Model: "model" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_data (InputLayer) [(None, 128)] 0 __________________________________________________________________________________________________ embedding (Embedding) (None, 128, 512) 1744384 input_data[0][0] __________________________________________________________________________________________________ add_channel (Reshape) (None, 128, 512, 1) 0 embedding[0][0] __________________________________________________________________________________________________ convolution_3 (Conv2D) (None, 126, 1, 128) 196736 add_channel[0][0] __________________________________________________________________________________________________ convolution_4 (Conv2D) (None, 125, 1, 128) 262272 add_channel[0][0] __________________________________________________________________________________________________ convolution_5 (Conv2D) (None, 124, 1, 128) 327808 add_channel[0][0] __________________________________________________________________________________________________ max_pooling_3 (MaxPooling2D) (None, 1, 1, 128) 0 convolution_3[0][0] __________________________________________________________________________________________________ max_pooling_4 (MaxPooling2D) (None, 1, 1, 128) 0 convolution_4[0][0] __________________________________________________________________________________________________ max_pooling_5 (MaxPooling2D) (None, 1, 1, 128) 0 convolution_5[0][0] __________________________________________________________________________________________________ concatenate (Concatenate) (None, 1, 1, 384) 0 max_pooling_3[0][0] max_pooling_4[0][0] max_pooling_5[0][0] __________________________________________________________________________________________________ flatten (Flatten) (None, 384) 0 concatenate[0][0] __________________________________________________________________________________________________ dropout (Dropout) (None, 384) 0 flatten[0][0] __________________________________________________________________________________________________ dense (Dense) (None, 18) 6930 dropout[0][0] ================================================================================================== Total params: 2,538,130 Trainable params: 2,538,130 Non-trainable params: 0 __________________________________________________________________________________________________ 

usage: train.py [-h] [-t TEST_SAMPLE_PERCENTAGE] [-p PADDING_SIZE] [-e EMBED_SIZE] [-f FILTER_SIZES] [-n NUM_FILTERS] [-d DROPOUT_RATE] [-c NUM_CLASSES] [-l REGULARIZERS_LAMBDA] [-b BATCH_SIZE] [--epochs EPOCHS] [--fraction_validation FRACTION_VALIDATION] [--results_dir RESULTS_DIR] This is the TextCNN train project. optional arguments: -h, --help show this help message and exit -t TEST_SAMPLE_PERCENTAGE, --test_sample_percentage TEST_SAMPLE_PERCENTAGE The fraction of test data.(default=0.1) -p PADDING_SIZE, --padding_size PADDING_SIZE Padding size of sentences.(default=128) -e EMBED_SIZE, --embed_size EMBED_SIZE Word embedding size.(default=512) -f FILTER_SIZES, --filter_sizes FILTER_SIZES Convolution kernel sizes.(default=3,4,5) -n NUM_FILTERS, --num_filters NUM_FILTERS Number of each convolution kernel.(default=128) -d DROPOUT_RATE, --dropout_rate DROPOUT_RATE Dropout rate in softmax layer.(default=0.5) -c NUM_CLASSES, --num_classes NUM_CLASSES Number of target classes.(default=18) -l REGULARIZERS_LAMBDA, --regularizers_lambda REGULARIZERS_LAMBDA L2 regulation parameter.(default=0.01) -b BATCH_SIZE, --batch_size BATCH_SIZE Mini-Batch size.(default=64) --epochs EPOCHS Number of epochs.(default=10) --fraction_validation FRACTION_VALIDATION The fraction of validation.(default=0.05) --results_dir RESULTS_DIR The results dir including log, model, vocabulary and some images.(default=./results/) 

usage: test.py [-h] [-p PADDING_SIZE] [-c NUM_CLASSES] results_dir This is the TextCNN test project. positional arguments: results_dir The results dir including log, model, vocabulary and some images. optional arguments: -h, --help show this help message and exit -p PADDING_SIZE, --padding_size PADDING_SIZE Padding size of sentences.(default=128) -c NUM_CLASSES, --num_classes NUM_CLASSES Number of target classes.(default=18)