Added num of letters to x_other_features
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parent
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commit
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.gitignore
vendored
2
.gitignore
vendored
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@ -91,3 +91,5 @@ ENV/
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# Custom
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data/
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cnn/internal_representations/inputs/
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joblist.xml
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new_sloleks.xml
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@ -3,9 +3,11 @@
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<component name="ChangeListManager">
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<list default="true" id="8a8ba9af-e1a4-433a-9968-475192610776" name="Default" comment="">
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/.idea/workspace.xml" afterPath="$PROJECT_DIR$/.idea/workspace.xml" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/accent_classification/letters/cnn.ipynb" afterPath="$PROJECT_DIR$/cnn/accent_classification/letters/cnn.ipynb" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/cnn.ipynb" afterPath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/cnn.ipynb" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/word_accetuation/syllables/cnn.ipynb" afterPath="$PROJECT_DIR$/cnn/word_accetuation/syllables/cnn.ipynb" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/results_presentation.ipynb" afterPath="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/results_presentation.ipynb" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/prepare_data.py" afterPath="$PROJECT_DIR$/prepare_data.py" />
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/workbench.py" afterPath="$PROJECT_DIR$/workbench.py" />
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</list>
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<option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
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<option name="TRACKING_ENABLED" value="true" />
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@ -32,28 +34,25 @@
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</provider>
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</entry>
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</file>
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<file leaf-file-name="prepare_data.py" pinned="false" current-in-tab="true">
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<file leaf-file-name="prepare_data.py" pinned="false" current-in-tab="false">
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</folding>
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</state>
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</provider>
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@ -69,13 +68,13 @@
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</provider>
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</entry>
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</file>
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<file leaf-file-name="workbench.py" pinned="false" current-in-tab="false">
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<file leaf-file-name="workbench.py" pinned="false" current-in-tab="true">
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<entry file="file://$PROJECT_DIR$/workbench.py">
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</folding>
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</state>
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</provider>
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@ -150,21 +149,6 @@
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</component>
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<component name="FindInProjectRecents">
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<findStrings>
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<find>count_vowels</find>
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<find>shuffle_full_vowel_inputs</find>
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<find>generate_presentable_y</find>
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<find>is_accetuated_vowel</find>
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<find>is_vowel</find>
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<find>load_shuffle_vector</find>
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<find>create_and_save_shuffle_vector</find>
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<find>load_extended_inputs</find>
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<find>create_and_save_inputs</find>
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<find>shuffle_inputs</find>
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<find>complete_feature_dict</find>
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<find>create_syllable_letters_translator</find>
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<find>syllable_letters_translator</find>
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<find>get_max_syllable</find>
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<find>check_feature_letter_usage</find>
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<find>orig_X</find>
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<find>vowels</find>
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<find>_create_syllable_letters_translator</find>
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@ -180,6 +164,21 @@
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<find>size</find>
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<find>decode_x</find>
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<find>self._input_type ==</find>
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<find>../</find>
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<find>math</find>
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<find>predict</find>
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<find>_reverse_inputs</find>
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<find>_letter_generator</find>
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<find>_accent_classification</find>
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<find>_create_feature_dictionary</find>
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<find>generate_data</find>
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<find>Data</find>
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<find>shuffle_vector</find>
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<find>shuffle_vector_path</find>
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<find>fit_generator</find>
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<find>../../../data/</find>
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<find>self.x_other_features_train</find>
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<find>_create_x_features</find>
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</findStrings>
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</component>
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<component name="Git.Settings">
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@ -196,10 +195,10 @@
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<option value="$PROJECT_DIR$/theano_tutorial/logistic_regression_loop.py" />
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<option value="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/cnn_test_on_other_attributes.ipynb" />
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<option value="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/character_based_ffnn_keras.py" />
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<option value="$PROJECT_DIR$/workbench.py" />
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<option value="$PROJECT_DIR$/cnn/word_accetuation/cnn_dictionary/character_based_ffnn_keras.ipynb" />
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<option value="$PROJECT_DIR$/tex_hyphenation.py" />
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<option value="$PROJECT_DIR$/prepare_data.py" />
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<option value="$PROJECT_DIR$/workbench.py" />
