| /cts/tests/tests/jvmti/attaching/jni/ |
| agent.c | 38 #define EVAL(A,B) CONCAT(A,B)
39 #define NAME(BASE) EVAL(BASE,AGENT_NR)
|
| /external/toybox/tests/ |
| sh.test | 16 EVAL="bash -c" testing "$2" "$1 printf %s $2" "$3" "$4" "$5"
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/ |
| head_test.py | 43 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL,
98 features=features, labels=None, mode=estimator_lib.ModeKeys.EVAL)
140 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
150 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
160 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
174 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
188 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
202 for mode in [estimator_lib.ModeKeys.TRAIN, estimator_lib.ModeKeys.EVAL]:
|
| head.py | 112 self.model, features, estimator_lib.ModeKeys.EVAL)
125 mode=estimator_lib.ModeKeys.EVAL,
144 self.model, features, estimator_lib.ModeKeys.EVAL)
217 mode == estimator_lib.ModeKeys.EVAL):
229 elif mode == estimator_lib.ModeKeys.EVAL:
|
| ar_model_test.py | 252 self.assertAllEqual(predicted_values["mean"].eval().shape,
272 raw_features, mode=estimator_lib.ModeKeys.EVAL)
275 chunked_features, mode=estimator_lib.ModeKeys.EVAL)
318 raw_features, mode=estimator_lib.ModeKeys.EVAL)
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| model_fn.py | 48 * `EVAL`: evaluation mode.
53 EVAL = 'eval'
58 if key not in (cls.TRAIN, cls.EVAL, cls.INFER):
142 if mode in (ModeKeys.TRAIN, ModeKeys.EVAL):
154 if mode == ModeKeys.INFER or mode == ModeKeys.EVAL:
277 elif self.mode == ModeKeys.EVAL:
278 core_mode = core_model_fn_lib.ModeKeys.EVAL
|
| logistic_regressor.py | 50 if mode == model_fn_lib.ModeKeys.EVAL:
|
| estimator_input_test.py | 111 assert mode in (model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
125 assert mode in (model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
140 assert mode in (model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
|
| /external/tensorflow/tensorflow/python/estimator/ |
| model_fn_test.py | 198 """Tests EstimatorSpec in eval mode."""
205 mode=model_fn.ModeKeys.EVAL,
216 mode=model_fn.ModeKeys.EVAL,
234 mode=model_fn.ModeKeys.EVAL,
243 mode=model_fn.ModeKeys.EVAL,
254 mode=model_fn.ModeKeys.EVAL,
263 mode=model_fn.ModeKeys.EVAL,
271 mode=model_fn.ModeKeys.EVAL,
279 mode=model_fn.ModeKeys.EVAL,
292 mode=model_fn.ModeKeys.EVAL,
[all...] |
| model_fn.py | 44 * `EVAL`: evaluation mode.
49 EVAL = 'eval'
86 * For `mode == ModeKeys.EVAL`: required field is `loss`.
91 ignored in eval and infer modes. Example:
111 mode == tf.estimator.ModeKeys.EVAL):
180 if mode in (ModeKeys.TRAIN, ModeKeys.EVAL):
|
| /external/toybox/scripts/ |
| runtest.sh | 97 echo -ne "$5" | ${EVAL:-eval} "$2" > actual
112 echo "echo -ne '$5' |$EVAL $2"
|
| /external/tensorflow/tensorflow/contrib/gan/python/estimator/python/ |
| head_impl.py | 172 elif mode == model_fn_lib.ModeKeys.EVAL:
177 mode=model_fn_lib.ModeKeys.EVAL,
|
| head_test.py | 78 self._test_modes_helper(model_fn_lib.ModeKeys.EVAL)
|
| gan_estimator_impl.py | 28 from tensorflow.contrib.gan.python.eval.python import summaries as tfgan_summaries
128 in (ex TRAIN, EVAL, PREDICT). This is useful for things like batch
219 elif mode == model_fn_lib.ModeKeys.EVAL:
275 model_fn_lib.ModeKeys.EVAL)
|
| gan_estimator_test.py | 109 elif mode == model_fn_lib.ModeKeys.EVAL:
161 elif mode == model_fn_lib.ModeKeys.EVAL:
172 self._test_logits_helper(model_fn_lib.ModeKeys.EVAL)
|
| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| logit_fns_test.py | 41 dummy_logit_fn, features, model_fn.ModeKeys.EVAL, 'fake_params',
44 self.assertAllClose([[4., 5.]], logit_fn_result.eval())
59 self.assertAllClose([[2., 3.]], logit_fn_result['head1'].eval())
60 self.assertAllClose([[4., 5.]], logit_fn_result['head2'].eval())
|
| head_test.py | 52 scaffold.ready_for_local_init_op.eval()
54 scaffold.ready_op.eval()
268 """Tests head.create_loss for eval mode."""
