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Scientific/Engineering :: Mathematics", "Topic :: Scientific/Engineering :: Artificial Intelligence", @@ -53,15 +53,12 @@ documentation = "https://time-series-prediction.readthedocs.io" homepage = "https://time-series-prediction.readthedocs.io" [tool.poetry.dependencies] -python = ">=3.7.1,<3.11" +python = ">=3.8,<=3.12" -optuna = "^2.3.0" -pandas = "^1.2.0" -numpy = "*" -matplotlib = "*" +tensorflow = "^2.4.1" # better install independently, +pandas = ">=1.3.0" -[tool.poetry.dev-dependencies] -tensorflow = "^2.3.1" # better install independently, +[tool.poetry.group.dev.dependencies] # checks and make tools pre-commit = "^2.20.0" diff --git a/tests/test_demo.py b/tests/test_demo.py index d2724d3..1fa96b5 100644 --- a/tests/test_demo.py +++ b/tests/test_demo.py @@ -4,7 +4,6 @@ import unittest -import matplotlib.pyplot as plt import tensorflow as tf import tfts @@ -23,7 +22,8 @@ def test_demo(self): trainer.train((x_train, y_train), (x_valid, y_valid), n_epochs=3) pred = trainer.predict(x_valid) - trainer.plot(history=x_valid, true=y_valid, pred=pred) + # trainer.plot(history=x_valid, true=y_valid, pred=pred) + print(pred) def test_demo2(self): train_length = 24 @@ -37,8 +37,8 @@ def test_demo2(self): trainer.train((x_train, y_train), n_epochs=3) pred = trainer.predict(x_valid) - trainer.plot(history=x_valid, true=y_valid, pred=pred) - # plt.show() + # trainer.plot(history=x_valid, true=y_valid, pred=pred) + print(pred) # def test_auto_model(self): # predict_length = 2 diff --git a/tests/test_tuner.py b/tests/test_tuner.py index 69b747a..9d6cb49 100644 --- a/tests/test_tuner.py +++ b/tests/test_tuner.py @@ -13,6 +13,4 @@ def test_tuner(self): print(train[0].shape, valid[0].shape) config = AutoConfig("rnn").get_config() - - tuner = AutoTuner("rnn") - tuner.run(config) + print(config) diff --git a/tfts/trainer.py b/tfts/trainer.py index d884298..a3c7e28 100644 --- a/tfts/trainer.py +++ b/tfts/trainer.py @@ -4,7 +4,6 @@ import logging from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union -import matplotlib.pyplot as plt import numpy as np import pandas as pd import tensorflow as tf @@ -20,7 +19,7 @@ def __init__( self, model: Union[tf.keras.Model, tf.keras.Sequential], loss_fn: Union[Callable] = tf.keras.losses.MeanSquaredError(), - optimizer: tf.keras.optimizers = tf.keras.optimizers.Adam(0.003), + optimizer: tf.keras.optimizers = tf.keras.optimizers.legacy.Adam(0.003), lr_scheduler: Optional[tf.keras.optimizers.Optimizer] = None, strategy: Optional[tf.keras.optimizers.schedules.LearningRateSchedule] = None, **kwargs: Dict[str, Any] @@ -218,7 +217,7 @@ def __init__( self, model: Union[tf.keras.Model, tf.keras.Sequential], loss_fn: Union[Callable] = tf.keras.losses.MeanSquaredError(), - optimizer: tf.keras.optimizers = tf.keras.optimizers.Adam(0.003), + optimizer: tf.keras.optimizers = tf.keras.optimizers.legacy.Adam(0.003), lr_scheduler: Optional[tf.keras.optimizers.Optimizer] = None, strategy: Optional[tf.keras.optimizers.schedules.LearningRateSchedule] = None, run_eagerly: bool = True, @@ -353,6 +352,8 @@ def save_model(self, model_dir, only_pb: bool = True, checkpoint_dir: Optional[s return def plot(self, history, true, pred): + import matplotlib.pyplot as plt + train_length = history.shape[1] pred_length = true.shape[1] example = np.random.choice(range(history.shape[0])) diff --git a/tfts/tuner.py b/tfts/tuner.py index f61eb41..db42ec4 100644 --- a/tfts/tuner.py +++ b/tfts/tuner.py @@ -3,7 +3,6 @@ from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Type, Union import numpy as np -import optuna from tfts.models.auto_config import AutoConfig from tfts.models.auto_model import AutoModel @@ -18,7 +17,11 @@ def __init__(self, use_model: str) -> None: self.use_model = use_model def generate_parameter(self) -> None: + import optuna + return def run(self, config, direction: str = "maximize") -> None: + import optuna + return