| /external/tensorflow/tensorflow/contrib/learn/python/learn/ |
| trainable.py | 37 max_steps=None):
64 behavior please set `max_steps` instead. If set, `max_steps` must be
70 max_steps: Number of total steps for which to train model. If `None`,
74 iterations. On the other hand, two calls to `fit(max_steps=100)` means
|
| graph_actions.py | 141 max_steps=None):
153 Training continues until `global_step_tensor` evaluates to `max_steps`, or, if
190 max_steps: Number of total steps for which to train model. If `None`,
192 On the other hand two calls of fit(max_steps=100) means, second call
204 ValueError: If both `steps` and `max_steps` are not `None`.
226 max_steps)
250 max_steps):
252 if (steps is not None) and (max_steps is not None):
253 raise ValueError('Can not provide both steps and max_steps.')
290 if max_steps is None
[all...] |
| graph_actions_test.py | 85 def begin(self, max_steps=None):
87 return super(_BaseMonitorWrapper, self).begin(max_steps)
300 max_steps=1)
326 max_steps=1)
341 max_steps=3)
365 max_steps=3)
387 max_steps=1)
559 max_steps=10)
572 max_steps=15)
|
| monitors.py | 97 def begin(self, max_steps=None):
103 max_steps: `int`, the maximum global step this training will run until.
110 self._max_steps = max_steps
171 `step` > `max_steps`.
334 step == self._max_steps): # Note: max_steps can be None here.
834 def begin(self, max_steps=None):
835 super(GraphDump, self).begin(max_steps=max_steps)
[all...] |
| monitors_test.py | 108 max_steps = num_epochs * num_steps_per_epoch - 1
110 max_steps = None
111 monitor.begin(max_steps=max_steps)
392 monitor.begin(max_steps=100)
477 monitor.begin(max_steps=100)
509 monitor.begin(max_steps=100)
756 def begin(self, max_steps):
[all...] |
| experiment.py | 386 max_steps=self._train_steps,
[all...] |
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| nonlinear_test.py | 46 classifier.fit(iris.data, iris.target, max_steps=200)
103 classifier.fit(iris.data, iris.target, max_steps=200)
115 classifier.fit(iris.data, iris.target, max_steps=200)
127 classifier.fit(iris.data, iris.target, max_steps=200)
|
| kmeans_test.py | 229 max_steps = 1
230 kmeans.fit(input_fn=self.input_fn(), max_steps=max_steps)
348 max_steps = 10 * self.num_points // self.batch_size
349 self.kmeans.fit(input_fn=self.input_fn(), max_steps=max_steps)
364 max_steps = 10 * self.num_points // self.batch_size
365 self.kmeans.fit(input_fn=self.input_fn(), max_steps=max_steps)
|
| estimator.py | 469 max_steps=None):
475 ValueError: If both `steps` and `max_steps` are not `None`.
477 if (steps is not None) and (max_steps is not None):
478 raise ValueError('Can not provide both steps and max_steps.')
481 SKCompat(self).fit(x, y, batch_size, steps, max_steps, monitors)
484 if max_steps is not None:
487 if max_steps <= start_step:
488 logging.info('Skipping training since max_steps has already saved.')
494 if steps is not None or max_steps is not None:
495 hooks.append(basic_session_run_hooks.StopAtStepHook(steps, max_steps))
[all...] |
| /external/tensorflow/tensorflow/python/debug/examples/ |
| examples_test.sh | 72 cat << EOF | ${DEBUG_MNIST_BIN} --debug --max_steps=1 --fake_data --ui_type=readline
|
| debug_mnist.py | 135 for i in range(FLAGS.max_steps):
146 "--max_steps",
|
| /external/tensorflow/tensorflow/python/estimator/ |
| training.py | 120 collections.namedtuple('TrainSpec', ['input_fn', 'max_steps', 'hooks'])):
127 def __new__(cls, input_fn, max_steps=None, hooks=None):
134 max_steps: Int. Positive number of total steps for which to train model.
151 # Validate max_steps.
