refactor (#266)

autokeras/__init__.py

@@ -1,2 +1,2 @@
-from autokeras.image_supervised import ImageClassifier, ImageRegressor
+from autokeras.image.image_supervised import ImageClassifier, ImageRegressor
 from autokeras.text.text_supervised import TextClassifier

autokeras/gan.py → autokeras/image/gan.py

@@ -5,8 +5,8 @@
 import torchvision.utils as vutils
 
 from autokeras.constant import Constant
-from autokeras.loss_function import binary_classification_loss
-from autokeras.model_trainer import GANModelTrainer
+from autokeras.nn.loss_function import binary_classification_loss
+from autokeras.nn.model_trainer import GANModelTrainer
 from autokeras.preprocessor import ImageDataTransformer
 from autokeras.unsupervised import Unsupervised
 from autokeras.utils import get_device

autokeras/image_supervised.py → autokeras/image/image_supervised.py

@@ -11,8 +11,8 @@
 
 from autokeras.cnn_module import CnnModule
 from autokeras.constant import Constant
-from autokeras.loss_function import classification_loss, regression_loss
-from autokeras.metric import Accuracy, MSE
+from autokeras.nn.loss_function import classification_loss, regression_loss
+from autokeras.nn.metric import Accuracy, MSE
 from autokeras.preprocessor import OneHotEncoder, ImageDataTransformer
 from autokeras.supervised import Supervised, PortableClass
 from autokeras.utils import has_file, pickle_from_file, pickle_to_file, temp_folder_generator, validate_xy

autokeras/net_transformer.py

@@ -2,10 +2,10 @@
 from operator import itemgetter
 from random import randrange, sample
 
-from autokeras.graph import NetworkDescriptor
+from autokeras.nn.graph import NetworkDescriptor
 
 from autokeras.constant import Constant
-from autokeras.layers import is_layer
+from autokeras.nn.layers import is_layer
 
 
 def to_wider_graph(graph):

autokeras/generator.py → autokeras/nn/generator.py

@@ -1,6 +1,6 @@
 from autokeras.constant import Constant
-from autokeras.graph import Graph
-from autokeras.layers import StubBatchNormalization, StubConv, StubDropout, StubPooling, StubDense, StubFlatten, \
+from autokeras.nn.graph import Graph
+from autokeras.nn.layers import StubBatchNormalization, StubConv, StubDropout, StubPooling, StubDense, StubFlatten, \
     StubReLU
 
 

autokeras/graph.py → autokeras/nn/graph.py

@@ -6,9 +6,9 @@
 import keras
 
 from autokeras.constant import Constant
-from autokeras.layer_transformer import wider_bn, wider_next_conv, wider_next_dense, wider_pre_dense, wider_pre_conv, \
+from autokeras.nn.layer_transformer import wider_bn, wider_next_conv, wider_next_dense, wider_pre_dense, wider_pre_conv, \
     deeper_conv_block, dense_to_deeper_block, add_noise
-from autokeras.layers import StubConcatenate, StubAdd, StubConv, is_layer, layer_width, \
+from autokeras.nn.layers import StubConcatenate, StubAdd, StubConv, is_layer, layer_width, \
     to_real_keras_layer, set_torch_weight_to_stub, set_stub_weight_to_torch, set_stub_weight_to_keras, \
     set_keras_weight_to_stub, StubBatchNormalization, StubReLU
 

autokeras/layer_transformer.py → autokeras/nn/layer_transformer.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from autokeras.layers import StubConv, StubBatchNormalization, StubDense, StubReLU
+from autokeras.nn.layers import StubConv, StubBatchNormalization, StubDense, StubReLU
 
 NOISE_RATIO = 1e-4
 

autokeras/search.py

@@ -7,8 +7,8 @@
 
 from autokeras.bayesian import edit_distance, BayesianOptimizer
 from autokeras.constant import Constant
-from autokeras.generator import CnnGenerator
-from autokeras.model_trainer import ModelTrainer
+from autokeras.nn.generator import CnnGenerator
+from autokeras.nn.model_trainer import ModelTrainer
 from autokeras.net_transformer import default_transform
 from autokeras.utils import pickle_to_file, pickle_from_file, verbose_print
 

autokeras/text/text_supervised.py

@@ -8,8 +8,8 @@
 
 from autokeras.cnn_module import CnnModule
 from autokeras.constant import Constant
-from autokeras.loss_function import classification_loss
-from autokeras.metric import Accuracy
+from autokeras.nn.loss_function import classification_loss
+from autokeras.nn.metric import Accuracy
 from autokeras.preprocessor import OneHotEncoder, TextDataTransformer
 from autokeras.supervised import Supervised
 from autokeras.text.text_preprocessor import text_preprocess

examples/code_reuse_example.py

@@ -6,9 +6,9 @@
 from torch.utils.data import DataLoader
 from torchvision.transforms import Compose
 
-from autokeras.loss_function import classification_loss
-from autokeras.metric import Accuracy
-from autokeras.model_trainer import ModelTrainer
+from autokeras.nn.loss_function import classification_loss
+from autokeras.nn.metric import Accuracy
+from autokeras.nn.model_trainer import ModelTrainer
 from autokeras.preprocessor import OneHotEncoder, MultiTransformDataset
 
