| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | hparam_test.py | 28 hparams = hparam.HParams()
29 self.assertDictEqual({}, hparams.values())
30 hparams.parse('')
31 self.assertDictEqual({}, hparams.values())
33 hparams.parse('xyz=123')
36 hparams = hparam.HParams(foo=1)
37 self.assertTrue('foo' in hparams)
38 self.assertFalse('bar' in hparams)
41 hparams = hparam.HParams(aaa=1, b=2.0, c_c='relu6', d='/a/b=c/d')
44 hparams.values())
[all …]
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| /external/tensorflow/tensorflow/python/grappler/ |
| D | hierarchical_controller.py | 153 def __init__(self, hparams, item, cluster, controller_id=0): argument
164 self.hparams = hparams
166 if self.hparams.num_groups is None:
169 self.num_groups = self.hparams.num_groups
176 self.hparams.max_num_outputs * self.hparams.max_output_size)
179 seed=self.hparams.seed)
182 self.hparams.name,
187 1 + self.hparams.max_num_outputs * self.hparams.max_output_size +
188 self.hparams.adj_embed_dim, self.hparams.grouping_hidden_size
192 [self.hparams.grouping_hidden_size, self.num_groups])
[all …]
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| D | graph_placer.py | 36 hparams=None, argument
74 original_run_time = hparams.failing_signal
76 if hparams is None:
77 hparams = hierarchical_controller.hierarchical_controller_hparams()
79 hparams.num_children = 1
86 hparams, item, cluster)
104 run_time = hparams.failing_signal
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/ |
| D | l2hmc_test.py | 103 hparams = get_default_hparams()
106 x_dim=hparams.x_dim,
108 n_steps=hparams.n_steps,
109 eps=hparams.eps)
110 samples = tf.random_normal(shape=[hparams.n_samples, hparams.x_dim])
116 self.assertEqual(x_accept_prob.shape, (hparams.n_samples,))
122 x_dim=hparams.x_dim,
124 n_steps=hparams.n_steps,
125 eps=hparams.eps)
126 x = tf.placeholder(tf.float32, shape=[None, hparams.x_dim])
[all …]
|
| /external/brotli/c/enc/ |
| D | quality.h | 122 BrotliHasherParams* hparams) { in ChooseHasher() argument
124 hparams->type = 10; in ChooseHasher()
126 hparams->type = 54; in ChooseHasher()
128 hparams->type = params->quality; in ChooseHasher()
130 hparams->type = params->quality < 7 ? 40 : params->quality < 9 ? 41 : 42; in ChooseHasher()
132 hparams->type = 6; in ChooseHasher()
133 hparams->block_bits = params->quality - 1; in ChooseHasher()
134 hparams->bucket_bits = 15; in ChooseHasher()
135 hparams->hash_len = 5; in ChooseHasher()
136 hparams->num_last_distances_to_check = in ChooseHasher()
[all …]
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| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| D | random_forest_test.py | 65 hparams = tensor_forest.ForestHParams(
72 classifier = random_forest.TensorForestEstimator(hparams.fill())
88 hparams = tensor_forest.ForestHParams(
96 regressor = random_forest.TensorForestEstimator(hparams.fill())
109 hparams = tensor_forest.ForestHParams(
117 hparams.fill(), keys_column='keys', include_all_in_serving=True)
148 hparams = tensor_forest.ForestHParams(
156 hparams.fill(),
174 hparams = tensor_forest.ForestHParams(
182 est = random_forest.CoreTensorForestEstimator(hparams.fill(), head=head_fn)
[all …]
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| /external/tensorflow/tensorflow/contrib/tensor_forest/python/ |
| D | tensor_forest_test.py | 35 hparams = tensor_forest.ForestHParams(
41 self.assertEquals(2, hparams.num_classes)
42 self.assertEquals(3, hparams.num_output_columns)
43 self.assertEquals(10, hparams.num_splits_to_consider)
45 self.assertEquals(1, hparams.valid_leaf_threshold)
46 self.assertEquals(0, hparams.base_random_seed)
49 hparams = tensor_forest.ForestHParams(
55 self.assertEquals(31, hparams.num_splits_to_consider)
58 hparams = tensor_forest.ForestHParams(
65 self.assertEquals("1000000", hparams.num_splits_to_consider)
[all …]
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| D | learn_runner.py | 71 def wrapped_experiment_fn(run_config, hparams): argument
79 if hparams is not None and not isinstance(hparams, hparam_lib.HParams):
81 if require_hparams and hparams is None:
85 experiment = experiment_fn(run_config, hparams)
110 hparams=None): argument
208 experiment = wrapped_experiment_fn(run_config=run_config, hparams=hparams)
212 if hparams is not None:
|
| D | learn_runner_test.py | 116 def build_experiment_for_run_config(run_config, hparams): argument
117 if hparams is not None and hparams != _HPARAMS:
180 hparams = _HPARAMS
184 build_experiment, _MODIR_DIR, schedule="simple_task", hparams=hparams)
224 hparams=_HPARAMS))
261 hparams=["hparams"])
271 def _experiment_fn(run_config, hparams): argument
272 del run_config, hparams # unused.
298 def _experiment_fn(run_config, hparams): argument
299 del run_config, hparams # unused.
[all …]
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/workshop/ |
| D | 3_inspecting.ipynb | 165 "# Create hparams and the model\n",
169 …"hparams = trainer_lib.create_hparams(hparams_set, data_dir=data_dir, problem_name=\"translate_end…
174 "translate_model = registry.model(model_name)(hparams, tf.estimator.ModeKeys.EVAL)"
185 "INFO:tensorflow:Setting hparams.layer_prepostprocess_dropout to 0.0\n",
186 "INFO:tensorflow:Setting hparams.symbol_dropout to 0.0\n",
187 "INFO:tensorflow:Setting hparams.attention_dropout to 0.0\n",
188 "INFO:tensorflow:Setting hparams.dropout to 0.0\n",
189 "INFO:tensorflow:Setting hparams.relu_dropout to 0.0\n"
|
| /external/tensorflow/tensorflow/contrib/model_pruning/python/ |
| D | pruning_test.py | 116 def _blockMasking(self, hparams, weights, expected_mask): argument
120 test_spec = ",".join(hparams)
|
| /external/tensorflow/ |
| D | RELEASE.md | 444 * Allow the use of '.' in variables (e.g. "hparams.parse('a.b=1.0')"),
449 object (e.g. "hparams.add_hparam(name='a.b', value=0.0)").
|