152 if max_steps is not None and max_steps <= 0:
154 'Must specify max_steps > 0, given: {}'.format(max_steps))
160 cls, input_fn=input_fn, max_steps=max_steps, hooks=hooks
[all...] |
| training_test.py | 61 _INVALID_MAX_STEPS_MSG = 'Must specify max_steps > 0'
191 self.assertIsNone(spec.max_steps)
197 spec = training.TrainSpec(input_fn=lambda: 1, max_steps=2, hooks=hooks)
199 self.assertEqual(2, spec.max_steps)
208 training.TrainSpec(input_fn=lambda: 1, max_steps=0)
436 input_fn=lambda: 1, max_steps=2, hooks=[_FakeHook()])
454 max_steps=train_spec.max_steps,
466 input_fn=lambda: 1, max_steps=2, hooks=[_FakeHook()])
476 max_steps=train_spec.max_steps
[all...] |
| estimator.py | 290 max_steps=None,
316 set `max_steps` instead. If set, `max_steps` must be `None`.
317 max_steps: Number of total steps for which to train model. If `None`,
321 before `max_steps` steps.
323 iterations. On the other hand, two calls to `train(max_steps=100)` means
333 ValueError: If both `steps` and `max_steps` are not `None`.
334 ValueError: If either `steps` or `max_steps` is <= 0.
336 if (steps is not None) and (max_steps is not None):
337 raise ValueError('Can not provide both steps and max_steps.'
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| kmeans_test.py | 221 max_steps = 1
222 kmeans.train(input_fn=self.input_fn(), max_steps=max_steps)
340 max_steps = 10 * self.num_points // self.batch_size
341 self.kmeans.train(input_fn=self.input_fn(), max_steps=max_steps)
357 max_steps = 10 * self.num_points // self.batch_size
358 self.kmeans.train(input_fn=self.input_fn(), max_steps=max_steps)
|
| /external/tensorflow/tensorflow/contrib/factorization/examples/ |
| mnist.py | 23 mnist --fake_data=False --max_steps=2000
230 for step in xrange(FLAGS.max_steps):
253 if (step + 1) % 1000 == 0 or (step + 1) == FLAGS.max_steps:
297 '--max_steps',
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| structural_ensemble_test.py | 79 estimator.train(input_fn=train_input_fn, max_steps=1)
81 estimator.train(input_fn=train_input_fn, max_steps=3)
|
| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| fully_connected_feed.py | 163 for step in xrange(FLAGS.max_steps):
192 if (step + 1) % 1000 == 0 or (step + 1) == FLAGS.max_steps:
234 '--max_steps',
|
| mnist_with_summaries.py | 159 for i in range(FLAGS.max_steps):
194 parser.add_argument('--max_steps', type=int, default=1000,
|
| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| cifar10_train.py | 116 hooks=[tf.train.StopAtStepHook(last_step=FLAGS.max_steps),
148 '--max_steps',
|
| /external/tensorflow/tensorflow/tools/ci_build/builds/ |
| test_tutorials.sh | 184 --data_dir="${TUT_TEST_DATA_DIR}/cifar10" --max_steps=50 \
|
| /external/tensorflow/tensorflow/python/estimator/canned/ |
| dnn_linear_combined_test.py | 774 dnn_lc_classifier.train(input_fn=self._input_fn, max_steps=1)
791 warm_started_dnn_lc_classifier.train(input_fn=self._input_fn, max_steps=1)
813 dnn_lc_regressor.train(input_fn=self._input_fn, max_steps=1)
829 warm_started_dnn_lc_regressor.train(input_fn=self._input_fn, max_steps=1)
852 dnn_lc_classifier.train(input_fn=self._input_fn, max_steps=1)
[all...] |
| dnn_testing_utils.py | 757 dnn_classifier.train(input_fn=self._input_fn, max_steps=1)
769 warm_started_dnn_classifier.train(input_fn=self._input_fn, max_steps=1)
788 dnn_regressor.train(input_fn=self._input_fn, max_steps=1)
799 warm_started_dnn_regressor.train(input_fn=self._input_fn, max_steps=1)
819 dnn_classifier.train(input_fn=self._input_fn, max_steps=1)
[all...] |
| linear_testing_utils.py | [all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| test_utils.py | 160 max_steps=train_iterations,
|
