| /external/tensorflow/tensorflow/contrib/training/ |
| D | __init__.py | 48 from tensorflow.contrib.training.python.training.bucket_ops import *
49 from tensorflow.contrib.training.python.training.device_setter import *
50 from tensorflow.contrib.training.python.training.evaluation import checkpoints_iterator
51 from tensorflow.contrib.training.python.training.evaluation import evaluate_once
52 from tensorflow.contrib.training.python.training.evaluation import evaluate_repeatedly
53 from tensorflow.contrib.training.python.training.evaluation import get_or_create_eval_step
54 from tensorflow.contrib.training.python.training.evaluation import StopAfterNEvalsHook
55 from tensorflow.contrib.training.python.training.evaluation import SummaryAtEndHook
56 from tensorflow.contrib.training.python.training.evaluation import wait_for_new_checkpoint
57 from tensorflow.contrib.training.python.training.feeding_queue_runner import FeedingQueueRunner
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| D | BUILD | 20 "python/training/__init__.py",
21 "python/training/bucket_ops.py",
22 "python/training/device_setter.py",
23 "python/training/evaluation.py",
24 "python/training/feeding_queue_runner.py",
25 "python/training/hparam.py",
26 "python/training/resample.py",
27 "python/training/sampling_ops.py",
28 "python/training/sequence_queueing_state_saver.py",
29 "python/training/training.py",
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| /external/tensorflow/tensorflow/python/training/ |
| D | training.py | 30 from tensorflow.python.training.adadelta import AdadeltaOptimizer
31 from tensorflow.python.training.adagrad import AdagradOptimizer
32 from tensorflow.python.training.adagrad_da import AdagradDAOptimizer
33 from tensorflow.python.training.proximal_adagrad import ProximalAdagradOptimizer
34 from tensorflow.python.training.adam import AdamOptimizer
35 from tensorflow.python.training.ftrl import FtrlOptimizer
36 from tensorflow.python.training.momentum import MomentumOptimizer
37 from tensorflow.python.training.moving_averages import ExponentialMovingAverage
38 from tensorflow.python.training.optimizer import Optimizer
39 from tensorflow.python.training.rmsprop import RMSPropOptimizer
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| D | resnet50.py | 73 def call(self, input_tensor, training=False): argument
75 x = self.bn2a(x, training=training)
79 x = self.bn2b(x, training=training)
83 x = self.bn2c(x, training=training)
148 def call(self, input_tensor, training=False): argument
150 x = self.bn2a(x, training=training)
154 x = self.bn2b(x, training=training)
158 x = self.bn2c(x, training=training)
161 shortcut = self.bn_shortcut(shortcut, training=training)
275 def call(self, inputs, training=True): argument
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| /external/tensorflow/tensorflow/contrib/opt/ |
| D | __init__.py | 22 from tensorflow.contrib.opt.python.training.adam_gs_optimizer import *
23 from tensorflow.contrib.opt.python.training.adamax import *
24 from tensorflow.contrib.opt.python.training.addsign import *
25 from tensorflow.contrib.opt.python.training.agn_optimizer import *
26 from tensorflow.contrib.opt.python.training.drop_stale_gradient_optimizer import *
27 from tensorflow.contrib.opt.python.training.elastic_average_optimizer import *
28 from tensorflow.contrib.opt.python.training.external_optimizer import *
29 from tensorflow.contrib.opt.python.training.lars_optimizer import *
30 from tensorflow.contrib.opt.python.training.ggt import *
31 from tensorflow.contrib.opt.python.training.lazy_adam_optimizer import *
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| D | BUILD | 17 "python/training/adam_gs_optimizer.py",
18 "python/training/adamax.py",
19 "python/training/addsign.py",
20 "python/training/agn_optimizer.py",
21 "python/training/drop_stale_gradient_optimizer.py",
22 "python/training/elastic_average_optimizer.py",
23 "python/training/external_optimizer.py",
24 "python/training/ggt.py",
25 "python/training/lars_optimizer.py",
26 "python/training/lazy_adam_gs_optimizer.py",
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | blocks.py | 87 def call(self, h, training=True): argument
91 h = block(h, training=training)
94 def backward_grads(self, x, y, dy, training=True): argument
103 x, y, dy, training=True)
105 y, dy, grads = block.backward_grads(y, dy, training=training)
170 def call(self, x, training=True): argument
173 f_x2 = self.f(x2, training=training)
179 g_y1 = self.g(y1, training=training)
184 def backward_grads(self, y, dy, training=True): argument
191 gy1 = self.g(y1, training=training)
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| D | revnet.py | 96 def call(self, inputs, training=True): argument
100 if training:
103 h = self._init_block(inputs, training=training)
104 if training:
108 h = block(h, training=training)
109 if training:
112 logits = self._final_block(h, training=training)
114 return (logits, saved_hidden) if training else (logits, None)
132 def compute_gradients(self, saved_hidden, labels, training=True, l2_reg=True): argument
157 logits = self._final_block(x, training=training)
