| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| D | learning_test.py | 31 from tensorflow.contrib.slim.python.slim import learning
70 [gradients_to_variables] = learning.clip_gradient_norms(
85 [gradients_to_variables] = learning.clip_gradient_norms(
104 gradients_to_variables = learning.clip_gradient_norms(
131 learning.multiply_gradients(grad_to_var, gradient_multipliers)
138 learning.multiply_gradients([grad_to_var], {})
145 learning.multiply_gradients([grad_to_var], 3)
153 learning.multiply_gradients(grad_to_var, gradient_multipliers)
161 [grad_to_var] = learning.multiply_gradients([grad_to_var],
183 [grad_to_var] = learning.multiply_gradients([grad_to_var],
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| /external/tensorflow/tensorflow/examples/udacity/ |
| D | 6_lstm.ipynb | 675 " 'Average loss at step %d: %f learning rate: %f' % (step, mean_loss, lr))\n",
708 "Average loss at step 0 : 3.29904174805 learning rate: 10.0\n",
718 "Average loss at step 100 : 2.59553678274 learning rate: 10.0\n",
721 "Average loss at step 200 : 2.24747137785 learning rate: 10.0\n",
724 "Average loss at step 300 : 2.09438110709 learning rate: 10.0\n",
727 "Average loss at step 400 : 1.99440989017 learning rate: 10.0\n",
730 "Average loss at step 500 : 1.9320810616 learning rate: 10.0\n",
733 "Average loss at step 600 : 1.90935629249 learning rate: 10.0\n",
736 "Average loss at step 700 : 1.85583009005 learning rate: 10.0\n",
739 "Average loss at step 800 : 1.82152368546 learning rate: 10.0\n",
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| /external/u-boot/doc/ |
| D | README.t1040-l2switch | 9 - Dynamic learning of MAC addresses and aging
11 - Independent and shared VLAN learning (IVL, SVL)
29 - MAC learning
32 - Private/Shared VLAN learning
39 ethsw [port <port_no>] learning { [help] | show | auto | disable } - enable/disable/show learning c…
47 ethsw vlan fdb { [help] | show | shared | private } - make VLAN learning shared or private
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| /external/tensorflow/tensorflow/core/protobuf/tpu/ |
| D | optimization_parameters.proto | 12 // Dynamic learning rate specification in the TPUEmbeddingConfiguration. The
13 // actual learning rates are provided as a scalar input list to the
17 // For tables where learning rates are dynamically computed and communicated
18 // to the TPU embedding program, a tag must be specified for the learning
24 // learning rate, and specifies exactly one tag if it uses dynamic learning
32 // the same dynamic learning rate, for example, their dynamic learning rate
38 // communicate dynamic learning rates to the TPU embedding program.
40 // equal to the number of unique tags. The learning rate associated with a
46 // Source of learning rate to use.
79 // learning rate feature instead, setting the learning rate to:
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| /external/tensorflow/tensorflow/contrib/boosted_trees/proto/ |
| D | learner.proto | 31 // LearningRateConfig describes all supported learning rate tuners.
40 // Config for a fixed learning rate.
45 // Config for a tuned learning rate.
47 // Max learning rate. Must be strictly positive.
50 // Number of learning rate values to consider between [0, max_learning_rate).
138 // Learning rate. By default we use fixed learning rate of 0.1.
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SendTPUEmbeddingGradients.pbtxt | 18 A TensorList of float32 scalars, one for each dynamic learning
21 Multiple tables can share the same dynamic learning rate tag as specified
22 in the configuration. If the learning rates for all tables are constant,
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| D | api_def_ResourceApplyProximalGradientDescent.pbtxt | 40 summary: "Update \'*var\' as FOBOS algorithm with fixed learning rate."
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| D | api_def_ApplyProximalGradientDescent.pbtxt | 46 summary: "Update \'*var\' as FOBOS algorithm with fixed learning rate."
