Method
__init__
(
self,
vocabulary_size,
embedding_size,
num_sampled=64,
activate_nce_loss=True,
nce_loss_args=None,
E_init=tl.initializers.random_uniform(minval=-1.0, maxval=1.0),
nce_W_init=tl.initializers.truncated_normal(stddev=0.03),
nce_b_init=tl.initializers.constant(value=0.0),
name=None, #'word2vec',
)
Source from the content-addressed store, hash-verified
| 186 | """ |
| 187 | |
| 188 | def __init__( |
| 189 | self, |
| 190 | vocabulary_size, |
| 191 | embedding_size, |
| 192 | num_sampled=64, |
| 193 | activate_nce_loss=True, |
| 194 | nce_loss_args=None, |
| 195 | E_init=tl.initializers.random_uniform(minval=-1.0, maxval=1.0), |
| 196 | nce_W_init=tl.initializers.truncated_normal(stddev=0.03), |
| 197 | nce_b_init=tl.initializers.constant(value=0.0), |
| 198 | name=None, #'word2vec', |
| 199 | ): |
| 200 | |
| 201 | super(Word2vecEmbedding, self).__init__(name) |
| 202 | self.vocabulary_size = vocabulary_size |
| 203 | self.embedding_size = embedding_size |
| 204 | self.num_sampled = num_sampled |
| 205 | self.E_init = E_init |
| 206 | self.activate_nce_loss = activate_nce_loss |
| 207 | |
| 208 | if self.activate_nce_loss: |
| 209 | self.nce_loss_args = nce_loss_args |
| 210 | self.nce_W_init = nce_W_init |
| 211 | self.nce_b_init = nce_b_init |
| 212 | |
| 213 | if not self._built: |
| 214 | self.build(tuple()) |
| 215 | self._built = True |
| 216 | |
| 217 | logging.info("Word2vecEmbedding %s: (%d, %d)" % (self.name, self.vocabulary_size, self.embedding_size)) |
| 218 | |
| 219 | def __repr__(self): |
| 220 | s = ('{classname}(') |
Callers
nothing calls this directly
Tested by
no test coverage detected