def model(ps):
src = tf.Input(shape=(ps.len_src, ), dtype='int32')
typ = tf.Input(shape=(ps.len_src, ), dtype='int32')
hint = tf.Input(shape=(ps.len_tgt, ), dtype='int32')
tgt = tf.Input(shape=(ps.len_tgt, ), dtype='int32')
ins = [src, typ, hint, tgt]
outs = [Trafo(ps)(ins)]
m = tf.Model(name='TrafoModel', inputs=ins, outputs=outs)
return m
def model_old(ps):
w, h = ps.img_width, ps.img_height
ins = [
tf.Input(shape=(w * h, ), dtype='float32'),
tf.Input(shape=(w * h, ), dtype='float32'),
tf.Input(shape=(1, ), dtype='int32'),
tf.Input(shape=(w * h, ), dtype='float32'),
tf.Input(shape=(1, ), dtype='int32'),
]
outs = [Mnist(ps)(ins)]
m = tf.Model(name='MnistModel', inputs=ins, outputs=outs)
return m
def model(ps):
seq = tf.Input(shape=(), dtype=tf.float32)
typ = tf.Input(shape=(), dtype=tf.float32)
opt = tf.Input(shape=(), dtype=tf.float32)
beg = tf.Input(shape=(), dtype=tf.float32)
end = tf.Input(shape=(), dtype=tf.float32)
uid = tf.Input(shape=(), dtype=tf.float32)
ins = [seq, typ, opt, beg, end, uid]
y = Squad(ps)([seq, typ])
outs = [SquadLoss(ps)([beg, end], y)]
m = tf.Model(name='SquadModel', inputs=ins, outputs=outs)
return m
def model(ps):
sh = (ps.len_src, )
src = tf.Input(shape=sh, dtype='int32', name='src')
typ = tf.Input(shape=sh, dtype='int32', name='typ')
sh = (ps.len_tgt, )
idx = tf.Input(shape=sh, dtype='int32', name='mlm_idx')
val = tf.Input(shape=sh, dtype='int32', name='mlm_val')
fit = tf.Input(shape=sh, dtype='bool', name='fit')
mlm = tf.Input(shape=sh, dtype='float32', name='mlm')
ins = [src, typ, fit, idx, val, mlm]
outs = [Bert(ps)(ins)]
m = tf.Model(name='BertModel', inputs=ins, outputs=outs)
return m