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| /external/iproute2/ip/ |
| D | iplink_vxlan.c | 82 __u8 learning = 1; in vxlan_parse_opt() local
246 learning = 0; in vxlan_parse_opt()
249 learning = 1; in vxlan_parse_opt()
316 learning = 0; in vxlan_parse_opt()
385 addattr8(n, 1024, IFLA_VXLAN_LEARNING, learning); in vxlan_parse_opt()
500 __u8 learning = rta_getattr_u8(tb[IFLA_VXLAN_LEARNING]); in vxlan_print_opt() local
502 print_bool(PRINT_JSON, "learning", NULL, learning); in vxlan_print_opt()
503 if (!learning) in vxlan_print_opt()
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| /external/tensorflow/tensorflow/contrib/slim/ |
| D | BUILD | 49 name = "learning",
50 srcs = ["python/slim/learning.py"],
76 ":learning",
137 ":learning",
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| D | README.md | 58 * [learning](https://www.tensorflow.org/code/tensorflow/contrib/slim/python/slim/learning.py):
118 trained or fine-tuned during learning and are loaded
121 are all other variables that are used during learning or evaluation but are not
123 a variable using during learning and evaluation but it is not actually part of
429 learning models, require the use of multiple loss functions simultaneously. In
517 [learning.py](https://www.tensorflow.org/code/tensorflow/contrib/slim/python/slim/learning.py).
522 call `slim.learning.create_train_op` and `slim.learning.train` to perform the
536 train_op = slim.learning.create_train_op(total_loss, optimizer)
539 slim.learning.train(
547 In this example, `slim.learning.train` is provided with the `train_op` which is
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| /external/tensorflow/tensorflow/contrib/model_pruning/python/ |
| D | learning.py | 58 train_step = _slim.learning.train_step
165 total_loss, _ = _slim.learning.train(
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| /external/tensorflow/tensorflow/contrib/model_pruning/ |
| D | BUILD | 57 name = "learning",
58 srcs = ["python/learning.py"],
187 ":learning",
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| D | __init__.py | 27 from tensorflow.contrib.model_pruning.python.learning import train
|
| /external/tensorflow/tensorflow/contrib/tpu/ |
| D | BUILD | 18 "//learning/brain:__subpackages__",
19 "//learning/deepmind:__subpackages__",
114 "//learning/brain:__subpackages__",
|
| /external/tensorflow/tensorflow/lite/g3doc/guide/ |
| D | index.md | 5 devices. It enables on-device machine learning inference with low latency and a
71 We believe the next wave of machine learning applications will have significant
146 models. This technique is called transfer learning, which starts with a model
148 similar problem. Deep learning from scratch can take days, but transfer learning
196 Future plans include using specialized machine learning hardware to get the best
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| /external/iproute2/bridge/ |
| D | link.c | 276 __s8 learning = -1; in brlink_modify() local
313 if (!on_off("learning", &learning, *argv)) in brlink_modify()
402 if (learning >= 0) in brlink_modify()
403 addattr8(&req.n, sizeof(req), IFLA_BRPORT_LEARNING, learning); in brlink_modify()
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| /external/tensorflow/tensorflow/python/ |
| D | BUILD | 351 "//learning/deepmind/courier:__subpackages__",
435 "//learning/deepmind/courier:__subpackages__",
1346 "//learning/brain/python/ops:__pkg__",
1737 "//learning/brain/python/ops:__pkg__",
1748 "//learning/brain/python/ops:__pkg__",
1781 "//learning/brain/python/ops:__pkg__",
1795 visibility = ["//learning/brain/python/ops:__pkg__"],
1825 "//learning/brain/python/ops:__pkg__",
1841 "//learning/brain/python/ops:__pkg__",
1849 "//learning/brain/python/ops:__pkg__",
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| /external/tensorflow/tensorflow/tools/ci_build/gpu_build/ |
| D | BUILD | 3 # learning applications.
|
| /external/tensorflow/tensorflow/lite/ |
| D | README.md | 4 devices. It enables low-latency inference of on-device machine learning models
|
| /external/tensorflow/tensorflow/c/ |
| D | generate-pc.sh | 70 Description: Library for computation using data flow graphs for scalable machine learning
|
| /external/tensorflow/tensorflow/lite/c/ |
| D | BUILD | 15 "//learning/brain/mobile/kernel_test:__subpackages__",
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| /external/tensorflow/tensorflow/examples/learn/ |
| D | README.md | 4 create, train, and use deep learning models easily.
|
| /external/linux-kselftest/tools/testing/selftests/net/forwarding/ |
| D | bridge_vlan_unaware.sh | 87 learning() function
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| D | bridge_vlan_aware.sh | 89 learning() function
|