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</list>
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</option>
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</component>
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@ -224,6 +223,8 @@
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<foldersAlwaysOnTop value="true" />
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</navigator>
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<panes>
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<pane id="Scope" />
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<pane id="Scratches" />
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<pane id="ProjectPane">
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<subPane>
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<PATH>
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@ -238,8 +239,6 @@
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</PATH>
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</subPane>
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</pane>
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<pane id="Scope" />
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<pane id="Scratches" />
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</panes>
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</component>
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<component name="PropertiesComponent">
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@ -830,31 +829,6 @@
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</state>
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</provider>
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</entry>
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<entry file="file://$PROJECT_DIR$/prepare_data.py">
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<provider selected="true" editor-type-id="text-editor">
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<state relative-caret-position="244">
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<folding>
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<element signature="e#13855#14684#0" expanded="false" />
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<element signature="e#16969#17882#0" expanded="false" />
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<element signature="e#18312#18508#0" expanded="false" />
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<element signature="e#18569#18760#0" expanded="false" />
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<element signature="e#18827#19474#0" expanded="false" />
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<element signature="e#19573#21871#0" expanded="false" />
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<element signature="e#22137#22836#0" expanded="false" />
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<element signature="e#29631#29772#0" expanded="false" />
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<element signature="e#29922#32067#0" expanded="false" />
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</folding>
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</state>
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</provider>
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</entry>
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<entry file="file://$PROJECT_DIR$/tex_hyphenation.py">
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<provider selected="true" editor-type-id="text-editor">
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<state relative-caret-position="1206">
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@ -863,16 +837,6 @@
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</state>
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</provider>
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</entry>
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<entry file="file://$PROJECT_DIR$/workbench.py">
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<provider selected="true" editor-type-id="text-editor">
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</entry>
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@ -921,5 +885,37 @@
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</state>
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</provider>
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</entry>
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<entry file="file://$PROJECT_DIR$/prepare_data.py">
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</component>
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</project>
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@ -7,11 +7,12 @@ import h5py
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import math
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import keras.backend as K
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import os.path
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import codecs
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class Data:
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def __init__(self, input_type, allow_shuffle_vector_generation=False, save_generated_data=True, shuffle_all_inputs=True,
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additional_letter_attributes=True, reverse_inputs=True, accent_classification=False):
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additional_letter_attributes=True, reverse_inputs=True, accent_classification=False, number_of_syllables=False):
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self._input_type = input_type
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self._save_generated_data = save_generated_data
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self._allow_shuffle_vector_generation = allow_shuffle_vector_generation
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@ -19,6 +20,7 @@ class Data:
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self._additional_letter_attributes = additional_letter_attributes
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self._reverse_inputs = reverse_inputs
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self._accent_classification = accent_classification
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self._number_of_syllables = number_of_syllables
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self.x_train = None
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self.x_other_features_train = None
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@ -88,7 +90,8 @@ class Data:
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# functions for creating X and y from content
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@staticmethod
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def _read_content(content_path):
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with open(content_path) as f:
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# with open(content_path) as f:
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with codecs.open(content_path, encoding='utf8') as f:
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content = f.readlines()
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return [x.split('\t') for x in content]
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@ -261,9 +264,9 @@ class Data:
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raise ValueError('No input_type provided. It could be \'l\', \'s\' or \'sl\'.')
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y = self._y_output(content, max_num_vowels, vowels, accentuated_vowels)
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print('CREATING OTHER FEATURES...')
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x_other_features = self._create_x_features(content, feature_dictionary)
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print('OTHER FEATURES CREATED!')
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# print('CREATING OTHER FEATURES...')
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x_other_features = self._create_x_features(content, feature_dictionary, vowels)
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# print('OTHER FEATURES CREATED!')
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if self._shuffle_all_inputs:
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print('SHUFFELING INPUTS...')
