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stress_asignment
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Added multiple results and created working grid settings and scripts

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master
lkrsnik 7 years ago
parent e79ae5c205
commit 7180550b0d
4 changed files with 65 additions and 42 deletions
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72
.idea/workspace.xml
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@ -2,11 +2,14 @@
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@ -81,6 +82,16 @@
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@ -150,9 +161,6 @@
</component>
<component name="FindInProjectRecents">
<findStrings>
<find>orig_X</find>
<find>vowels</find>
<find>_create_syllable_letters_translator</find>
<find>_get_unresonant_silent_consonants</find>
<find>el[0]</find>
<find>max_num_vowels</find>
@ -170,7 +178,6 @@
<find>predict</find>
<find>_reverse_inputs</find>
<find>_letter_generator</find>
<find>_accent_classification</find>
<find>_create_feature_dictionary</find>
<find>generate_data</find>
<find>Data</find>
@ -180,6 +187,10 @@
<find>../../../data/</find>
<find>self.x_other_features_train</find>
<find>_create_x_features</find>
<find>force</find>
<find>test_and_validation_size</find>
<find>_accent_classification</find>
<find>self.y_train</find>
</findStrings>
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@ -199,13 +210,14 @@
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@ -224,7 +236,6 @@
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<subPane>
<PATH>
@ -239,6 +250,7 @@
</PATH>
</subPane>
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@ -538,16 +550,6 @@
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1
notes
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@ -0,0 +1 @@
256(0.3)-512(0.3)-512(0.3):115(3)-46(3) - [LETTERS ACCENT TYPE] One layer less

28
workbench.py
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@ -27,7 +27,11 @@ from prepare_data import *
# save_inputs('../../internal_representations/inputs/shuffeled_matrix_validate_inputs_other_features_output_11.h5', X_validate, y_validate, other_features = X_other_features_validate)
# X_train, X_other_features_train, y_train = load_inputs('cnn/internal_representations/inputs/shuffeled_matrix_train_inputs_other_features_output_11.h5', other_features=True)
# X_validate, X_other_features_validate, y_validate = load_inputs('cnn/internal_representations/inputs/shuffeled_matrix_validate_inputs_other_features_output_11.h5', other_features=True)
data = Data('l', save_generated_data=False, number_of_syllables=True)
# letters
# data = Data('l', save_generated_data=False, number_of_syllables=True)
# syllabled letters
data = Data('l', save_generated_data=False, accent_classification=True)
data.generate_data('letters_word_accetuation_train',
'letters_word_accetuation_test',
'letters_word_accetuation_validate', content_name='SlovarIJS_BESEDE_utf8.lex',
@ -36,7 +40,7 @@ data.generate_data('letters_word_accetuation_train',
num_examples = len(data.x_train) # training set size
nn_output_dim = 10
nn_output_dim = 13
nn_hdim = 516
batch_size = 16
# actual_epoch = 1
@ -46,13 +50,23 @@ num_fake_epoch = 20
# letters
conv_input_shape=(23, 36)
othr_input = (141, )
# syllabled letters
# conv_input_shape=(10, 5168)
# othr_input = (140, )
othr_input = (150, )
conv_input = Input(shape=conv_input_shape, name='conv_input')
# letters
x_conv = Conv1D(115, (3), padding='same', activation='relu')(conv_input)
x_conv = Conv1D(46, (3), padding='same', activation='relu')(x_conv)
# syllabled letters
# x_conv = Conv1D(200, (2), padding='same', activation='relu')(conv_input)
x_conv = MaxPooling1D(pool_size=2)(x_conv)
x_conv = Flatten()(x_conv)
@ -62,10 +76,10 @@ x = concatenate([x_conv, othr_input])
# x = Dense(1024, input_dim=(516 + 256), activation='relu')(x)
x = Dense(256, activation='relu')(x)
x = Dropout(0.3)(x)
x = Dense(256, activation='relu')(x)
x = Dense(512, activation='relu')(x)
x = Dropout(0.3)(x)
x = Dense(512, activation='relu')(x)
x = Dropout(0.3)(x)
x = Dense(256, activation='relu')(x)
x = Dropout(0.2)(x)
x = Dense(nn_output_dim, activation='sigmoid')(x)

6
workbench.xrsl
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@ -2,13 +2,13 @@
(jobName="accetuation_nn")
(executable="workbench.sh")
(inputfiles=
("workbench.py" "")("prepare_data.py" "")("content_shuffle_vector.h5" "cnn/internal_representations/inputs/content_shuffle_vector.h5")("shuffle_vector_test.h5" "cnn/internal_representations/inputs/shuffle_vector_test.h5")("shuffle_vector_train.h5" "cnn/internal_representations/inputs/shuffle_vector_train.h5")("shuffle_vector_validate.h5" "cnn/internal_representations/inputs/shuffle_vector_validate.h5")("SlovarIJS_BESEDE_utf8.lex" "data/SlovarIJS_BESEDE_utf8.lex")("40_epoch.h5" "")("40_epoch_history.pkl" "")
("workbench.py" "")("prepare_data.py" "")("content_shuffle_vector.h5" "cnn/internal_representations/inputs/content_shuffle_vector.h5")("shuffle_vector_test.h5" "cnn/internal_representations/inputs/shuffle_vector_test.h5")("shuffle_vector_train.h5" "cnn/internal_representations/inputs/shuffle_vector_train.h5")("shuffle_vector_validate.h5" "cnn/internal_representations/inputs/shuffle_vector_validate.h5")("SlovarIJS_BESEDE_utf8.lex" "data/SlovarIJS_BESEDE_utf8.lex")("40_epoch.h5" "")("40_epoch_history.pkl" "")("notes" "")
)
(outputfiles=("40_epoch.h5" "")("workbench.py" "")("workbench.sh" "")("40_epoch_history.pkl" "")
(outputfiles=("40_epoch.h5" "")("workbench.py" "")("workbench.sh" "")("40_epoch_history.pkl" "")("notes" "")
)
(stdout="out.txt")
(stderr="err.txt")
(gmlog="gmlog")
(runtimeenvironment="APPS/BASE/THEANO-GPU-0.9")
(gridTime=2000)
(gridTime=750)
(memory=12000)

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