Python model.SequenceLossParams() Examples
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code examples of model.SequenceLossParams().
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Example #1
Source File: common_flags.py From DOTA_models with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #2
Source File: common_flags.py From yolo_v2 with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #3
Source File: common_flags.py From Gun-Detector with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #4
Source File: common_flags.py From hands-detection with MIT License | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #5
Source File: common_flags.py From object_detection_kitti with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #6
Source File: common_flags.py From object_detection_with_tensorflow with MIT License | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #7
Source File: common_flags.py From g-tensorflow-models with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #8
Source File: common_flags.py From models with Apache License 2.0 | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }
Example #9
Source File: common_flags.py From multilabel-image-classification-tensorflow with MIT License | 6 votes |
def create_mparams(): return { 'conv_tower_fn': model.ConvTowerParams(final_endpoint=FLAGS.final_endpoint), 'sequence_logit_fn': model.SequenceLogitsParams( use_attention=FLAGS.use_attention, use_autoregression=FLAGS.use_autoregression, num_lstm_units=FLAGS.num_lstm_units, weight_decay=FLAGS.weight_decay, lstm_state_clip_value=FLAGS.lstm_state_clip_value), 'sequence_loss_fn': model.SequenceLossParams( label_smoothing=FLAGS.label_smoothing, ignore_nulls=FLAGS.ignore_nulls, average_across_timesteps=FLAGS.average_across_timesteps) }