/external/tensorflow/tensorflow/python/keras/benchmarks/keras_examples_benchmarks/ |
D | mnist_conv_custom_training_benchmark_test.py | 60 def compute_loss(self, targets, predictions, loss_fn, batch_size): argument 62 per_example_loss = loss_fn(targets, predictions) 67 def train_step(self, inputs, model, loss_fn, optimizer, batch_size): argument 83 loss = self.compute_loss(train_y, predictions, loss_fn, batch_size) 89 def distributed_train_step(self, batch_dataset, model, loss_fn, optimizer, argument 110 loss_fn, 120 loss_fn, argument 160 loss_fn, optimizer, 164 total_loss += self.train_step(batch_dataset, model, loss_fn, 176 loss_fn, argument [all …]
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/external/tensorflow/tensorflow/python/distribute/ |
D | single_loss_example.py | 42 def loss_fn(ctx, x): function 48 dataset_fn, loss_fn, optimizer, distribution, iterations_per_step) 68 def loss_fn(): function 73 return optimizer.minimize(loss_fn, lambda: layer.trainable_variables) 75 return optimizer.minimize(loss_fn) 77 return optimizer.minimize(loss_fn()) 105 def loss_fn(): function 116 return optimizer.minimize(loss_fn, lambda: layer.trainable_variables) 119 return optimizer.minimize(loss_fn)
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D | step_fn.py | 88 def __init__(self, dataset_fn, loss_fn, optimizer, distribution, argument 91 self._loss_fn = loss_fn
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D | collective_all_reduce_strategy_test.py | 127 def loss_fn(x): function 135 loss = loss_fn(x)
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D | parameter_server_strategy_test.py | 456 def loss_fn(x): function 464 loss = loss_fn(x)
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/external/tensorflow/tensorflow/python/keras/distribute/ |
D | test_example.py | 45 def loss_fn(): function 50 return optimizer.minimize(loss_fn, lambda: layer.trainable_variables) 52 return optimizer.minimize(loss_fn) 54 return optimizer.minimize(loss_fn()) 82 def loss_fn(): function 93 return optimizer.minimize(loss_fn, lambda: layer.trainable_variables) 96 return optimizer.minimize(loss_fn)
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D | minimize_loss_test.py | 344 def loss_fn(): function 356 return optimizer.minimize(loss_fn, [w]) 359 return optimizer.minimize(loss_fn) 361 return optimizer.minimize(loss_fn()) 439 def loss_fn(): function 445 loss_fn, lambda: layer.trainable_variables) 447 train_op = optimizer.minimize(loss_fn) 448 loss = loss_fn()
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D | keras_optimizer_v2_test.py | 64 def loss_fn(): function 68 train_op = optimizer.minimize(loss_fn, var_list=[var])
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D | mirrored_strategy_test.py | 74 def loss_fn(ctx): function 78 gradients_fn = backprop.implicit_grad(loss_fn)
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/external/tensorflow/tensorflow/python/keras/engine/ |
D | training_eager_v1.py | 36 def _eager_loss_fn(outputs, targets, loss_fn, output_name): argument 38 loss = loss_fn(targets, outputs) 149 loss_fn for loss_fn in model.loss_functions if loss_fn is not None 161 for i, loss_fn in enumerate(loss_fns): 178 if hasattr(loss_fn, 'reduction'): 179 per_sample_losses = loss_fn.call(targets[i], outs[i]) 184 loss_reduction = loss_fn.reduction 200 output_loss = loss_fn(targets[i], outs[i], sample_weight=weights)
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D | training_v1.py | 1591 loss_fn = endpoint.loss_fn 1609 if hasattr(loss_fn, 'reduction'): 1610 per_sample_losses = loss_fn.call(y_true, y_pred) 1615 loss_reduction = loss_fn.reduction 1631 output_loss = loss_fn(y_true, y_pred, sample_weight=sample_weight) 2719 e.loss_fn 2889 loss_fn, argument 2915 self._loss_fn = loss_fn 2935 def loss_fn(self): member in _TrainingEndpoint 2991 self.loss_fn, K.dtype(self.output)) [all …]
