| /* ----------------------------------------------------------------------- *//** |
| * |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyright ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| * |
| *//* ----------------------------------------------------------------------- */ |
| |
| drop table if exists cifar_10_sample; |
| create table cifar_10_sample( |
| id INTEGER, |
| x REAL[], |
| y SMALLINT, |
| imgpath TEXT |
| ); |
| copy cifar_10_sample from stdin delimiter '|'; |
| 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0 | '0/img0.jpg' |
| 2|{{{126,118,110},{122,115,108},{126,119,111},{127,119,109},{130,122,111},{130,122,111},{132,124,113},{133,125,114},{130,122,111},{132,124,113},{134,126,115},{131,123,112},{131,123,112},{134,126,115},{133,125,114},{136,128,117},{137,129,118},{137,129,118},{136,128,117},{131,123,112},{130,122,111},{132,124,113},{132,124,113},{132,124,113},{129,122,110},{127,121,109},{127,121,109},{125,119,107},{124,118,106},{124,118,106},{120,114,102},{117,111,99}},{{122,115,107},{119,112,104},{121,114,106},{124,116,107},{129,121,110},{130,122,111},{130,122,111},{130,122,111},{128,120,109},{131,123,112},{134,126,115},{132,124,113},{132,124,113},{134,126,115},{136,128,117},{139,131,120},{141,133,122},{138,130,119},{135,127,116},{130,122,111},{131,123,112},{132,124,113},{133,125,114},{133,125,114},{131,124,113},{129,123,111},{130,124,112},{129,123,111},{127,121,109},{124,118,106},{122,116,104},{117,111,99}},{{122,115,107},{121,114,106},{121,114,106},{125,118,108},{128,120,109},{129,121,110},{131,123,112},{130,122,111},{128,120,109},{131,123,112},{133,125,114},{134,126,115},{136,128,117},{137,129,118},{138,130,119},{139,131,120},{139,131,120},{139,131,120},{139,131,120},{139,131,120},{139,131,120},{137,129,118},{137,129,118},{138,130,119},{136,129,118},{135,129,117},{133,127,115},{130,124,112},{129,123,111},{126,120,108},{123,117,105},{121,115,103}},{{123,116,108},{123,116,108},{125,118,110},{127,119,109},{127,119,108},{129,121,110},{132,125,113},{131,123,112},{130,122,111},{134,127,115},{134,126,115},{135,127,116},{133,125,114},{134,126,116},{136,128,118},{140,132,121},{142,134,123},{141,133,122},{141,132,122},{142,133,123},{141,132,122},{141,133,122},{140,131,120},{137,128,117},{136,128,117},{136,130,118},{132,127,115},{128,122,110},{127,121,109},{127,121,109},{125,119,107},{123,117,105}},{{124,119,110},{125,119,111},{128,122,113},{129,123,113},{132,123,113},{136,123,115},{137,125,116},{134,125,116},{135,125,116},{136,125,116},{134,125,115},{133,126,116},{136,124,115},{135,127,113},{137,131,115},{140,130,118},{141,130,120},{139,131,120},{137,132,118},{135,133,117},{134,130,117},{136,130,118},{136,130,119},{134,129,117},{132,127,115},{132,126,114},{131,125,113},{131,124,112},{129,122,110},{127,121,109},{128,122,110},{128,122,110}},{{124,121,112},{124,121,112},{128,124,115},{129,125,116},{136,124,118},{145,124,121},{143,126,121},{136,128,120},{136,126,119},{140,123,118},{136,126,118},{133,129,121},{146,130,130},{136,130,115},{135,133,112},{138,131,117},{138,130,119},{139,132,120},{137,132,117},{133,132,113},{132,131,115},{135,130,118},{136,129,118},{135,130,118},{131,127,115},{132,124,113},{132,124,113},{131,123,112},{129,122,110},{128,122,110},{127,121,109},{127,121,109}},{{123,120,111},{122,119,110},{124,121,112},{126,122,113},{132,122,115},{138,125,119},{135,128,120},{128,130,119},{130,129,119},{134,124,117},{127,118,110},{129,126,120},{142,135,139},{154,139,136},{141,130,123},{130,133,125},{131,135,121},{138,135,122},{143,130,122},{145,124,120},{142,126,119},{140,128,118},{141,128,119},{142,126,118},{139,125,116},{134,126,115},{134,126,115},{133,125,114},{131,123,112},{129,122,110},{126,120,108},{124