chore: import upstream snapshot with attribution
This commit is contained in:
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# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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# @package _group_
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hydra:
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run:
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dir: .
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defaults:
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- task: null
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- model: null
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- criterion: cross_entropy
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- optimizer: null
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- lr_scheduler: fixed
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- bpe: null
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- tokenizer: null
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- scoring: null
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- generation: null
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- common_eval: null
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- eval_lm: null
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# @package _group_
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activation_fn: "relu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 512
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decoder_output_dim: 512
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decoder_input_dim: 512
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decoder_ffn_embed_dim: 4096
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decoder_layers: 12
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decoder_attention_heads: 16
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decoder_normalize_before: true
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no_decoder_final_norm: true
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "relu"
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dropout: 0.3
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attention_dropout: 0.1
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activation_dropout: 0.1
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relu_dropout: 0.1
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decoder_embed_dim: 1024
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decoder_output_dim: 1024
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decoder_input_dim: 1024
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decoder_ffn_embed_dim: 4096
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decoder_layers: 16
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decoder_attention_heads: 8
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decoder_normalize_before: true
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no_decoder_final_norm: true
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adaptive_softmax_cutoff: "20000,60000"
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adaptive_softmax_dropout: 0.2
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: true
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adaptive_input_factor: 4
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adaptive_input_cutoff: "20000,60000"
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tie_adaptive_weights: true
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tie_adaptive_proj: true
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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# @package _group_
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activation_fn: "relu"
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dropout: 0.1
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attention_dropout: 0.0
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 1024
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decoder_output_dim: 1024
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decoder_input_dim: 1024
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decoder_ffn_embed_dim: 4096
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decoder_layers: 12
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decoder_attention_heads: 16
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decoder_normalize_before: true
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no_decoder_final_norm: false
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "relu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 512
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decoder_output_dim: 512
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decoder_input_dim: 512
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decoder_ffn_embed_dim: 4096
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decoder_layers: 12
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decoder_attention_heads: 16
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decoder_normalize_before: true
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no_decoder_final_norm: true
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "gelu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 768
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decoder_output_dim: 768
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decoder_input_dim: 768
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decoder_ffn_embed_dim: 3072
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decoder_layers: 12
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decoder_attention_heads: 12
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decoder_normalize_before: true
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no_decoder_final_norm: false
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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# @package _group_
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activation_fn: "gelu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 1600
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decoder_output_dim: 1600
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decoder_input_dim: 1600
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decoder_ffn_embed_dim: 6400
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decoder_layers: 48
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decoder_attention_heads: 25
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decoder_normalize_before: true
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no_decoder_final_norm: false
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "gelu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 1280
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decoder_output_dim: 1280
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decoder_input_dim: 1280
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decoder_ffn_embed_dim: 5120
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decoder_layers: 36
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decoder_attention_heads: 20
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decoder_normalize_before: true
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no_decoder_final_norm: false
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "gelu"
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dropout: 0.1
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attention_dropout: 0.1
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activation_dropout: 0.0
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relu_dropout: 0.0
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decoder_embed_dim: 1024
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decoder_output_dim: 1024
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decoder_input_dim: 1024
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decoder_ffn_embed_dim: 4096
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decoder_layers: 24
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decoder_attention_heads: 16
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decoder_normalize_before: true
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no_decoder_final_norm: false
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adaptive_softmax_cutoff: null
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adaptive_softmax_dropout: 0
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: false
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adaptive_input_factor: 4
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adaptive_input_cutoff: null
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tie_adaptive_weights: false
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tie_adaptive_proj: false
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,36 @@
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# @package _group_
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activation_fn: "relu"
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dropout: 0.3
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attention_dropout: 0.1
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activation_dropout: 0.1
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relu_dropout: 0.1
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decoder_embed_dim: 1024
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decoder_output_dim: 1024
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decoder_input_dim: 1024
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decoder_ffn_embed_dim: 4096
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decoder_layers: 16
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decoder_attention_heads: 8
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decoder_normalize_before: true
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no_decoder_final_norm: true
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adaptive_softmax_cutoff: "20000,60000"
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adaptive_softmax_dropout: 0.2
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adaptive_softmax_factor: 4
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no_token_positional_embeddings: false
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share_decoder_input_output_embed: false
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character_embeddings: false
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character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
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character_embedding_dim: 4
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char_embedder_highway_layers: 2
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adaptive_input: true
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adaptive_input_factor: 4
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adaptive_input_cutoff: "20000,60000"
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tie_adaptive_weights: true
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tie_adaptive_proj: true
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decoder_learned_pos: false
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decoder_layerdrop: 0
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decoder_layers_to_keep: null
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layernorm_embedding: false
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no_scale_embedding: false
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quant_noise_pq: 0
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quant_noise_pq_block_size: 8
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quant_noise_scalar: 0
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@@ -0,0 +1,5 @@
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# @package _group_
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activation: gelu
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vq_type: gumbel
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vq_depth: 2
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combine_groups: true
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@@ -0,0 +1,8 @@
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# @package _group_
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quantize_targets: true
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final_dim: 256
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encoder_layerdrop: 0.05
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dropout_input: 0.1
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dropout_features: 0.1
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feature_grad_mult: 0.1
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@@ -0,0 +1,20 @@
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# @package _group_
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quantize_targets: true
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extractor_mode: layer_norm
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layer_norm_first: true
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final_dim: 768
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latent_temp: [2.0,0.1,0.999995]
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encoder_layerdrop: 0.0
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dropout_input: 0.0
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dropout_features: 0.0
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dropout: 0.0
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attention_dropout: 0.0
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conv_bias: true
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encoder_layers: 24
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encoder_embed_dim: 1024
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encoder_ffn_embed_dim: 4096
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encoder_attention_heads: 16
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feature_grad_mult: 1.0
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Reference in New Issue
Block a user