 

examples/load_raw_image/load.py

@@ -1,8 +1,7 @@
 #To run first unzip ../load_raw_image_data.zip into ../
 # so the train and test directories reside in this directory 
 
-from autokeras.image_supervised import load_image_dataset
-from keras.datasets import mnist
+from autokeras.image.image_supervised import load_image_dataset
 from autokeras import ImageClassifier
 
 

tests/common.py

@@ -4,8 +4,8 @@
 import numpy as np
 
 from autokeras.constant import Constant
-from autokeras.graph import Graph
-from autokeras.layers import StubReLU, StubConv, StubBatchNormalization, StubDropout, StubFlatten, StubSoftmax, \
+from autokeras.nn.graph import Graph
+from autokeras.nn.layers import StubReLU, StubConv, StubBatchNormalization, StubDropout, StubFlatten, StubSoftmax, \
     StubDense, StubConcatenate, StubAdd, StubPooling
 from autokeras.preprocessor import ImageDataTransformer
 

tests/test_dcgan.py → tests/image/test_dcgan.py

@@ -3,7 +3,7 @@
 import numpy as np
 
 from autokeras.constant import Constant
-from autokeras.gan import DCGAN
+from autokeras.image.gan import DCGAN
 from tests.common import clean_dir
 
 
@@ -12,7 +12,7 @@ def mock_train(**kwargs):
     return 1, 0
 
 
-@patch('autokeras.gan.GANModelTrainer.train_model', side_effect=mock_train)
+@patch('autokeras.image.gan.GANModelTrainer.train_model', side_effect=mock_train)
 def test_fit_generate(_):
     Constant.MAX_ITER_NUM = 1
     Constant.MAX_MODEL_NUM = 4

tests/test_image_supervised.py → tests/image/test_image_supervised.py

@@ -2,7 +2,7 @@
 
 import pytest
 
-from autokeras.image_supervised import *
+from autokeras.image.image_supervised import *
 from tests.common import clean_dir, MockProcess, simple_transform
 
 
@@ -175,7 +175,7 @@ def test_fit_csv_file(_, _1):
     clean_dir(os.path.join(path, "temp"))
 
 
-@patch('autokeras.image_supervised.temp_folder_generator', return_value='dummy_path/')
+@patch('autokeras.image.image_supervised.temp_folder_generator', return_value='dummy_path/')
 def test_init_image_classifier_with_none_path(_):
     clf = ImageClassifier()
     assert clf.path == 'dummy_path/'

tests/test_generator.py → tests/nn/test_generator.py

@@ -1,5 +1,5 @@
-from autokeras.generator import *
-from autokeras.graph import TorchModel
+from autokeras.nn.generator import *
+from autokeras.nn.graph import TorchModel
 
 
 def test_default_generator():

tests/test_graph.py → tests/nn/test_graph.py

@@ -1,5 +1,5 @@
-from autokeras.generator import CnnGenerator
-from autokeras.graph import *
+from autokeras.nn.generator import CnnGenerator
+from autokeras.nn.graph import *
 from autokeras.net_transformer import legal_graph
 from tests.common import get_conv_data, get_add_skip_model, get_conv_dense_model, get_pooling_model, \
     get_concat_skip_model

tests/test_layer_transformer.py → tests/nn/test_layer_transformer.py

@@ -1,6 +1,6 @@
 from autokeras.constant import Constant
-from autokeras.generator import CnnGenerator
-from autokeras.layer_transformer import *
+from autokeras.nn.generator import CnnGenerator
+from autokeras.nn.layer_transformer import *
 from tests.common import get_conv_dense_model
 
 

tests/test_model_trainer.py → tests/nn/test_model_trainer.py

@@ -1,8 +1,8 @@
-from autokeras.gan import Generator, Discriminator
-from autokeras.generator import CnnGenerator
-from autokeras.loss_function import classification_loss, regression_loss, binary_classification_loss
-from autokeras.metric import Accuracy, MSE
-from autokeras.model_trainer import ModelTrainer, GANModelTrainer
+from autokeras.image.gan import Generator, Discriminator
+from autokeras.nn.generator import CnnGenerator
+from autokeras.nn.loss_function import classification_loss, regression_loss, binary_classification_loss
+from autokeras.nn.metric import Accuracy, MSE
+from autokeras.nn.model_trainer import ModelTrainer, GANModelTrainer
 from tests.common import get_classification_data_loaders, get_regression_data_loaders, \
     get_classification_train_data_loaders
 

tests/test_net_transformer.py

@@ -1,7 +1,7 @@
 import torch
 
-from autokeras.generator import CnnGenerator
-from autokeras.graph import Graph
+from autokeras.nn.generator import CnnGenerator
+from autokeras.nn.graph import Graph
 from autokeras.net_transformer import *
 from tests.common import get_conv_dense_model, get_pooling_model, get_conv_data
 

tests/test_search.py

@@ -1,7 +1,7 @@
 from unittest.mock import patch
 
-from autokeras.loss_function import classification_loss
-from autokeras.metric import Accuracy
+from autokeras.nn.loss_function import classification_loss
+from autokeras.nn.metric import Accuracy
 from autokeras.search import *
 
 from tests.common import clean_dir, MockProcess, get_classification_data_loaders, get_add_skip_model, \