def func_point_logits(dec_h, enc_e, enc_len):
'''
Args:
dec_h : shape(b_sz, h_dec_sz)
enc_e : shape(b_sz, tstp_enc, dec_emb_sz)
enc_len : shape(b_sz,)
'''
dec_h_ex = tf.expand_dims(dec_h, dim=1) # shape(b_sz, 1, h_dec_sz)
dec_h_ex = tf.tile(
dec_h_ex, [1, tstp_enc, 1]) # shape(b_sz, tstp_enc, h_dec_sz)
linear_concat = tf.concat(
2, [dec_h_ex, enc_e
]) # shape(b_sz, tstp_enc, h_dec_sz+ dec_emb_sz)
point_linear = TfUtils.last_dim_linear( # shape(b_sz, tstp_enc, h_dec_sz)
linear_concat,
output_size=h_dec_sz,
bias=False,
scope='Ptr_W')
point_v = TfUtils.last_dim_linear( # shape(b_sz, tstp_enc, 1)
tf.tanh(point_linear),
output_size=1,
bias=False,
scope='Ptr_V')
point_logits = tf.squeeze(point_v,
squeeze_dims=[2
]) # shape(b_sz, tstp_enc)
mask = TfUtils.mkMask(enc_len,
maxLen=tstp_enc) # shape(b_sz, tstp_enc)
point_logits = tf.select(mask, point_logits,
tf.ones_like(point_logits) *
small_num) # shape(b_sz, tstp_enc)
return point_logits
def func_point_logits(dec_h, enc_ptr, enc_len):
'''
Args:
dec_h : shape(b_sz, tstp_dec, h_dec_sz)
enc_ptr : shape(b_sz, tstp_dec, tstp_enc, Ptr_sz)
enc_len : shape(b_sz,)
'''
dec_h_ex = tf.expand_dims(
dec_h, axis=2) # shape(b_sz, tstp_dec, 1, h_dec_sz)
dec_h_ex = tf.tile(dec_h_ex,
[1, 1, tstp_enc, 1
]) # shape(b_sz, tstp_dec, tstp_enc, h_dec_sz)
linear_concat = tf.concat(axis=3, values=[
dec_h_ex, enc_ptr
]) # shape(b_sz, tstp_dec, tstp_enc, h_dec_sz+ Ptr_sz)
point_linear = TfUtils.last_dim_linear( # shape(b_sz, tstp_dec, tstp_enc, h_dec_sz)
linear_concat,
output_size=h_dec_sz,
bias=False,
scope='Ptr_W')
point_v = TfUtils.last_dim_linear( # shape(b_sz, tstp_dec, tstp_enc, 1)
tf.tanh(point_linear),
output_size=1,
bias=False,
scope='Ptr_V')
point_logits = tf.squeeze(
point_v, axis=[3]) # shape(b_sz, tstp_dec, tstp_enc)
enc_len = tf.expand_dims(enc_len, 1) # shape(b_sz, 1)
enc_len = tf.tile(enc_len, [1, tstp_dec]) # shape(b_sz, tstp_dec)
mask = TfUtils.mkMask(
enc_len, maxLen=tstp_enc) # shape(b_sz, tstp_dec, tstp_enc)
point_logits = tf.where(
mask,
point_logits, # shape(b_sz, tstp_dec, tstp_enc)
tf.ones_like(point_logits) * small_num)
return point_logits