,118,106}},{{121,118,109},{121,118,109},{122,119,110},{123,118,109},{127,121,113},{130,126,117},{131,131,121},{134,136,125},{130,131,121},{133,130,121},{133,127,119},{136,131,123},{115,104,98},{128,91,93},{151,118,117},{139,136,125},{135,137,122},{140,136,124},{139,132,124},{141,131,126},{140,128,121},{136,129,117},{134,131,118},{135,128,117},{137,126,116},{135,127,116},{135,127,116},{133,125,114},{131,123,112},{128,122,110},{127,121,109},{125,119,107}},{{124,121,112},{124,121,112},{126,123,114},{127,122,113},{128,124,115},{132,130,121},{138,131,123},{162,149,143},{156,144,138},{137,133,124},{141,136,128},{143,136,125},{137,120,105},{119,80,78},{144,108,108},{147,136,125},{142,133,123},{146,133,124},{149,134,123},{148,132,120},{151,130,121},{140,129,119},{127,134,118},{126,133,117},{131,128,116},{135,127,116},{134,126,115},{132,124,113},{130,122,111},{128,122,110},{128,122,110},{126,120,108}},{{126,123,114},{126,123,114},{128,125,116},{130,127,118},{129,129,119},{135,131,122},{143,122,119},{142,106,108},{163,131,132},{147,134,128},{140,136,127},{139,132,124},{141,134,128},{120,115,122},{134,131,142},{151,151,155},{143,139,133},{154,128,121},{152,90,85},{155,61,56},{158,77,80},{155,115,115},{141,131,121},{133,131,118},{135,128,117},{135,127,116},{134,126,115},{132,124,113},{130,123,112},{129,123,111},{126,120,108},{126,120,108}},{{126,121,112},{126,121,113},{130,125,116},{131,126,116},{131,128,117},{134,127,119},{141,123,120},{110,64,71},{121,57,65},{151,117,110},{143,135,122},{132,134,122},{136,138,130},{102,114,121},{80,97,121},{90,107,138},{130,146,164},{149,133,146},{142,71,84},{165,54,64},{151,34,43},{150,63,65},{159,116,110},{142,131,119},{134,130,118},{135,127,116},{136,128,117},{134,126,115},{131,123,112},{130,124,112},{126,120,108},{124,118,106}},{{129,122,114},{128,121,114},{131,124,116},{133,127,115},{135,129,117},{136,129,120},{138,132,127},{150,123,127},{144,96,100},{152,120,109},{144,129,114},{131,128,119},{171,174,177},{160,168,180},{132,146,167},{97,117,145},{106,131,159},{136,135,162},{150,112,134},{186,129,141},{202,129,128},{149,78,70},{159,118,107},{146,134,121},{135,132,119},{136,128,117},{136,128,117},{136,128,117},{134,126,115},{134,128,116},{131,125,113},{126,120,108}},{{133,126,118},{132,125,117},{134,127,119},{136,130,118},{136,130,118},{138,132,123},{139,131,126},{113,113,117},{126,135,146},{168,171,175},{149,142,143},{119,111,122},{148,157,188},{194,207,232},{166,178,191},{159,172,180},{180,194,207},{191,192,207},{170,156,167},{189,168,173},{211,196,191},{149,139,127},{147,135,123},{149,136,123},{145,134,122},{140,132,121},{138,130,119},{136,128,117},{132,125,113},{132,126,114},{131,125,113},{128,122,110}},{{134,127,119},{135,128,120},{136,128,121},{136,130,118},{137,131,119},{137,131,122},{142,134,128},{90,93,108},{33,52,92},{89,107,144},{145,161,193},{152,169,196},{116,138,164},{133,151,175},{167,177,200},{189,194,216},{207,211,225},{210,216,225},{204,212,217},{203,212,214},{173,170,171},{143,132,131},{146,137,129},{145,137,122},{144,136,120},{141,133,122},{139,131,120},{138,130,119},{133,125,114},{130,124,112},{128,122,110},{126,120,108}},{{131,124,116},{134,128,120},{135,128,120},{136,130,118},{139,133,121},{138,131,122},{109,101,95},{121,117,130},{103,109,150},{52,67,114},{60,87,130},{108,140,172},{150,174,198},{146,165,191},{128,141,172},{140,148,181},{158,164,187},{169,181,196},{183,201,208},{183,195,199},{154,140,144},{156,133,132},{150,137,128},{142,138,121},{141,138,121},{141,133,122},{137,129,118},{136,128,117},{135,127,116},{133,127,115},{129,123,111},{128,122,110}},{{132,124,116},{130,121,114},{135,126,120},{140,131,122},{140,134,122},{138,135,124},{125,119,115},{157,159,162},{162,174,189},{140,149,179