def __init__(self, inputSize, dictSize, patternSize, embSize, ls, cost) :
		# pooler = MCONV.NoPooling()
		pooler = MCONV.MaxPooling2D(1, 2)
		
		emb = MCONV.Embedding(size=inputSize, nbDimentions=embSize, dictSize=dictSize, name = 'Emb')
		
		c1 = MCONV.Convolution2D( 
			nbFilters = 1,
			filterHeight = 1,
			filterWidth = patternSize/2,
			activation = MA.ReLU(),
			pooler = pooler,
			name = "conv1"
		)

		c2 = MCONV.Convolution2D( 
			nbFilters = 4,
			filterHeight = 1,
			filterWidth = patternSize/2,
			activation = MA.ReLU(),
			pooler = MCONV.NoPooling(),
			name = "conv2"
		)

		f = MCONV.Flatten(name = "flat")
		h = ML.Hidden(5, activation = MA.ReLU(), decorators = [], regularizations = [], name = "hid" )
		o = ML.SoftmaxClassifier(2, decorators = [], learningScenario = ls, costObject = cost, name = "out", regularizations = [] )
		
		self.model = emb > c1 > c2 > f > h > o
dataset/ETHPy150Open tariqdaouda/Mariana/Mariana/examples/conv_basic_emb.py/ConvEmb.__init__/original