efe5155ad7184f04510a5cc53b6327993ce77cd4,texar/modules/decoders/transformer_decoders.py,TransformerDecoder,default_hparams,#,83

Before Change

            the sentence is completed.
        The meaning of other parameters are similar to TransformerEncoder
        
        return {
            "sampling_method": "argmax",
            "initializer": None,
            "multiply_embedding_mode": "sqrt_depth",
            "position_embedder_hparams": None,
            "share_embed_and_transform": True,
            "transform_with_bias": True,
            "num_heads":8,
            "num_blocks":6,
            "maximum_decode_length":10,
            "embedding_dropout":0.1,
            "attention_dropout":0.1,
            "residual_dropout":0.1,
            "poswise_feedforward":None,
            "num_units":512,
            "eos_idx": 2,
            "bos_idx": 1,
            "beam_width":1,
            "alpha":0,
            "name":"transformer_decoder",
        }

    def _prepare_tokens_to_embeds(self, tokens):
         a callable function to transform tokens into embeddings.
        token_emb = tf.nn.embedding_lookup(self._embedding, tokens)

After Change

            the sentence is completed.
        The meaning of other parameters are similar to TransformerEncoder
        
        return {
            "initializer": None,
            "position_embedder_hparams": None,
            "share_embed_and_transform": True,
            "transform_with_bias": True,
            "num_heads":8,
            "num_blocks":6,
            "maximum_decode_length":256,
            "embedding_dropout":0.1,
            "attention_dropout":0.1,
            "residual_dropout":0.1,
            "poswise_feedforward": {
		"name":"ffn",
		"layers":[
		    {
			"type":"Dense",
			"kwargs": {
			    "name":"conv1",
			    "units":2048,
			    "activation":"relu",
			    "use_bias":True,
			}
		    },
		    {
			"type":"Dropout",
			"kwargs": {
			    "rate": 0.1,
			}
		    },
		    {
			"type":"Dense",
			"kwargs": {
			    "name":"conv2",
			    "units":512,
			    "use_bias":True,
			    }
		    }
		],
            },
            "dim":512,
            "eos_idx": 2,
            "bos_idx": 1,
            "beam_width":1,
            "alpha":0,
            "name":"transformer_decoder",
        }

    def _prepare_tokens_to_embeds(self, tokens):
         a callable function to transform tokens into embeddings.
        token_emb = tf.nn.embedding_lookup(self._embedding, tokens)

Instances