def legacy_transformer_model_description_dynamic_axes(ntokens=28785): input_desc = Legacy_IODescription('input1', ['bptt', 'batch_size']) label_desc = Legacy_IODescription('label', ['bptt_x_batch_size']) loss_desc = Legacy_IODescription('loss', []) predictions_desc = Legacy_IODescription('predictions', ['bptt', 'batch_size', ntokens]) return Legacy_ModelDescription([input_desc, label_desc],[loss_desc, predictions_desc]),\ Legacy_IODescription('__learning_rate', [1])
def legacy_transformer_model_description(bptt=35, batch_size=20, ntokens=28785): input_desc = Legacy_IODescription('input1', [bptt, batch_size]) label_desc = Legacy_IODescription('label', [bptt * batch_size]) loss_desc = Legacy_IODescription('loss', []) predictions_desc = Legacy_IODescription('predictions', [bptt, batch_size, ntokens]) return Legacy_ModelDescription([input_desc, label_desc],[loss_desc, predictions_desc]),\ Legacy_IODescription('__learning_rate', [1])
def legacy_transformer_model_description_dynamic_axes(ntokens=28785): input_desc = Legacy_IODescription("input1", ["bptt", "batch_size"]) label_desc = Legacy_IODescription("label", ["bptt_x_batch_size"]) loss_desc = Legacy_IODescription("loss", []) predictions_desc = Legacy_IODescription("predictions", ["bptt", "batch_size", ntokens]) return ( Legacy_ModelDescription([input_desc, label_desc], [loss_desc, predictions_desc]), Legacy_IODescription("__learning_rate", [1]), )
def legacy_transformer_model_description(bptt=35, batch_size=20, ntokens=28785): input_desc = Legacy_IODescription("input1", [bptt, batch_size]) label_desc = Legacy_IODescription("label", [bptt * batch_size]) loss_desc = Legacy_IODescription("loss", []) predictions_desc = Legacy_IODescription("predictions", [bptt, batch_size, ntokens]) return ( Legacy_ModelDescription([input_desc, label_desc], [loss_desc, predictions_desc]), Legacy_IODescription("__learning_rate", [1]), )
def legacy_ort_trainer_learning_rate_description(): return Legacy_IODescription( "Learning_Rate", [ 1, ], torch.float32, )
def legacy_bert_model_description(): vocab_size = 30528 input_ids_desc = Legacy_IODescription('input_ids', ['batch', 'max_seq_len_in_batch']) segment_ids_desc = Legacy_IODescription('segment_ids', ['batch', 'max_seq_len_in_batch']) input_mask_desc = Legacy_IODescription('input_mask', ['batch', 'max_seq_len_in_batch']) masked_lm_labels_desc = Legacy_IODescription('masked_lm_labels', ['batch', 'max_seq_len_in_batch']) next_sentence_labels_desc = Legacy_IODescription('next_sentence_labels', ['batch', ]) loss_desc = Legacy_IODescription('loss', []) return Legacy_ModelDescription([input_ids_desc, segment_ids_desc, input_mask_desc, masked_lm_labels_desc, next_sentence_labels_desc], [loss_desc])
def legacy_bert_model_description(): vocab_size = 30528 input_ids_desc = Legacy_IODescription("input_ids", ["batch", "max_seq_len_in_batch"]) segment_ids_desc = Legacy_IODescription("segment_ids", ["batch", "max_seq_len_in_batch"]) input_mask_desc = Legacy_IODescription("input_mask", ["batch", "max_seq_len_in_batch"]) masked_lm_labels_desc = Legacy_IODescription("masked_lm_labels", ["batch", "max_seq_len_in_batch"]) next_sentence_labels_desc = Legacy_IODescription( "next_sentence_labels", [ "batch", ], ) loss_desc = Legacy_IODescription("loss", []) return Legacy_ModelDescription( [input_ids_desc, segment_ids_desc, input_mask_desc, masked_lm_labels_desc, next_sentence_labels_desc], [loss_desc], )