diff options
Diffstat (limited to 'tensorflow/contrib/learn/python/learn/estimators/head_test.py')
| -rw-r--r-- | tensorflow/contrib/learn/python/learn/estimators/head_test.py | 80 |
1 files changed, 41 insertions, 39 deletions
diff --git a/tensorflow/contrib/learn/python/learn/estimators/head_test.py b/tensorflow/contrib/learn/python/learn/estimators/head_test.py index 9b8cba1526..abaf3a61a1 100644 --- a/tensorflow/contrib/learn/python/learn/estimators/head_test.py +++ b/tensorflow/contrib/learn/python/learn/estimators/head_test.py @@ -124,7 +124,7 @@ class PoissonHeadTest(test.TestCase): train_op_fn=head_lib.no_op_train_fn, logits=logits) self._assert_output_alternatives(model_fn_ops) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_no_variables(self) loss = self._log_poisson_loss(logits, labels) _assert_metrics(self, loss, {"loss": loss}, model_fn_ops) @@ -150,7 +150,7 @@ class RegressionHeadTest(test.TestCase): train_op_fn=head_lib.no_op_train_fn, logits=((1.,), (1.,), (3.,))) self._assert_output_alternatives(model_fn_ops) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_no_variables(self) _assert_metrics(self, 5. / 3, {"loss": 5. / 3}, model_fn_ops) @@ -180,7 +180,7 @@ class RegressionHeadTest(test.TestCase): _assert_variables( self, expected_global=w, expected_model=w, expected_trainable=w) variables.global_variables_initializer().run() - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_metrics(self, 2. / 3, {"loss": 2. / 3}, model_fn_ops) def testRegressionWithLogitsAndLogitsInput(self): @@ -208,7 +208,7 @@ class RegressionHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_metrics(self, 5. / 3, {"loss": 5. / 3}, model_fn_ops) def testRegressionWithLabelName(self): @@ -223,7 +223,7 @@ class RegressionHeadTest(test.TestCase): logits=((1.,), (1.,), (3.,))) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_metrics(self, 5. / 3, {"loss": 5. / 3}, model_fn_ops) def testRegressionWithWeights(self): @@ -238,7 +238,7 @@ class RegressionHeadTest(test.TestCase): logits=((1.,), (1.,), (3.,))) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["regression_head/loss"]) _assert_metrics(self, 2. / len(weights), {"loss": 2. / np.sum(weights)}, model_fn_ops) @@ -261,7 +261,7 @@ class RegressionHeadTest(test.TestCase): expected_trainable=("regression_head/centered_bias_weight:0",)) variables.global_variables_initializer().run() _assert_summary_tags( - self, ["loss", "regression_head/centered_bias/bias_0"]) + self, ["regression_head/loss", "regression_head/centered_bias/bias_0"]) _assert_metrics(self, 5. / 3, {"loss": 5. / 3}, model_fn_ops) def testRegressionErrorInSparseTensorLabels(self): @@ -330,7 +330,7 @@ class MultiLabelHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = .89985204 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -347,7 +347,7 @@ class MultiLabelHeadTest(test.TestCase): train_op_fn=head_lib.no_op_train_fn, logits=logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = 1.00320443 _assert_metrics(self, expected_loss, { "accuracy": 0., @@ -387,7 +387,7 @@ class MultiLabelHeadTest(test.TestCase): _assert_variables( self, expected_global=w, expected_model=w, expected_trainable=w) variables.global_variables_initializer().run() - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = .69314718 _assert_metrics(self, expected_loss, { "accuracy": 2. / 3, @@ -432,7 +432,7 @@ class MultiLabelHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = .89985204 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -451,7 +451,7 @@ class MultiLabelHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = 1.377779 expected_eval_metrics = { "accuracy": 1. / 3, @@ -519,7 +519,7 @@ class MultiLabelHeadTest(test.TestCase): head_lib.no_op_train_fn, logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = .89985204 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -539,7 +539,7 @@ class MultiLabelHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) _assert_metrics(self, .089985214, self._expected_eval_metrics(2.69956), model_fn_ops) @@ -559,7 +559,7 @@ class MultiLabelHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) _assert_metrics(self, 0.089985214, self._expected_eval_metrics(0.089985214), model_fn_ops) @@ -583,7 +583,7 @@ class MultiLabelHeadTest(test.TestCase): expected_trainable=("multi_label_head/centered_bias_weight:0",)) variables.global_variables_initializer().run() _assert_summary_tags(self, ( - "loss", + "multi_label_head/loss", "multi_label_head/centered_bias/bias_0", "multi_label_head/centered_bias/bias_1", "multi_label_head/centered_bias/bias_2" @@ -608,7 +608,7 @@ class MultiLabelHeadTest(test.TestCase): train_op_fn=head_lib.no_op_train_fn, logits=self._logits) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_label_head/loss"]) expected_loss = .89985204 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -674,7 +674,7 @@ class BinaryClassificationHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) expected_loss = .81326175 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -702,7 +702,7 @@ class BinaryClassificationHeadTest(test.TestCase): _assert_variables( self, expected_global=w, expected_model=w, expected_trainable=w) variables.global_variables_initializer().run() - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) expected_loss = .69314718 label_mean = np.mean(self._labels) _assert_metrics(self, expected_loss, { @@ -738,7 +738,7 @@ class BinaryClassificationHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) expected_loss = .81326175 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -817,7 +817,7 @@ class BinaryClassificationHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) expected_loss = .81326175 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -838,7 +838,7 @@ class BinaryClassificationHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) expected_total_loss = .31326166 _assert_metrics( self, @@ -871,7 +871,7 @@ class BinaryClassificationHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_logistic_head/loss"]) # logloss: z:label, x:logit # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x)) # expected_loss is (total_weighted_loss)/1 since htere is 1 nonzero @@ -911,7 +911,8 @@ class BinaryClassificationHeadTest(test.TestCase): expected_trainable=("binary_logistic_head/centered_bias_weight:0",)) variables.global_variables_initializer().run() _assert_summary_tags( - self, ["loss", "binary_logistic_head/centered_bias/bias_0"]) + self, ["binary_logistic_head/loss", + "binary_logistic_head/centered_bias/bias_0"]) expected_loss = .81326175 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -960,7 +961,7 @@ class MultiClassHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.5514447 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -999,7 +1000,7 @@ class MultiClassHeadTest(test.TestCase): _assert_variables( self, expected_global=w, expected_model=w, expected_trainable=w) variables.global_variables_initializer().run() - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.0986123 _assert_metrics(self, expected_loss, { "accuracy": 0., @@ -1050,7 +1051,7 @@ class MultiClassHeadTest(test.TestCase): expected_trainable=("multi_class_head/centered_bias_weight:0",)) variables.global_variables_initializer().run() _assert_summary_tags(self, - ["loss", + ["multi_class_head/loss", "multi_class_head/centered_bias/bias_0", "multi_class_head/centered_bias/bias_1", "multi_class_head/centered_bias/bias_2"]) @@ -1068,7 +1069,7 @@ class MultiClassHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.5514447 _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -1087,7 +1088,7 @@ class MultiClassHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 3.1698461 expected_eval_metrics = { "accuracy": 0., @@ -1126,7 +1127,7 @@ class MultiClassHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.5514447 _assert_metrics(self, expected_loss * weight, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -1150,7 +1151,7 @@ class MultiClassHeadTest(test.TestCase): logits=self._logits) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.5514447 * weight _assert_metrics(self, expected_loss, self._expected_eval_metrics(expected_loss), model_fn_ops) @@ -1257,7 +1258,7 @@ class MultiClassHeadTest(test.TestCase): data_flow_ops.tables_initializer().run() self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 1.5514447 expected_eval_metrics = { "accuracy": 0., @@ -1283,7 +1284,7 @@ class MultiClassHeadTest(test.TestCase): data_flow_ops.tables_initializer().run() self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["multi_class_head/loss"]) expected_loss = 0.5514447 expected_eval_metrics = { "accuracy": 1., @@ -1322,7 +1323,7 @@ class BinarySvmHeadTest(test.TestCase): logits=self._predictions) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_svm_head/loss"]) expected_loss = np.average(self._expected_losses) _assert_metrics(self, expected_loss, { "accuracy": 1., @@ -1352,7 +1353,7 @@ class BinarySvmHeadTest(test.TestCase): _assert_variables( self, expected_global=w, expected_model=w, expected_trainable=w) variables.global_variables_initializer().run() - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_svm_head/loss"]) expected_loss = 1. _assert_metrics(self, expected_loss, { "accuracy": .5, @@ -1384,7 +1385,7 @@ class BinarySvmHeadTest(test.TestCase): self._assert_output_alternatives(model_fn_ops) self.assertIsNone(model_fn_ops.train_op) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_svm_head/loss"]) expected_loss = np.average(self._expected_losses) _assert_metrics(self, expected_loss, { "accuracy": 1., @@ -1403,7 +1404,7 @@ class BinarySvmHeadTest(test.TestCase): logits=self._predictions) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_svm_head/loss"]) expected_loss = np.average(self._expected_losses) _assert_metrics(self, expected_loss, { "accuracy": 1., @@ -1422,7 +1423,7 @@ class BinarySvmHeadTest(test.TestCase): logits=self._predictions) self._assert_output_alternatives(model_fn_ops) _assert_no_variables(self) - _assert_summary_tags(self, ["loss"]) + _assert_summary_tags(self, ["binary_svm_head/loss"]) expected_weighted_sum = np.sum( np.multiply(weights, self._expected_losses)) _assert_metrics(self, expected_weighted_sum / len(weights), { @@ -1450,7 +1451,8 @@ class BinarySvmHeadTest(test.TestCase): expected_trainable=("binary_svm_head/centered_bias_weight:0",)) variables.global_variables_initializer().run() _assert_summary_tags( - self, ["loss", "binary_svm_head/centered_bias/bias_0"]) + self, ["binary_svm_head/loss", + "binary_svm_head/centered_bias/bias_0"]) expected_loss = np.average(self._expected_losses) _assert_metrics(self, expected_loss, { "accuracy": 1., |