Searched refs:batch_outs (Results 1 – 7 of 7) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | training_arrays.py | 304 batch_outs = f(actual_inputs)
338 if not isinstance(batch_outs, list):
339 batch_outs = [batch_outs]
342 batch_outs = distributed_training_utils._per_replica_aggregate_batch(
343 model._distribution_strategy, batch_outs, model, mode)
347 aggregator.create(batch_outs)
348 aggregator.aggregate(batch_outs)
351 batch_logs = cbks.make_logs(model, batch_logs, batch_outs, mode)
398 batch_outs = f(ins_batch)
399 if not isinstance(batch_outs, list):
[all …]
|
| D | training_v2_utils.py | 228 def _aggregate_predict_results(strategy, batch_outs, model): argument
233 if not isinstance(batch_outs, list):
234 batch_outs = [batch_outs]
248 batch_index, batch_outs = (batch_outs[:num_replicas],
249 batch_outs[num_replicas:])
262 nested_outs = batch_outs[i * num_replicas:i * num_replicas + num_replicas]
|
| D | training_v2.py | 128 batch_outs = execution_function(iterator)
160 data_batch_size = batch_outs['batch_size']
161 batch_outs = (batch_outs['total_loss'] + batch_outs['output_losses']
162 + batch_outs['metrics'])
167 batch_outs = training_v2_utils._aggregate_predict_results(
168 strategy, batch_outs, model)
171 aggregator.create(batch_outs)
174 aggregator.aggregate(batch_outs)
177 batch_outs,
180 cbks.make_logs(model, batch_logs, batch_outs, mode)
|
| D | training_utils.py | 86 def create(self, batch_outs): argument
95 def aggregate(self, batch_outs, batch_start=None, batch_end=None): argument
130 def create(self, batch_outs): argument
131 self.results = [0.] * len(batch_outs)
133 def aggregate(self, batch_outs, batch_start=None, batch_end=None): argument
136 self.results[0] += batch_outs[0]
138 self.results[0] += batch_outs[0] * (batch_end - batch_start)
140 self.results[1:] = batch_outs[1:]
318 def create(self, batch_outs): argument
323 batch_outs)
[all …]
|
| D | training_generator.py | 265 batch_outs = batch_function(*batch_data)
266 if not isinstance(batch_outs, list):
267 batch_outs = [batch_outs]
270 aggregator.create(batch_outs)
290 aggregator.aggregate(batch_outs)
293 batch_logs = cbks.make_logs(model, batch_logs, batch_outs, mode)
|
| D | training_distributed.py | 386 _, batch_outs = K.batch_get_value([test_op, output_tensors])
398 outs[i] += batch_outs[label]
401 outs[i] = batch_outs[label]
532 _, batch_outs = K.batch_get_value([predict_ops, output_tensors])
547 single_model_output = batch_outs[output_start_index:output_end_index]
550 batch_logs = cbks.make_logs(model, batch_logs, batch_outs, mode)
|
| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | distributed_training_utils.py | 1054 def _per_replica_aggregate_batch(strategy, batch_outs, model, mode): argument
1060 nested_outs = batch_outs[i * num_replicas:i * num_replicas + num_replicas]
1064 return batch_outs
|