280 mode=model_fn.ModeKeys.EVAL,
286 actual_training_loss.eval())
289 """Tests head.create_loss for eval mode and large logits."""
304 mode=model_fn.ModeKeys.EVAL,
310 expected_training_loss, actual_training_loss.eval(), atol=1e-4)
313 """Tests head.create_loss for eval mode when labels has the wrong shape."""
321 mode=model_fn.ModeKeys.EVAL,
[all...] |
| /external/tensorflow/tensorflow/python/estimator/canned/ |
| head_test.py | 57 scaffold.ready_for_local_init_op.eval()
59 scaffold.ready_op.eval()
172 spec.predictions[prediction_keys.PredictionKeys.PROBABILITIES].eval({
191 mode=model_fn.ModeKeys.EVAL,
200 mode=model_fn.ModeKeys.EVAL,
207 training_loss.eval({
227 mode=model_fn.ModeKeys.EVAL,
237 mode=model_fn.ModeKeys.EVAL,
254 mode=model_fn.ModeKeys.EVAL,
259 training_loss.eval({
[all...] |
| dnn_testing_utils.py | 123 global_step_var.assign(global_step).eval()
149 elif mode == model_fn.ModeKeys.EVAL:
252 elif mode == model_fn.ModeKeys.EVAL:
274 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
301 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
332 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
359 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
386 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
414 model_fn.ModeKeys.TRAIN, model_fn.ModeKeys.EVAL,
442 elif mode == model_fn.ModeKeys.EVAL
[all...] |
| head.py | 627 """Returns the Eval metric ops."""
708 required argument when `mode` equals `TRAIN` or `EVAL`.
769 # Eval.
770 if mode == model_fn.ModeKeys.EVAL:
772 mode=model_fn.ModeKeys.EVAL,
[all...] |
| /external/tensorflow/tensorflow/contrib/tpu/python/tpu/ |
| tpu_context.py | 40 This immutable object holds TPUEstimator config, train/eval batch size, and
96 if mode != model_fn_lib.ModeKeys.EVAL else config.evaluation_master)
258 elif mode == model_fn_lib.ModeKeys.EVAL:
314 if mode == model_fn_lib.ModeKeys.EVAL else run_config.master)
436 elif mode == model_fn_lib.ModeKeys.EVAL:
443 'eval batch size {} must be divisible by number of replicas {}'
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/client/ |
| random_forest.py | 160 # If we're doing eval, optionally ignore device_assigner.
164 (local_eval and mode == model_fn_lib.ModeKeys.EVAL)):
328 pass through into the inference/eval results dict. Useful for
344 local_eval: If True, don't use a device assigner for eval. This is to
345 support some common setups where eval is done on a single machine, even
429 if (mode == model_fn_lib.ModeKeys.EVAL or
439 if (mode == model_fn_lib.ModeKeys.EVAL or
|
| /external/mesa3d/src/gallium/drivers/swr/rasterizer/core/ |
| rasterizer.cpp | 122 #define EVAL \
161 EVAL;
164 EVAL;
167 EVAL;
170 EVAL;
175 EVAL;
178 EVAL;
181 EVAL;
184 EVAL;
189 EVAL;
[all...] |
| /external/tensorflow/tensorflow/examples/get_started/regression/ |
| custom_regression.py | 69 assert mode == tf.estimator.ModeKeys.EVAL
|
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| wals_test.py | 96 In INFER and EVAL modes, one must also provide project_row, a boolean which
102 mode: Can be one of model_fn.ModeKeys.{TRAIN, INFER, EVAL}.
103 project_row: A boolean. Used in INFER and EVAL modes. Specifies whether
159 if mode == model_fn.ModeKeys.INFER or mode == model_fn.ModeKeys.EVAL:
162 msg='project_row must be specified in INFER or EVAL mode.')
322 # projection is idempotent, the eval loss must match the model loss.
331 mode=model_fn.ModeKeys.EVAL,
342 msg="""After row update, eval loss = {}, does not match the true
349 mode=model_fn.ModeKeys.EVAL,
360 msg="""After col update, eval loss = {}, does not match the tru
[all...] |
