2e0f0929df4b01b269962a6423d6cb78b6d3da17,tensorlayer/layers/inputs.py,EmbeddingInput,__init__,#EmbeddingInput#Any#Any#Any#Any#Any#Any#,280

Before Change

        logging.info("EmbeddingInput %s: (%d, %d)" % (self.name, vocabulary_size, embedding_size))

        with tf.variable_scope(name):

            embeddings = tf.get_variable(
                name="embeddings", shape=(vocabulary_size, embedding_size), initializer=E_init,
                dtype=LayersConfig.tf_dtype, **self.E_init_args
            )

            self.outputs = tf.nn.embedding_lookup(embeddings, self.inputs)

        self._add_layers(self.outputs)
        self._add_params(embeddings)

After Change

        self.dtype = dtype
        logging.info("OneHotInput  %s: %s" % (self.name, str(inputs.shape.as_list())))

        if self.depth is None:
            raise RuntimeError(self.__class__.__name__ + ": depth == None the number of output units is undefined")

    def build(self, inputs):
        pass

    def forward(self, inputs):

Instances