from sklearn.utils import shuffle
from sklearn.neighbors import KNeighborsClassifier
if __name__ == "__main__":
from __test_my_layer import MyLayerV1
e_len = 128
batch_size = 128
db = INFO['fashion']
shape = db['shape']
n_cls = db['n_cls']
X_train, X_test, y_train, y_test = get_fewshot(*load_data('fashion'),
shot=None)
X_train, y_train = shuffle(X_train, y_train)
X_test, y_test = shuffle(X_test, y_test)
X_train = reshape(X_train / 255.0, shape)
X_test = reshape(X_test / 255.0, shape)
# %% CNN My Dual Model
in_layer = layers.Input(shape=shape)
conv_01 = layers.Conv2D(32, (3, 3))(in_layer)
batch_01 = layers.BatchNormalization()(conv_01)
active_01 = layers.Activation('relu')(batch_01)
from tensorflow.keras import backend as K
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.callbacks import EarlyStopping
from sklearn.neighbors import KNeighborsClassifier
if __name__ == "__main__":
embed_size = 128
db = INFO['fashion']
shape = db['shape']
n_cls = db['n_cls']
X_train, X_test, y_train, y_test = load_data('fashion')
X_train = reshape(X_train / 255.0, shape)
X_test = reshape(X_test / 255.0, shape)
# %% CNN My Dual Model
in_layer = layers.Input(shape=shape)
conv_01 = layers.Conv2D(32, (3, 3))(in_layer)
batch_01 = layers.BatchNormalization()(conv_01)
active_01 = layers.Activation('relu')(batch_01)
conv_02 = layers.Conv2D(32, (3, 3))(active_01)
batch_02 = layers.BatchNormalization()(conv_02)
active_02 = layers.Activation('relu')(batch_02)
# %% Initialization way = -1 shot = None s_ver = 'V01' build = 'MyModelV2' db = 'mnist' n_cls = INFO[db]['n_cls'] shape = INFO[db]['shape'] rpt = Reporter(file_dir='./my_report.log') # %% Dataset loading data = load_data(db) X_train, X_test, y_train, y_test = get_fewshot(*data, shot, way) X_train, y_train = shuffle(X_train, y_train) X_test, y_test = shuffle(X_test, y_test) X_train = reshape(X_train / 255.0, shape) X_test = reshape(X_test / 255.0, shape) # %% Generator section traingen = MyTriplet(X_train, y_train, n_cls) validgen = MyTriplet(X_test, y_test, n_cls) # %% Schema creation schema = load_schema(s_ver)
