Created
July 10, 2019 07:29
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from keras.layers import Dense, Dropout, Flatten, Conv1D, Input, MaxPooling1D | |
from keras.models import Model | |
from keras.callbacks import EarlyStopping, ModelCheckpoint | |
from keras import backend as K | |
K.clear_session() | |
inputs = Input(shape=(8000,1)) | |
#First Conv1D layer | |
conv = Conv1D(8,13, padding='valid', activation='relu', strides=1)(inputs) | |
conv = MaxPooling1D(3)(conv) | |
conv = Dropout(0.3)(conv) | |
#Second Conv1D layer | |
conv = Conv1D(16, 11, padding='valid', activation='relu', strides=1)(conv) | |
conv = MaxPooling1D(3)(conv) | |
conv = Dropout(0.3)(conv) | |
#Third Conv1D layer | |
conv = Conv1D(32, 9, padding='valid', activation='relu', strides=1)(conv) | |
conv = MaxPooling1D(3)(conv) | |
conv = Dropout(0.3)(conv) | |
#Fourth Conv1D layer | |
conv = Conv1D(64, 7, padding='valid', activation='relu', strides=1)(conv) | |
conv = MaxPooling1D(3)(conv) | |
conv = Dropout(0.3)(conv) | |
#Flatten layer | |
conv = Flatten()(conv) | |
#Dense Layer 1 | |
conv = Dense(256, activation='relu')(conv) | |
conv = Dropout(0.3)(conv) | |
#Dense Layer 2 | |
conv = Dense(128, activation='relu')(conv) | |
conv = Dropout(0.3)(conv) | |
outputs = Dense(len(labels), activation='softmax')(conv) | |
model = Model(inputs, outputs) | |
model.summary() |
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