SEED = 285139
# feat_cols = ["close", "volume", "amount"]
FEAT_COLS = ["close"]
# pylint: disable-msg=E0601,E1101
if __name__ == '__main__':
np.random.seed(SEED)
regressor = dnc_regressor.DNC_Model(
controller_units=CONTROLLER_UNITS,
memory_size=MEMORY_SIZE,
word_size=WORD_SIZE,
num_read_heads=NUM_READ_HEADS,
time_step=MAX_STEP,
feat_size=len(FEAT_COLS) * 2 * (TIME_SHIFT + 1),
dropout_rate=DROPOUT_RATE,
decayed_dropout_start=DECAYED_DROPOUT_START,
dropout_decay_steps=DROPOUT_DECAY_STEPS,
learning_rate=LEARNING_RATE,
decayed_lr_start=DECAYED_LR_START,
lr_decay_steps=LR_DECAY_STEPS)
run("test18_dnc",
regressor,
max_step=MAX_STEP,
time_shift=TIME_SHIFT,
feat_cols=FEAT_COLS)
np.random.seed(SEED)
regressor = dnc_regressor.DNC_Model_V4(
num_dnc_layers = NUM_DNC_LAYERS,
num_fcn_layers = NUM_FCN_LAYERS,
output_size=DNC_OUTPUT_SIZE,
controller_units=CONTROLLER_UNITS, memory_size=MEMORY_SIZE,
word_size=WORD_SIZE, num_read_heads=NUM_READ_HEADS,
time_step=MAX_STEP,
feat_size=len(FEAT_COLS) * 2 * (TIME_SHIFT + 1),
dropout_rate=DROPOUT_RATE,
decayed_dropout_start=DECAYED_DROPOUT_START,
dropout_decay_steps=DROPOUT_DECAY_STEPS,
learning_rate=LEARNING_RATE,
decayed_lr_start=DECAYED_LR_START,
lr_decay_steps=LR_DECAY_STEPS,
clipvalue=CLIP_VALUE
)
run(
id="test23_mdnc",
regressor=regressor,
max_step=MAX_STEP,
time_shift=TIME_SHIFT,
feat_cols=FEAT_COLS,
val_save_freq=VAL_SAVE_FREQ,
steps_per_epoch=STEPS_PER_EPOCH,
include_seqlens=False,
)
"layer_norm": True,
"activation": 'tanh',
'cell_type': 'clstm',
'connect': 'sparse',
}
memory_unit_config = {
"cell_type": 'cbmu',
"memory_length": 64,
"memory_width": 32,
"read_heads": 4,
"write_heads": 2,
"dnc_norm": True,
"bypass_dropout": False,
"wgate1": False,
}
regressor = dnc.MANN_Model(controller_config,
memory_unit_config,
time_step=MAX_STEP,
feat_size=len(feat_cols) * 2 * (TIME_SHIFT + 1),
dropout_rate=DROPOUT_RATE,
decayed_dropout_start=DECAYED_DROPOUT_START,
dropout_decay_steps=DROPOUT_DECAY_STEPS,
learning_rate=LEARNING_RATE,
decayed_lr_start=DECAYED_LR_START,
lr_decay_steps=LR_DECAY_STEPS,
seed=SEED)
run(regressor)