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D | training_utils_v1.py | 912 metric, output_shape=output_shapes[i], loss_fn=loss_fns[i]) 1134 def get_metric_function(metric, output_shape=None, loss_fn=None): argument 1150 isinstance(loss_fn, losses.SparseCategoricalCrossentropy) or 1151 (isinstance(loss_fn, losses.LossFunctionWrapper) and 1152 loss_fn.fn == losses.sparse_categorical_crossentropy)) 1155 isinstance(loss_fn, losses.BinaryCrossentropy) or 1156 (isinstance(loss_fn, losses.LossFunctionWrapper) and 1157 loss_fn.fn == losses.binary_crossentropy)) 1221 loss_fn = losses.get(loss) 1227 loss_fn, [all …]
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/external/tensorflow/tensorflow/python/keras/saving/saved_model/ |
D | save_impl.py | 105 for loss_fn in all_losses: 106 if loss_fn in keras_loss_cache: 107 wrapped_loss_functions.append(keras_loss_cache[loss_fn]) 109 wrapped_loss = _wrap_unconditional_loss(loss_fn, len(keras_loss_cache)) 110 keras_loss_cache[loss_fn] = wrapped_loss 611 def _wrap_unconditional_loss(loss_fn, index): argument 614 fn = loss_fn.args[0] if isinstance(loss_fn, functools.partial) else loss_fn
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/external/tensorflow/tensorflow/python/keras/mixed_precision/ |
D | keras_test.py | 579 def loss_fn(y_true, y_pred): function 593 loss=loss_fn, 611 {'MultiplyLayer': mp_test_util.MultiplyLayer, 'loss_fn': loss_fn}): 681 def loss_fn(y_true, y_pred): function 690 loss=loss_fn, 759 def loss_fn(y_true, y_pred): function 769 loss=loss_fn, 862 def loss_fn(y_true, y_pred): function 868 loss=loss_fn,
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/external/tensorflow/tensorflow/tools/api/golden/v2/ |
D | tensorflow.estimator.-multi-class-head.pbtxt | 20 …lasses\', \'weight_column\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'name\'], var…
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D | tensorflow.estimator.-regression-head.pbtxt | 20 …argspec: "args=[\'self\', \'label_dimension\', \'weight_column\', \'loss_reduction\', \'loss_fn\',…
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D | tensorflow.estimator.-multi-label-head.pbtxt | 20 …ht_column\', \'thresholds\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'classes_for_…
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D | tensorflow.estimator.-binary-class-head.pbtxt | 20 …ht_column\', \'thresholds\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'name\'], var…
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.estimator.-binary-class-head.pbtxt | 20 …ht_column\', \'thresholds\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'name\'], var…
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D | tensorflow.estimator.-multi-class-head.pbtxt | 20 …lasses\', \'weight_column\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'name\'], var…
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D | tensorflow.estimator.-multi-label-head.pbtxt | 20 …ht_column\', \'thresholds\', \'label_vocabulary\', \'loss_reduction\', \'loss_fn\', \'classes_for_…
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D | tensorflow.estimator.-regression-head.pbtxt | 20 …argspec: "args=[\'self\', \'label_dimension\', \'weight_column\', \'loss_reduction\', \'loss_fn\',…
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/external/tensorflow/tensorflow/python/keras/ |
D | losses.py | 1224 def _ragged_tensor_apply_loss(loss_fn, y_true, y_pred): argument 1260 lambda: loss_fn(*_convert_to_dense(inputs)), lambda: loss_fn(*inputs)) 1262 return loss_fn(*inputs)
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D | losses_test.py | 191 loss_fn = losses.get('mse') 192 mse_obj = losses.LossFunctionWrapper(loss_fn, name=loss_fn.__name__) 212 def loss_fn(y_true, y_pred): function 219 mse_obj = losses.LossFunctionWrapper(loss_fn) 1793 def loss_fn(y_true, y_pred): function 1797 loss = loss_fn(y_true, y_pred)
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/external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
D | learning_rate_schedule_test.py | 128 def loss_fn(): function 137 loss = loss_fn()
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