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| D | blocks_test.py | 67 y_tr, y_ev = block(x, training=True), block(x, training=False)
78 y_tr, y_ev = block(x, training=True), block(x, training=False)
104 y_tr, y_ev = block(x, training=True), block(x, training=False)
111 y_tr, y_ev = block(x, training=True), block(x, training=False)
147 y1, y2 = block((x1, x2), training=True)
151 x=(x1, x2), y=(y1, y2), dy=(dy1, dy2), training=True)
176 y1, y2 = block((x1, x2), training=True)
180 x=(x1, x2), y=(y1, y2), dy=(dy1, dy2), training=True)
210 y1, y2 = block((x1, x2), training=True)
218 x=(x1, x2), y=(y1, y2), dy=(dy1, dy2), training=True)
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/densenet/ |
| D | densenet.py | 69 def call(self, x, training=True): argument
70 output = self.batchnorm1(x, training=training)
74 output = self.batchnorm2(output, training=training)
77 output = self.dropout(output, training=training)
107 def call(self, x, training=True): argument
108 output = self.batchnorm(x, training=training)
141 def call(self, x, training=True): argument
143 output = self.blocks[i](x, training=training)
275 def call(self, x, training=True): argument
279 output = self.batchnorm1(output, training=training)
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| /external/tensorflow/tensorflow/contrib/checkpoint/python/ |
| D | BUILD | 15 "//tensorflow/python/training/tracking:data_structures",
25 "//tensorflow/python/training/tracking:base",
26 "//tensorflow/python/training/tracking:data_structures",
39 "//tensorflow/python/training/tracking:base",
40 "//tensorflow/python/training/tracking:util",
50 "//tensorflow/python/training/tracking:base",
67 "//tensorflow/python/training/tracking:util",
78 "//tensorflow/python:training",
79 "//tensorflow/python/training/tracking:base",
92 "//tensorflow/python/training/tracking:base",
[all …]
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| /external/tensorflow/tensorflow/contrib/checkpoint/ |
| D | __init__.py | 52 from tensorflow.python.training.checkpoint_management import CheckpointManager
53 from tensorflow.python.training.tracking.base import Trackable as CheckpointableBase
54 from tensorflow.python.training.tracking.data_structures import List
55 from tensorflow.python.training.tracking.data_structures import Mapping
56 from tensorflow.python.training.tracking.data_structures import NoDependency
57 from tensorflow.python.training.tracking.python_state import PythonState as PythonStateWrapper
58 from tensorflow.python.training.tracking.tracking import AutoTrackable as Checkpointable
59 from tensorflow.python.training.tracking.util import capture_dependencies
60 from tensorflow.python.training.tracking.util import list_objects
61 from tensorflow.python.training.tracking.util import object_metadata
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| /external/tensorflow/tensorflow/python/layers/ |
| D | normalization_test.py | 37 from tensorflow.python.training import gradient_descent
38 from tensorflow.python.training import saver as saver_lib
54 training = not freeze_mode
55 bn = bn_layer.apply(conv, training=training)
264 training = array_ops.placeholder(dtype='bool')
265 outputs = bn.apply(inputs, training=training)
291 training = array_ops.placeholder(dtype='bool')
292 outputs = bn.apply(inputs, training=training)
321 training = array_ops.placeholder(dtype='bool')
322 outputs = bn.apply(inputs, training=training)
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| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | training_test.py | 27 from tensorflow.contrib.training.python.training import training
38 from tensorflow.python.training import basic_session_run_hooks
39 from tensorflow.python.training import checkpoint_management
40 from tensorflow.python.training import gradient_descent
41 from tensorflow.python.training import monitored_session
42 from tensorflow.python.training import saver as saver_lib
62 clipped_gradients_to_variables = training.clip_gradient_norms(
75 clipped_gradients_to_variables = training.clip_gradient_norms_fn(3.0)(
101 train_op = training.create_train_op(loss, optimizer)
119 train_op = training.create_train_op(loss, optimizer)
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| /external/tensorflow/tensorflow/python/autograph/pyct/static_analysis/ |
| D | type_info_test.py | 32 from tensorflow.python.training import training
86 opt = training.GradientDescentOptimizer(0.1)
89 node = self._parse_and_analyze(test_fn, {'training': training})
92 self.assertEquals(training.GradientDescentOptimizer,
94 self.assertEquals((training.__name__, 'GradientDescentOptimizer'),
110 opt = training.GradientDescentOptimizer(0.1)
113 node = self._parse_and_analyze(test_fn, {'training': training})
115 self.assertEquals(training.GradientDescentOptimizer.minimize,
138 opt = training.GradientDescentOptimizer(0.1)
140 opt = training.GradientDescentOptimizer(0.01)
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| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| D | BUILD | 32 ":training",
38 name = "training",
55 "//tensorflow/python:training",