},{140,154,186},{131,146,177},{99,114,155},{137,152,188},{164,182,209},{164,182,203},{156,170,195},{146,162,184},{147,161,179},{168,173,191},{159,159,158},{147,144,128},{146,139,124},{146,139,123},{143,135,123},{142,134,124},{136,128,117},{133,125,114},{134,127,116},{127,121,109},{129,123,111},{129,123,111}},{{141,129,119},{136,122,116},{135,124,120},{141,129,128},{135,130,122},{148,152,145},{185,191,204},{141,169,193},{119,147,170},{181,181,202},{192,200,212},{204,203,220},{167,172,199},{132,143,172},{119,136,168},{137,160,193},{169,188,213},{185,192,204},{175,177,202},{92,107,179},{97,120,166},{134,143,141},{149,140,126},{147,137,121},{140,132,126},{140,131,128},{138,131,116},{137,129,115},{137,128,119},{133,125,115},{131,124,112},{129,122,111}},{{139,129,117},{132,130,117},{127,134,120},{131,137,124},{157,154,155},{180,178,199},{118,136,175},{89,115,149},{153,146,163},{192,179,185},{182,207,197},{193,217,214},{202,206,219},{193,200,218},{171,186,209},{129,149,182},{96,125,171},{137,161,179},{169,183,203},{53,62,153},{34,44,157},{102,112,172},{124,127,141},{145,138,133},{143,133,125},{140,133,117},{139,132,117},{137,129,117},{136,128,116},{137,129,118},{135,127,116},{130,122,111}},{{134,128,114},{137,129,112},{143,130,112},{145,90,76},{165,123,127},{107,118,147},{94,115,158},{162,137,167},{152,76,85},{165,113,119},{207,202,202},{200,212,217},{213,213,226},{223,226,236},{220,229,236},{210,224,231},{150,175,200},{71,107,153},{104,138,195},{107,119,184},{50,51,159},{70,83,198},{60,77,162},{114,111,149},{140,126,118},{136,130,103},{133,125,112},{136,127,117},{134,126,110},{135,127,115},{134,126,115},{129,121,110}},{{137,127,114},{154,108,97},{159,66,64},{168,25,19},{151,29,30},{117,61,76},{168,148,162},{201,168,175},{180,136,140},{192,168,177},{222,207,225},{228,224,240},{219,216,222},{187,186,189},{189,190,189},{214,215,210},{233,229,229},{181,198,221},{77,114,170},{93,124,184},{133,149,200},{68,82,181},{33,46,185},{86,86,176},{134,125,146},{137,128,123},{136,128,117},{135,128,113},{134,126,112},{132,124,113},{131,123,112},{129,121,110}},{{139,122,111},{133,65,55},{151,14,14},{167,15,13},{174,17,17},{171,20,23},{155,53,47},{191,142,135},{216,219,216},{213,237,237},{214,218,224},{166,172,170},{95,92,90},{46,40,39},{51,45,44},{82,74,75},{125,112,115},{164,166,160},{147,167,173},{55,80,130},{118,138,172},{139,150,196},{64,67,163},{104,112,203},{113,111,187},{121,103,148},{140,131,120},{136,129,106},{133,124,120},{130,122,113},{129,121,110},{127,119,108}},{{140,121,112},{133,85,73},{137,45,37},{147,29,31},{162,20,19},{180,18,10},{173,19,14},{161,56,61},{181,157,159},{148,152,149},{90,79,74},{44,39,25},{55,47,39},{69,59,54},{57,45,43},{43,31,31},{33,28,24},{34,29,26},{54,48,52},{58,57,67},{73,79,100},{142,144,158},{137,137,155},{113,126,182},{84,89,183},{102,86,158},{130,123,125},{135,128,110},{135,123,122},{131,121,111},{128,120,107},{126,118,106}},{{135,124,117},{106,91,83},{65,46,39},{114,58,55},{154,47,45},{162,31,28},{145,27,26},{99,25,26},{61,33,30},{39,31,22},{52,47,36},{97,89,77},{135,124,111},{143,132,119},{137,125,113},{126,114,102},{110,99,92},{93,81,78},{74,60,59},{63,51,47},{80,71,69},{1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1 | '0/img2.jpg' |
| \. |
| |
| DROP TABLE IF EXISTS cifar_10_sample_batched; |
| DROP TABLE IF EXISTS cifar_10_sample_batched_summary; |
| SELECT minibatch_preprocessor_dl('cifar_10_sample','cifar_10_sample_batched','y','x', 2, 255); |
| |
| DROP TABLE IF EXISTS model_arch; |
| SELECT load_keras_model('model_arch', |
| $${ |
| "class_name": "Sequential", |
| "keras_version": "2.1.6", |
| "config": [{ |
| "class_name": "Conv2D", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_avg"}}, |