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@ -347,7 +350,7 @@ class Data:
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split = min(split_options, key=lambda x: x[1])
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return consonants[:split[0] + 1], consonants[split[0] + 1:]
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def _create_x_features(self, content, feature_dictionary):
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def _create_x_features(self, content, feature_dictionary, vowels):
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content = content
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x_other_features = []
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for el in content:
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@ -364,6 +367,14 @@ class Data:
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x_el_other_features.append(0)
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else:
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x_el_other_features.extend([0] * feature[0])
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if self._number_of_syllables:
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list_of_letters = list(el[0])
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num_of_vowels = 0
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for i in range(len(list_of_letters)):
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if self._is_vowel(list(el[0]), i, vowels):
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num_of_vowels += 1
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x_el_other_features.append(num_of_vowels)
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x_other_features.append(x_el_other_features)
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return np.array(x_other_features)
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@ -652,6 +663,60 @@ class Data:
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def _get_nonresonant_silent_consonants():
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return ['p', 't', 's', 'š', 'č', 'k', 'f', 'h', 'c']
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@staticmethod
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def _create_slovene_feature_dictionary():
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# old: http://nl.ijs.si/ME/Vault/V3/msd/html/
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# new: http://nl.ijs.si/ME/V4/msd/html/
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# changes: http://nl.ijs.si/jos/msd/html-en/msd.diffs.html
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return [[21,
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'P',
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['p', 's'],
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['n', 'p', 's'],
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['m', 'z', 's'],
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['e', 'd', 'm'],
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['i', 'r', 'd', 't', 'm', 'o'],
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['-', 'n', 'd']],
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[3, 'V', ['p', 'd']],
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[1, 'M'],
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[21,
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'K',
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['b'],
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['-', 'g', 'v', 'd'],
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['m', 'z', 's'],
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['e', 'd', 'm'],
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['i', 'r', 'd', 't', 'm', 'o'],
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['-', 'n', 'd']],
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[17,
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'S',
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['o'],
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['m', 'z', 's'],
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['e', 'd', 'm'],
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['i', 'r', 'd', 't', 'm', 'o'],
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['-', 'n', 'd']],
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[40,
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'Z',
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['o', 's', 'k', 'z', 'p', 'c', 'v', 'n', 'l'],
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['-', 'p', 'd', 't'],
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['-', 'm', 'z', 's'],
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['-', 'e', 'd', 'm'],
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['-', 'i', 'r', 'd', 't', 'm', 'o'],
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['-', 'e', 'd', 'm'],
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['-', 'm', 'z', 's'],
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['-', 'k', 'z']],
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[1, 'L'],
|
||||
[5, 'R', ['s'], ['n', 'r', 's']],
|
||||
[7, 'D', ['-', 'r', 'd', 't', 'm', 'o']],
|
||||
[24,
|
||||
'G',
|
||||
['g'],
|
||||
['-'],
|
||||
['n', 'm', 'd', 's', 'p', 'g'],
|
||||
['-', 'p', 'd', 't'],
|
||||
['-', 'e', 'm', 'd'],
|
||||
['-', 'm', 'z', 's'],
|
||||
['-', 'n', 'd']]
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def _create_feature_dictionary():
|
||||
# old: http://nl.ijs.si/ME/Vault/V3/msd/html/
|
||||
|
|
|
|||
1204
sloleks_accetuation.ipynb
Normal file
1204
sloleks_accetuation.ipynb
Normal file
File diff suppressed because one or more lines are too long
108
workbench.py
108
workbench.py
|
|
@ -1,26 +1,17 @@
|
|||
|
||||
# coding: utf-8
|
||||
|
||||
# In[1]:
|
||||
|
||||
|
||||
# -*- coding: utf-8 -*-
|
