Functions — github.com/ValentinVignal/midiGenerator

↓ 2 callersMethodgenerate_from_array

:param mask: :param array: (nb_instruments, batch, nb_steps, step_size, inputs_size, channels) :param length: :retur

src/MidiGenerator/MGGenerate.py:18

↓ 2 callersMethodgenerate_from_data

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:262

↓ 2 callersMethodget_all_song

:param in_batch_format: :param song_number: :return:

src/NN/Sequences/KerasSequence.py:352

↓ 2 callersMethodget_config

(self)

src/NN/layers/wrapper/l.py:16

↓ 2 callersMethodget_index_first_step_song

:param song_number: :return:

src/NN/Sequences/KerasSequence.py:317

↓ 2 callersMethodget_item

(self, item)

src/NN/Sequences/KerasSequence.py:129

↓ 2 callersMethodget_nn_mask

:param instrument_mask: :return:

src/Midi/Player/BandPlayer.py:90

↓ 2 callersMethodget_played_model

:return: nb_instruments, input_size, length, 1)

src/Midi/Player/BandPlayer.py:155

↓ 2 callersMethodget_song_len

:param song_number: :return: The number of steps available in this song

src/NN/Sequences/KerasSequence.py:305

↓ 2 callersMethodget_val_acc_mean

:param logs: :return:

src/NN/Callbacks/BestAccuracy.py:55

↓ 2 callersMethodget_val_acc_mean

:param logs: :return:

src/NN/Callbacks/CheckPoint.py:60

↓ 2 callersMethodget_val_loss

:param logs: :return:

src/NN/Callbacks/BestAccuracy.py:69

↓ 2 callersMethodget_val_loss

:param logs: :return:

src/NN/Callbacks/CheckPoint.py:74

↓ 2 callersMethodget_xy

(self, index, nb_el=None)

src/NN/Sequences/FastSequence.py:163

↓ 2 callersFunctionhas_tensorboard

(root)

simpleWorkingScripts/diagnose_tensorboard.py:371

↓ 2 callersMethodis_a_default_param

:param name: :return: True if the parameters cannot change

src/BayesianOpt/Dimensions.py:98

↓ 2 callersFunctionmidifile_to_stream

:param filename: :param keep_drums: :return:

src/Midi/open.py:84

↓ 2 callersMethodnew_model

:param loss_options: :param model_id: model_name;model_param;nb_steps :param input_param: :param opt_param: {'lr', '

src/NN/KerasNeuralNetwork.py:100

↓ 2 callersFunctionno_silence

Erase silence at the begining and at the end of the matrix :param matrix: np array (nb_instruments, input_size, nb_steps, 2) :return:

src/Midi/open.py:12

↓ 2 callersFunctionnotes_to_matrix

:param notes: The notes :param durations: The duration of the notes :param offsets: The offset of the notes :return: The matrix corr

src/Midi/open.py:29

↓ 2 callersFunctionpip

Invoke command-line Pip with the specified args. Returns: A bytestring containing the output of Pip.

simpleWorkingScripts/diagnose_tensorboard.py:89

↓ 2 callersMethodpoint_to_dict

:param x: list of all dimension value :return: the value but in a dict with the names of the dimension as a key: d[name] = value

src/BayesianOpt/Dimensions.py:130

↓ 2 callersMethodsave_tensorboard_plots

(self, path)

src/NN/KerasNeuralNetwork.py:379

↓ 2 callersMethodset_in_training

(self, in_training)

src/NN/in_training.py:59

↓ 2 callersMethodshow_pianoroll

(self, pianoroll)

src/Images/RealTimePianoroll.py:38

↓ 2 callersMethodsong_file

:param song_number: :return: the number of the file where the song is stored

src/NN/Sequences/KerasSequence.py:292

↓ 2 callersFunctiontranspose_to_c

:param keep_non_traditional: :param stream: music21 stream :return:

src/Midi/open.py:364

↓ 2 callersMethodupdate_with_fit_args

(self, **kwargs)

src/NN/layers/vae.py:378

↓ 1 callersMethod__getitem__

(self, index)

src/NN/in_training.py:73

↓ 1 callersMethod__init__

(self, **kwargs)

src/NN/in_training.py:7

↓ 1 callersMethod__init__

:param sizes: List()[int] :param dropout: :param indep_weights:

src/NN/layers/gnc.py:123

↓ 1 callersMethod__init__

(self, **kwargs)

simpleWorkingScripts/keras_if.py:50

↓ 1 callersMethodaccuracy_generation

:param array: (nb_instruments, size, nb_step * length, channels) :param truth: (nb_instruments, size, nb_step * length, channels)

src/MidiGenerator/MGComputeGeneration.py:45

↓ 1 callersMethodadd_clean_args

:param argtype: :return:

src/Args/Parser.py:470

↓ 1 callersMethodadd_compute_data_args

:param self: :param argtype: :return:

src/Args/Parser.py:421

↓ 1 callersMethodadd_create_model_args

:param self: :param argtype: :return:

src/Args/Parser.py:225

↓ 1 callersMethodadd_evaluate_model_args

:param self: :param argtype: :return:

src/Args/Parser.py:168

↓ 1 callersMethodadd_execution_type_args

:param self: :param argtype: :return:

src/Args/Parser.py:387

↓ 1 callersMethodadd_generation_args

:param self: :param artype: :return:

src/Args/Parser.py:340

↓ 1 callersMethodadd_hp_search_args

:param argtype: :return:

src/Args/Parser.py:450

↓ 1 callersMethodadd_hp_summary_args

:param argtype: :return:

src/Args/Parser.py:510

↓ 1 callersMethodadd_load_data_args

:param self: :param argtype: :return:

src/Args/Parser.py:408

↓ 1 callersMethodadd_load_model_args

:param self: :param argtype: :return:

src/Args/Parser.py:371

↓ 1 callersMethodadd_loss_args

:param argtyp: :return:

src/Args/Parser.py:180

↓ 1 callersMethodadd_n_scripts_bo_args

:param argtype: :return:

src/Args/Parser.py:519

↓ 1 callersMethodadd_train_args

:param self: :param argtype: :return:

src/Args/Parser.py:129

↓ 1 callersMethodadd_zip_args

:param argtype: :return:

src/Args/Parser.py:491

↓ 1 callersMethodallow_growth

:return:

src/NN/KerasNeuralNetwork.py:479

↓ 1 callersMethodbuild

(self, input_shape)

simpleWorkingScripts/keras_if.py:26

↓ 1 callersFunctionbuild_model

()

simpleWorkingScripts/working_rnn.py:76

↓ 1 callersFunctionbuild_model

()

simpleWorkingScripts/stack_no_eager.py:53

↓ 1 callersFunctioncheck

Decorator to register a function as a check. Checks are run in the order in which they are registered. Args: fn: A function that takes

simpleWorkingScripts/diagnose_tensorboard.py:61

↓ 1 callersFunctioncheck_args

:param args: :return:

compute_data.py:18

↓ 1 callersMethodclear_session

()

src/NN/KerasNeuralNetwork.py:502

↓ 1 callersMethodcompare_test_predict_on_batch

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:348

↓ 1 callersMethodcompute_axis

(self, axis)

src/NN/layers/shapes.py:105

↓ 1 callersMethodcompute_axis

(self, axis)

src/NN/layers/shapes.py:202

↓ 1 callersMethodcompute_axis_with_batch

(self, input_shape)

src/NN/layers/shapes.py:127

↓ 1 callersMethodcompute_axis_with_batch

(self, input_shape)

src/NN/layers/shapes.py:222

↓ 1 callersMethodcompute_epoch_start

(self, nb_epochs)

src/NN/layers/vae.py:370

↓ 1 callersMethodcompute_epoch_start

(self)

src/NN/Callbacks/Annealing.py:57

↓ 1 callersMethodcompute_epoch_stop

(self, nb_epochs)

src/NN/layers/vae.py:374

↓ 1 callersMethodcompute_epoch_stop

(self)

src/NN/Callbacks/Annealing.py:61

↓ 1 callersFunctioncompute_filters_before_pooling

:param input_filters: :param filters: :return:

src/NN/shapes/convolution.py:51

↓ 1 callersMethodcompute_output_shape

:param input_shape: :return:

src/NN/layers/gnc.py:163

↓ 1 callersFunctioncompute_size_before_pooling

:param input_size: int :param nb_pool: :param stride: int :return:

src/NN/shapes/convolution.py:36

↓ 1 callersMethodcompute_sum_axis_with_batch

(sum_axis)

src/NN/layers/vae.py:279

↓ 1 callersMethodcompute_sum_axis_with_batch

(sum_axis)

src/NN/layers/vae.py:337

↓ 1 callersFunctionconverter_func

:param use_binary: :param arr: :param mono: :param no_duration: :return:

src/Midi/create.py:146

↓ 1 callersFunctionconverter_func_mono

:param use_binary: :param arr: (nb_instruments, 88, nb_steps, 1) :return:

src/Midi/create.py:97

↓ 1 callersFunctionconverter_func_poly

:param arr: (nb_instruments, 88, nb_steps, 2) :param no_duration: if True : all notes will be the shortest length possible :return:

src/Midi/create.py:58

↓ 1 callersFunctioncreate

# Mandatory arguments :param loss_options: :param input_param: { nb_instruments,

src/NN/Models/RRMVAEMono/RRMVAEMono.py:42

↓ 1 callersFunctioncreate

# Mandatory arguments :param loss_options: :param input_param: { nb_instruments,

src/NN/Models/RMVAEMono/RMVAEMono.py:42

↓ 1 callersFunctioncreate_dimensions

From the args, it creates all the dimensions on which the bayesian optimization will work on :param args: :return:

bayesian-opt.py:33

↓ 1 callersFunctioncreate_model

Creates a model from all the inputs == dimensions of the bayesian optimization

bayesian-opt.py:226

↓ 1 callersMethodcreate_optimizer

:param kwargs: :return:

src/NN/KerasNeuralNetwork.py:150

↓ 1 callersMethodcreate_tensorboard_plots

(self, log_dir, path)

src/NN/KerasNeuralNetwork.py:389

↓ 1 callersMethodcreate_token

create a token in the temp file for the save folder :return:

src/MidiGenerator/MGLogistic.py:13

↓ 1 callersMethodcreate_token_midis_path

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:291

↓ 1 callersMethodcreate_token_midis_path

:return:

src/MidiGenerator/MGLogistic.py:62

↓ 1 callersMethodcreate_tokens

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:300

↓ 1 callersFunctiondecay_func

(lr_init)

simpleWorkingScripts/working_rnn.py:51

↓ 1 callersFunctiondecay_func

(lr_init)

simpleWorkingScripts/stack_no_eager.py:25

↓ 1 callersMethoddecay_func

(lr_init, **kwargs)

src/NN/KerasNeuralNetwork.py:186

↓ 1 callersMethoddefault_value

:param name: :return: The default value of the dimension

src/BayesianOpt/Dimensions.py:122

↓ 1 callersMethoddelete_token

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:282

↓ 1 callersMethoddelete_token

Delete the token associated to the model :return:

src/MidiGenerator/MGLogistic.py:22

↓ 1 callersMethoddelete_tokens

:return:

src/MidiGenerator/MGLogistic.py:81

↓ 1 callersMethoddescription_msg

:param argtype: :return: The description message for the ArgumentParser

src/Args/Parser.py:75

↓ 1 callersMethoddisable_eager_exection

()

src/NN/KerasNeuralNetwork.py:506

↓ 1 callersMethoddo_init

:param argtype: :return:

src/Args/Parser.py:29

↓ 1 callersFunctioneval_song_array

:param seed_length: :param array: (instruments, size, length, channels) :return:

src/res/eval/eval.py:17

↓ 1 callersFunctioneval_song_midi

:param path: :return:

src/res/eval/eval.py:42

↓ 1 callersFunctioneval_songs_folder

:param path: :return:

src/res/eval/eval.py:59

↓ 1 callersMethodevaluate_generator

(self, generator, in_training=0, **kwargs)

src/NN/in_training.py:48

↓ 1 callersFunctionf0

(x)

simpleWorkingScripts/keras_if.py:80

↓ 1 callersFunctionf1

(x)

simpleWorkingScripts/keras_if.py:84

↓ 1 callersMethodfrom_config

(self)

src/NN/layers/attention.py:125

↓ 1 callersMethodgenerate_fill

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:268

↓ 1 callersMethodgenerate_from_noise

(self, *args, **kwargs)

src/MidiGenerator/MGInit.py:265

Functions815 in github.com/ValentinVignal/midiGenerator