| "name": "conv2d_1", |
| "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, |
| "dtype": "float32", "activation": "relu", "trainable": true, |
| "data_format": "channels_last", "filters": 32, "padding": "valid", |
| "strides": [1, 1], "dilation_rate": [1, 1], "kernel_regularizer": null, |
| "bias_initializer": {"class_name": "Zeros", "config": {}}, |
| "batch_input_shape": [null, 32, 32, 3], "use_bias": true, |
| "activity_regularizer": null, "kernel_size": [3, 3]}}, |
| {"class_name": "MaxPooling2D", "config": {"name": "max_pooling2d_1", "trainable": true, "data_format": "channels_last", "pool_size": [2, 2], "padding": "valid", "strides": [2, 2]}}, |
| {"class_name": "Dropout", "config": {"rate": 0.25, "noise_shape": null, "trainable": true, "seed": null, "name": "dropout_1"}}, |
| {"class_name": "Flatten", "config": {"trainable": true, "name": "flatten_1", "data_format": "channels_last"}}, |
| {"class_name": "Dense", "config": {"kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "scale": 1.0, "seed": null, "mode": "fan_avg"}}, "name": "dense_1", "kernel_constraint": null, "bias_regularizer": null, "bias_constraint": null, "activation": "softmax", "trainable": true, "kernel_regularizer": null, "bias_initializer": |
| {"class_name": "Zeros", "config": {}}, "units": 2, "use_bias": true, "activity_regularizer": null} |
| }], "backend": "tensorflow"}$$); |
| ALTER TABLE model_arch RENAME model_id TO id; |
| |
| -- Please do not break up the compile_params string |
| -- It might break the assertion |
| |
| DROP TABLE IF EXISTS keras_saved_out, keras_saved_out_summary; |
| SELECT madlib_keras_fit( |
| 'cifar_10_sample_batched', |
| 'keras_saved_out', |
| 'dependent_var', |
| 'independent_var', |
| 'model_arch', |
| 1, |
| $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text, |
| $$ batch_size=2, epochs=1, verbose=0 $$::text, |
| 3, |
| FALSE, |
| 'cifar_10_sample_batched'); |
| |
| SELECT assert( |
| model_arch_table = 'model_arch' AND |
| model_arch_id = 1 AND |
| model_type = 'madlib_keras' AND |
| start_training_time < now() AND |
| end_training_time > start_training_time AND |
| source_table = 'cifar_10_sample_batched' AND |
| validation_table = 'cifar_10_sample_batched' AND |
| model = 'keras_saved_out' AND |
| dependent_varname = 'dependent_var' AND |
| dependent_vartype = 'smallint' AND |
| independent_varname = 'independent_var' AND |
| normalizing_const = 255.0 AND |
| name is NULL AND |
| description is NULL AND |
| model_size > 0 AND |
| madlib_version is NOT NULL AND |
| compile_params = $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text AND |
| fit_params = $$ batch_size=2, epochs=1, verbose=0 $$::text AND |
| num_iterations = 3 AND |
| num_classes = 2 AND |
| class_values = '{0,1}' AND |
| accuracy is not NULL AND |
| loss is not NULL AND |
| array_upper(accuracy_iter, 1) = 3 AND |
| array_upper(loss_iter, 1) = 3 AND |
| array_upper(time_iter, 1) = 3 AND |
| accuracy_validation is not NULL AND |
| loss_validation is not NULL AND |
| array_upper(accuracy_iter_validation, 1) = 3 AND |
| array_upper(loss_iter_validation, 1) = 3 , |
| 'Keras model output Summary Validation failed. Actual:' || __to_char(summary)) |
| FROM (SELECT * FROM keras_saved_out_summary) summary; |
| |
| SELECT assert(accuracy_validation > 0.9999, |
| 'Validation accuracy after 3 iterations of training is only ' || __to_char(100*accuracy) || '%, should have reached 100%') |
| FROM keras_saved_out_summary; |
| |
| SELECT assert(model_data IS NOT NULL , 'Keras model output validation failed') FROM (SELECT * FROM keras_saved_out) k; |
| |
| |
| -- Test for |
| -- Non null name and description columns |
| -- Null validation table |