||||
from __future__ import unicode_literals
|
||||
# text in Western (Windows 1252)
|
||||
|
||||
import pickle
|
||||
import numpy as np
|
||||
# import StringIO
|
||||
import math
|
||||
from keras.models import Sequential
|
||||
from keras.layers import Dense, Dropout, Merge
|
||||
from keras import optimizers
|
||||
from keras.models import Model
|
||||
from keras.layers import Dense, Dropout, Input
|
||||
from keras.layers.merge import concatenate
|
||||
from keras import regularizers
|
||||
from keras.layers.convolutional import Conv1D
|
||||
from keras.layers.convolutional import MaxPooling1D
|
||||
from keras.constraints import maxnorm
|
||||
from keras.layers import Flatten
|
||||
from keras.optimizers import SGD
|
||||
from keras.models import load_model
|
||||
# from keras import backend as Input
|
||||
np.random.seed(7)
|
||||
|
||||
# get_ipython().magic('run ../../../prepare_data.py')
|
||||
|
|
@ -34,39 +25,68 @@ from prepare_data import *
|
|||
# X_train, X_other_features_train, y_train, X_validate, X_other_features_validate, y_validate = generate_full_matrix_inputs()
|
||||
# save_inputs('../../internal_representations/inputs/shuffeled_matrix_train_inputs_other_features_output_11.h5', X_train, y_train, other_features = X_other_features_train)
|
||||
# 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)
|
||||
# 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)
|
||||
data.generate_data('letters_word_accetuation_train',
|
||||
'letters_word_accetuation_test',
|
||||
'letters_word_accetuation_validate', content_name='SlovarIJS_BESEDE_utf8.lex',
|
||||
content_shuffle_vector='content_shuffle_vector', shuffle_vector='shuffle_vector',
|
||||
inputs_location='', content_location='')
|
||||
|
||||
num_examples = len(X_train) # training set size
|
||||
nn_output_dim = 11
|
||||
|
||||
num_examples = len(data.x_train) # training set size
|
||||
nn_output_dim = 10
|
||||
nn_hdim = 516
|
||||
|
||||
word_processor = Sequential()
|
||||
word_processor.add(Conv1D(43, (3), input_shape=(23, 43), padding='same', activation='relu'))
|
||||
word_processor.add(Conv1D(43, (3), padding='same', activation='relu'))
|
||||
word_processor.add(MaxPooling1D(pool_size=2))
|
||||
word_processor.add(Flatten())
|
||||
word_processor.add(Dense(516, activation='relu', kernel_constraint=maxnorm(3)))
|
||||
|
||||
metadata_processor = Sequential()
|
||||
metadata_processor.add(Dense(256, input_dim=167, activation='relu'))
|
||||
|
||||
model = Sequential()
|
||||
model.add(Merge([word_processor, metadata_processor], mode='concat')) # Merge is your sensor fusion buddy
|
||||
model.add(Dense(1024, input_dim=(516 + 256), activation='relu'))
|
||||
model.add(Dropout(0.3))
|
||||
model.add(Dense(1024, input_dim=(516 + 256), activation='relu'))
|
||||
model.add(Dropout(0.2))
|
||||
model.add(Dense(nn_output_dim, activation='sigmoid'))
|
||||
batch_size = 16
|
||||
# actual_epoch = 1
|
||||
actual_epoch = 60
|
||||
# num_fake_epoch = 2
|
||||
num_fake_epoch = 20
|
||||
|
||||
|
||||
# In[10]:
|
||||
|
||||
|
||||
# epochs = 5
|
||||
# lrate = 0.1
|
||||
# decay = lrate/epochs
|
||||
# sgd = SGD(lr=lrate, momentum=0.9, decay=decay, nesterov=False)
|
||||
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
|
||||
model.fit([X_train, X_other_features_train], y_train, validation_data=([X_validate, X_other_features_validate], y_validate), epochs=10, batch_size=10)
|
||||
model.save('v1_1.h5')
|
||||
conv_input_shape=(23, 36)
|
||||
othr_input = (141, )
|
||||
|
||||
conv_input = Input(shape=conv_input_shape, name='conv_input')
|
||||
x_conv = Conv1D(133, (3), padding='same', activation='relu')(conv_input)
|
||||
x_conv = Conv1D(46, (3), padding='same', activation='relu')(x_conv)
|
||||
x_conv = MaxPooling1D(pool_size=2)(x_conv)
|
||||
x_conv = Flatten()(x_conv)
|
||||
|
||||
othr_input = Input(shape=othr_input, name='othr_input')
|
||||
|
||||
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 = Dropout(0.3)(x)
|
||||
x = Dense(256, activation='relu')(x)
|
||||
x = Dropout(0.2)(x)
|
||||
x = Dense(nn_output_dim, activation='sigmoid')(x)
|
||||
|
||||
|
||||
|
||||
|
||||
model = Model(inputs=[conv_input, othr_input], outputs=x)
|
||||
opt = optimizers.Adam(lr=1E-4, beta_1=0.9, beta_2=0.999, epsilon=1e-08)
|
||||
model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[actual_accuracy,])
|
||||
# model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
|
||||
|
||||
|
||||
history = model.fit_generator(data.generator('train', batch_size, content_name='SlovarIJS_BESEDE_utf8.lex', content_location=''),
|
||||
data.x_train.shape[0]/(batch_size * num_fake_epoch),
|
||||
epochs=actual_epoch*num_fake_epoch,
|
||||
validation_data=data.generator('test', batch_size, content_name='SlovarIJS_BESEDE_utf8.lex', content_location=''),
|
||||
validation_steps=data.x_test.shape[0]/(batch_size * num_fake_epoch),
|
||||
verbose=2
|
||||
)
|
||||
|
||||
name = '60_epoch'
|
||||
model.save(name + '.h5')
|
||||
output = open(name + '_history.pkl', 'wb')
|
||||
pickle.dump(history.history, output)
|
||||
output.close()
|
||||
|
|
|
|||
3
workbench.sh
Normal file
3
workbench.sh
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
#!/bin/sh
|
||||
#export KERAS_BACKEND=theano
|
||||
THEANO_FLAGS='mode=FAST_RUN,device=gpu,floatX=float32,nvcc.flags=-D_FORCE_INLINES' python3 workbench.py
|
||||
14
workbench.xrsl
Normal file
14
workbench.xrsl
Normal file
|
|
@ -0,0 +1,14 @@
|
|||
&
|
||||
(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")
|
||||
)
|
||||
(outputfiles=("60_epoch.h5" "")("workbench.py" "")("workbench.sh" "")("60_epoch_history.pkl" "")
|
||||
)
|
||||
(stdout="out.txt")
|
||||
(stderr="err.txt")
|
||||
(gmlog="gmlog")
|
||||
(runtimeenvironment="APPS/BASE/THEANO-GPU-0.9")
|
||||
(gridTime=1000)
|
||||
(memory=12000)
|
||||
Loading…
Reference in New Issue
Block a user