931e81f0..a64a964727c 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 @@ -319,9 +319,9 @@ public class RankingExpressionWithTensorFlowTestCase { @Test public void testFunctionGeneration() { final String name = "mnist_saved"; - final String expression = "join(join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))"; + final String expression = "join(join(reduce(join(join(join(reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))"; final String functionExpression1 = "join(reduce(join(reduce(rename(input, (d0, d1), (d0, d4)), sum, d0), constant(" + name + "_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(" + name + "_dnn_hidden1_bias_read), f(a,b)(a + b))"; - final String functionExpression2 = "join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))"; + final String functionExpression2 = "join(reduce(join(join(join(0.009999999776482582, imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))"; RankProfileSearchFixture search = fixtureWith("tensor(d0[1],d1[784])(0.0)", "tensorflow('mnist/saved')", @@ -349,9 +349,9 @@ public class RankingExpressionWithTensorFlowTestCase { " rank-profile my_profile_child inherits my_profile {\n" + " }"; - final String expression = "join(join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden2_add, reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))"; + final String expression = "join(join(reduce(join(join(join(reduce(constant(" + name + "_dnn_hidden2_Const), sum, d2), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden2_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_dnn_outputs_bias_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))"; final String functionExpression1 = "join(reduce(join(reduce(rename(input, (d0, d1), (d0, d4)), sum, d0), constant(" + name + "_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(" + name + "_dnn_hidden1_bias_read), f(a,b)(a + b))"; - final String functionExpression2 = "join(reduce(join(join(join(imported_ml_function_" + name + "_dnn_hidden1_add, 0.009999999776482582, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))"; + final String functionExpression2 = "join(reduce(join(join(join(0.009999999776482582, imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(a * b)), imported_ml_function_" + name + "_dnn_hidden1_add, f(a,b)(max(a,b))), constant(" + name + "_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(" + name + "_dnn_hidden2_bias_read), f(a,b)(a + b))"; RankProfileSearchFixture search = fixtureWithUncompiled(rankProfiles, new StoringApplicationPackage(applicationDir)); search.compileRankProfile("my_profile", applicationDir.append("models")); diff --git a/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java b/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java index ced7243adf5..ca84eb5eed7 100644 --- a/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java +++ b/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java @@ -67,7 +67,7 @@ public class MlModelsTest { "rankingExpression(Placeholder).rankingScript: attribute(argument)\n" + "rankingExpression(Placeholder).type: tensor<float>(d0[],d1[784])\n" + "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).rankingScript: join(reduce(join(rename(rankingExpression(input), (d0, d1), (d0, d4)), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))\n" + - "rankingExpression(mnist_tensorflow).rankingScript: join(reduce(join(map(join(reduce(join(join(join(rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), 0.009999999776482582, f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.0507009873554805 * if (a >= 0, a, 1.6732632423543772 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))\n" + + "rankingExpression(mnist_tensorflow).rankingScript: join(reduce(join(map(join(reduce(join(join(join(0.009999999776482582, rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.0507009873554805 * if (a >= 0, a, 1.6732632423543772 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))\n" + "rankingExpression(mnist_softmax_tensorflow).rankingScript: join(reduce(join(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b))\n" + "rankingExpression(mnist_softmax_onnx).rankingScript: join(reduce(join(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b))\n" + "rankingExpression(my_xgboost).rankingScript: if (f29 < -0.1234567, if (!(f56 >= -0.242398), 1.71218, -1.70044), if (f109 < 0.8723473, -1.94071, 1.85965)) + if (!(f60 >= -0.482947), if (f29 < -4.2387498, 0.784718, -0.96853), -6.23624)\n" + diff --git a/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java b/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java index 2d3ddc33afb..36b11cee067 100644 --- a/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java +++ b/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java @@ -158,7 +158,7 @@ public class ModelEvaluationTest { private final String mnistProfile = "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).rankingScript: join(reduce(join(rename(input, (d0, d1), (d0, d4)), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))\n" + "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).type: tensor(d3[300])\n" + - "rankingExpression(serving_default.y).rankingScript: join(reduce(join(map(join(reduce(join(join(join(rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), 0.009999999776482582, f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.0507009873554805 * if (a >= 0, a, 1.6732632423543772 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))\n" + + "rankingExpression(serving_default.y).rankingScript: join(reduce(join(map(join(reduce(join(join(join(0.009999999776482582, rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.0507009873554805 * if (a >= 0, a, 1.6732632423543772 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))\n" + "rankingExpression(serving_default.y).input.type: tensor(d0[],d1[784])\n" + "rankingExpression(serving_default.y).type: tensor(d0[],d1[10])\n"; |