Loading fairseq/models/fconv.py +2 −3 Changes for fairseq/models/fconv.py: 2 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -10,7 +10,7 @@ import torch import torch.nn as nn import torch.nn.functional as F from fairseq import utils from fairseq import options, utils from fairseq.data.consts import LEFT_PAD_SOURCE, LEFT_PAD_TARGET from fairseq.modules import BeamableMM, GradMultiply, LearnedPositionalEmbedding, LinearizedConvolution, AdaptiveSoftmax Loading Loading @@ -139,8 +139,7 @@ class FConvLanguageModel(FairseqLanguageModel): max_positions=args.max_target_positions, share_embed=False, positional_embeddings=False, adaptive_softmax_cutoff=list( map(int, args.adaptive_softmax_cutoff.split(','))) if args.adaptive_softmax_cutoff else None, adaptive_softmax_cutoff=options.eval_str_list(args.adaptive_softmax_cutoff, type=int), normalization_constant=args.normalization_constant, ) return FConvLanguageModel(decoder) Loading fairseq/options.py +7 −5 Changes for fairseq/options.py: 7 added lines, 5 removed lines. Original line number Diff line number Diff line Loading @@ -34,13 +34,15 @@ def get_generation_parser(interactive=False): return parser def _eval_float_list(x): def eval_str_list(x, type=float): if x is None: return None if isinstance(x, str): x = eval(x) try: return list(x) return list(map(type, x)) except: return [float(x)] return [type(x)] def get_eval_lm_parser(): Loading Loading @@ -75,8 +77,8 @@ def parse_args_and_arch(parser, input_args=None): args = parser.parse_args(input_args) # Post-process args. args.lr = _eval_float_list(args.lr) args.update_freq = _eval_float_list(args.update_freq) args.lr = eval_str_list(args.lr, type=float) args.update_freq = eval_str_list(args.update_freq, type=int) if args.max_sentences_valid is None: args.max_sentences_valid = args.max_sentences Loading Loading
fairseq/models/fconv.py +2 −3 Changes for fairseq/models/fconv.py: 2 added lines, 3 removed lines. Original line number Diff line number Diff line Loading @@ -10,7 +10,7 @@ import torch import torch.nn as nn import torch.nn.functional as F from fairseq import utils from fairseq import options, utils from fairseq.data.consts import LEFT_PAD_SOURCE, LEFT_PAD_TARGET from fairseq.modules import BeamableMM, GradMultiply, LearnedPositionalEmbedding, LinearizedConvolution, AdaptiveSoftmax Loading Loading @@ -139,8 +139,7 @@ class FConvLanguageModel(FairseqLanguageModel): max_positions=args.max_target_positions, share_embed=False, positional_embeddings=False, adaptive_softmax_cutoff=list( map(int, args.adaptive_softmax_cutoff.split(','))) if args.adaptive_softmax_cutoff else None, adaptive_softmax_cutoff=options.eval_str_list(args.adaptive_softmax_cutoff, type=int), normalization_constant=args.normalization_constant, ) return FConvLanguageModel(decoder) Loading
fairseq/options.py +7 −5 Changes for fairseq/options.py: 7 added lines, 5 removed lines. Original line number Diff line number Diff line Loading @@ -34,13 +34,15 @@ def get_generation_parser(interactive=False): return parser def _eval_float_list(x): def eval_str_list(x, type=float): if x is None: return None if isinstance(x, str): x = eval(x) try: return list(x) return list(map(type, x)) except: return [float(x)] return [type(x)] def get_eval_lm_parser(): Loading Loading @@ -75,8 +77,8 @@ def parse_args_and_arch(parser, input_args=None): args = parser.parse_args(input_args) # Post-process args. args.lr = _eval_float_list(args.lr) args.update_freq = _eval_float_list(args.update_freq) args.lr = eval_str_list(args.lr, type=float) args.update_freq = eval_str_list(args.update_freq, type=int) if args.max_sentences_valid is None: args.max_sentences_valid = args.max_sentences Loading