68 ":training",
86 ":training",
102 ":training",
117 ":training",
128 "//tensorflow/python:training",
143 ":training",
160 ":training",
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | noise.py | 64 def call(self, inputs, training=None): argument
70 return K.in_train_phase(noised, inputs, training=training)
112 def call(self, inputs, training=None): argument
120 return K.in_train_phase(noised, inputs, training=training)
173 def call(self, inputs, training=None): argument
196 return K.in_train_phase(dropped_inputs, inputs, training=training)
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| /external/tensorflow/tensorflow/contrib/distribute/python/ |
| D | checkpointing_test.py | 27 from tensorflow.python.keras.engine import training
30 from tensorflow.python.training import adam as adam_v1
31 from tensorflow.python.training import checkpoint_management
32 from tensorflow.python.training import training_util
33 from tensorflow.python.training.tracking import tracking
34 from tensorflow.python.training.tracking import util as trackable_utils
45 class Subclassed(training.Model):
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| /external/tensorflow/tensorflow/contrib/quantize/ |
| D | README.md | 1 # Quantization-aware training
3 Quantization-aware model training ensures that the forward pass matches precision
4 for both training and inference. There are two aspects to this:
6 * Operator fusion at inference time are accurately modeled at training time.
7 * Quantization effects at inference are modeled at training time.
23 during training. This allows a model trained with quantization in the loop to be
29 training graph. To create a fake quantized training graph:
35 # Call the training rewrite which rewrites the graph in-place with
36 # FakeQuantization nodes and folds batchnorm for training. It is
38 # with this training tool. When training from scratch, quant_delay
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| /external/tensorflow/tensorflow/python/saved_model/ |
| D | BUILD | 118 "//tensorflow/python:training",
179 "//tensorflow/python:training",
278 "//tensorflow/python/training/tracking:base",
312 "//tensorflow/python/training/saving:functional_saver",
313 "//tensorflow/python/training/tracking",
314 "//tensorflow/python/training/tracking:base",
315 "//tensorflow/python/training/tracking:graph_view",
316 "//tensorflow/python/training/tracking:object_identity",
317 "//tensorflow/python/training/tracking:util",
358 "//tensorflow/python/training/tracking",
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| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| D | util.py | 90 def call(self, x, training=None): argument
97 if training is None:
98 training = tf.keras.backend.learning_phase() # Could be a tensor.
99 result = smart_cond.smart_cond(training,
100 lambda: f(training=True),
101 lambda: f(training=False))
|
| /external/tensorflow/tensorflow/lite/g3doc/convert/ |
| D | quantization.md | 7 # Post-training: Quantizing models for CPU model size
21 # During training: Quantizing models for integer-only execution.
25 Currently, this requires training a model with
39 specify how those uint8 values map to the float input values used while training
45 For most users, we recommend using post-training quantization. We are working on
46 new tools for post-training and during training quantization that we hope will
|
| /external/tensorflow/tensorflow/contrib/gan/python/estimator/python/ |
| D | gan_estimator_test.py | 48 from tensorflow.python.training import input as input_lib
49 from tensorflow.python.training import learning_rate_decay
50 from tensorflow.python.training import sync_replicas_optimizer
51 from tensorflow.python.training import training
52 from tensorflow.python.training import training_util
142 cls._generator_optimizer = training.GradientDescentOptimizer(1.0)
143 cls._discriminator_optimizer = training.GradientDescentOptimizer(1.0)
178 training.GradientDescentOptimizer(learning_rate=1.0),
219 return training.GradientDescentOptimizer(lr)
221 gopt = make_opt if lr_decay else training.GradientDescentOptimizer(1.0)
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| D | tpu_gan_estimator_test.py | 46 from tensorflow.python.training import learning_rate_decay
47 from tensorflow.python.training import training
48 from tensorflow.python.training import training_util
102 training.GradientDescentOptimizer(1.0))
104 training.GradientDescentOptimizer(1.0))
160 return training.GradientDescentOptimizer(lr)
162 gopt = make_opt if lr_decay else training.GradientDescentOptimizer(1.0)
163 dopt = make_opt if lr_decay else training.GradientDescentOptimizer(1.0)
270 generator_optimizer=training.GradientDescentOptimizer(1.0),
271 discriminator_optimizer=training.GradientDescentOptimizer(1.0),
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| /external/tensorflow/tensorflow/python/estimator/ |
| D | training.py | 26 from tensorflow_estimator.python.estimator import training
30 training.__all__ = [s for s in dir(training) if not s.startswith('__')]
32 from tensorflow_estimator.python.estimator.training import *
|