def build(self):
""" Initialize the weights of the model
"""
# For projecting on the keyboard space
self.project_hidden = tfutils.single_layer_perceptron([music.NB_NOTES, self.args.hidden_size],
'project_hidden')
# For projecting on the keyboard space
self.project_keyboard = tfutils.single_layer_perceptron([self.args.hidden_size, music.NB_NOTES],
'project_keyboard') # Should we do the activation sigmoid here ?
def build(self):
""" Initialize the weights of the model
"""
# TODO: Control over the the Cell using module arguments instead of global arguments (hidden_size and num_layer) !!
# RNN network
rnn_cell = tf.nn.rnn_cell.BasicLSTMCell(self.args.hidden_size, state_is_tuple=True) # Or GRUCell, LSTMCell(args.hidden_size)
if not self.args.test: # TODO: Should use a placeholder instead
rnn_cell = tf.nn.rnn_cell.DropoutWrapper(rnn_cell, input_keep_prob=1.0, output_keep_prob=0.9) # TODO: Custom values
rnn_cell = tf.nn.rnn_cell.MultiRNNCell([rnn_cell] * self.args.num_layers, state_is_tuple=True)
self.rnn_cell = rnn_cell
# For projecting on the keyboard space
self.project_output = tfutils.single_layer_perceptron([self.args.hidden_size, 12 + 1], # TODO: HACK: Input/output space hardcoded !!!
'project_output') # Should we do the activation sigmoid here ?
def build(self):
""" Initialize the weights of the model
"""
self.rnn_cell = tfutils.get_rnn_cell(self.args, "deco_cell")
self.project_key = tfutils.single_layer_perceptron([self.args.hidden_size, 1],
'project_key')