def __init__(self, n_filter, filter_size, stride=1, pad=0):
self.FN = n_filter
self.FH = filter_size[0]
self.FW = filter_size[1]
self.W = None #.astype(np.float32)
self.b = None #.astype(np.float32)
self.stride = stride
self.pad = pad
# 中間データ（backward時に使用）
self.x = None
self.col = None
self.col_W = None
# 重み・バイアスパラメータの勾配
self.dW = None
self.db = None
self.xp = None
name = 'conv'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.params['W_' + self.name] = self.W
self.params['b_' + self.name] = self.b
self.grads = {}
self.grads['W_' + self.name] = self.dW
self.grads['b_' + self.name] = self.db
def __init__(self, W, b, stride=1, pad=0):
self.W = W #.astype(np.float32)
self.b = b #.astype(np.float32)
self.stride = stride
self.pad = pad
# 中間データ（backward時に使用）
self.x = None
self.col = None
self.col_W = None
# 重み・バイアスパラメータの勾配
self.dW = None
self.db = None
self.xp = None
name = 'conv'
self.name = ut.naming(name, names)
names.append(self.name)
# self.params = {}
# self.params['W_' + self.name] = self.W
# self.params['b_' + self.name] = self.b
self.grads = {}
self.grads['W_' + self.name] = self.dW
self.grads['b_' + self.name] = self.db
def __init__(self):
self.x_shape = None
name = 'Flatten'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self):
self.mask = None
name = 'ReLU'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self):
self.y = None
self.t = None
name = 'Mean_squared_error'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self):
self.y = None
self.t = None
name = 'Softmax_cross_entropy'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self, ratio=0.5):
self.ratio = ratio
self.mask = None
self.xp = None
name = 'Dropout'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self, alpha=1.0):
self.mask = None
self.alpha = alpha
self.y = None
self.xp = None
name = 'ELU'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self, pool_h, pool_w, stride=1, pad=0):
self.pool_h = pool_h
self.pool_w = pool_w
self.stride = stride
self.pad = pad
self.x = None
self.arg_max = None
self.xp = None
name = 'MaxPooling'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
def __init__(self, variational=False):
self.y = None
self.t = None
self.l1 = None
self.l2 = None
self.dl1 = None
self.dl2 = None
self.variational = variational
name = 'Softmax_cross_entropy'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.grads = {}
self.params['l1_' + self.name] = 0 # self.l1
self.params['l2_' + self.name] = 0 # self.l2
self.grads['l1_' + self.name] = 0 # self.dl1
self.grads['l2_' + self.name] = 0 # self.dl2
def __init__(self):
self.eps = 1e-5
self.gamma = None
self.beta = None
self.dgamma = None
self.dbeta = None
self.xp = None
name = 'bn'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.params['g_' + self.name] = self.gamma
self.params['b_' + self.name] = self.beta
self.grads = {}
self.grads['g_' + self.name] = self.dgamma
self.grads['b_' + self.name] = self.dbeta
def __init__(self, alpha=1.6732632423543772, scale=1.0507009873554805):
self.mask = None
self.y = None
self.alpha = alpha
self.scale = scale
self.dalpha = None
self.dscale = None
self.xp = None
name = 'selu'
self.name = ut.naming(name, names)
names.append(self.name)
# self.params = {}
# self.params['a_' + self.name] = self.alpha
# self.params['s_' + self.name] = self.scale
self.grads = {}
self.grads['a_' + self.name] = self.dalpha
self.grads['s_' + self.name] = self.dscale
def __init__(self, W, b):
self.W = W # .astype(np.float32)
self.b = b # .astype(np.float32)
self.x = None
self.dW = None
self.db = None
self.xp = None
name = 'lin'
self.name = ut.naming(name, names)
names.append(self.name)
# self.params = {}
# self.params['W_' + self.name] = self.W
# self.params['b_' + self.name] = self.b
self.grads = {}
self.grads['W_' + self.name] = self.dW
self.grads['b_' + self.name] = self.db
def __init__(self, output_size):
self.output_size = output_size
self.W = None #.astype(np.float32)
self.b = None #.astype(np.float32)
self.x = None
self.dW = None
self.db = None
self.xp = None
name = 'lin'
self.name = ut.naming(name, names)
names.append(self.name)
self.params = {}
self.params['W_' + self.name] = self.W
self.params['b_' + self.name] = self.b
self.grads = {}
self.grads['W_' + self.name] = self.dW
self.grads['b_' + self.name] = self.db