| DROP TABLE IF EXISTS keras_out, keras_out_summary; |
| SELECT madlib_keras_fit( |
| 'cifar_10_sample_batched', |
| 'keras_out', |
| 'dependent_var', |
| 'independent_var', |
| 'model_arch', |
| 1, |
| $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text, |
| $$ batch_size=2, epochs=1, verbose=0 $$::text, |
| 1, |
| FALSE, |
| NULL, |
| 'model name', 'model desc'); |
| SELECT assert( |
| model_arch_table = 'model_arch' AND |
| model_arch_id = 1 AND |
| model_type = 'madlib_keras' AND |
| start_training_time < now() AND |
| end_training_time > start_training_time AND |
| source_table = 'cifar_10_sample_batched' AND |
| validation_table = 'cifar_10_sample_batched' AND |
| model = 'keras_out' AND |
| dependent_varname = 'dependent_var' AND |
| independent_varname = 'independent_var' AND |
| name = 'model name' AND |
| description = 'model desc' AND |
| model_size > 0 AND |
| madlib_version is NOT NULL AND |
| compile_params = $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text AND |
| fit_params = $$ batch_size=2, epochs=1, verbose=0 $$::text AND |
| num_iterations = 1 AND |
| num_classes = 2 AND |
| class_values = '{0,1}' AND |
| accuracy is not NULL AND |
| loss is not NULL AND |
| array_upper(accuracy_iter, 1) = 1 AND |
| array_upper(loss_iter, 1) = 1 AND |
| array_upper(time_iter, 1) = 1 AND |
| accuracy_validation is NULL AND |
| loss_validation is NULL AND |
| array_upper(accuracy_iter_validation,1) = 0 AND |
| array_upper(loss_iter_validation,1) = 0 , |
| 'Keras model output Summary Validation failed. Actual:' || __to_char(summary)) |
| FROM (SELECT * FROM keras_out_summary) summary; |
| |
| SELECT assert(model_data IS NOT NULL , 'Keras model output validation failed') FROM (SELECT * FROM keras_out) k; |
| |
| DROP TABLE IF EXISTS cifar10_predict; |
| SELECT madlib_keras_predict( |
| 'keras_saved_out', |
| 'cifar_10_sample', |
| 'id', |
| 'model_arch', |
| 1, |
| 'x', |
| $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text, |
| 'cifar10_predict'); |
| |
| -- Validate that prediction output table exists and has correct schema |
| SELECT assert(UPPER(atttypid::regtype::TEXT) = 'INTEGER', 'id column should be INTEGER type') |
| FROM pg_attribute WHERE attrelid = 'cifar10_predict'::regclass |
| AND attname = 'id'; |
| |
| SELECT assert(UPPER(atttypid::regtype::TEXT) = |
| 'DOUBLE PRECISION', 'prediction column should be DOUBLE PRECISION type') |
| FROM pg_attribute WHERE attrelid = 'cifar10_predict'::regclass |
| AND attname = 'prediction'; |
| |
| -- Validate correct number of rows returned. |
| SELECT assert(COUNT(*)=2, 'Output table of madlib_keras_predict should have two rows') FROM cifar10_predict; |
| |
| -- First test that all values are in set of class values; if this breaks, it's definitely a problem. |
| SELECT assert(prediction in (0,1),'Predicted value not in set of defined class values for model') FROM cifar10_predict; |
| |
| -- Then test that each of the two images is correctly predicted. If this breaks, it's likely a different problem. |
| SELECT assert(prediction=0,'Incorrect prediction for first image. Predicted: ' || __to_char(prediction) || ', Expected: 0') FROM cifar10_predict WHERE id=1; |
| SELECT assert(prediction=1,'Incorrect prediction for second image. Predicted: ' || __to_char(prediction) || ', Expected: 1') FROM cifar10_predict WHERE id=2; |
| |
| select assert(trap_error($TRAP$madlib_keras_predict( |
| 'keras_saved_out', |
| 'cifar_10_sample_batched', |
| 'id', |
| 'model_arch', |
| 1, |
| 'x', |
| $$ optimizer=SGD(lr=0.01, decay=1e-6, nesterov=True), loss='categorical_crossentropy', metrics=['accuracy']$$::text, |
| 'cifar10_predict');$TRAP$) = 1, |
| 'Passing batched image table to predict should error out.'); |
