/external/tensorflow/tensorflow/python/ops/ |
D | confusion_matrix.py | 29 labels, predictions, expected_rank_diff=0, name=None): argument 55 [labels, predictions]): 56 predictions = ops.convert_to_tensor(predictions) 58 predictions_shape = predictions.get_shape() 67 predictions = array_ops.squeeze(predictions, [-1]) 71 return labels, predictions 74 rank_diff = array_ops.rank(predictions) - array_ops.rank(labels) 77 predictions = control_flow_ops.cond( 79 lambda: array_ops.squeeze(predictions, [-1]), 80 lambda: predictions) [all …]
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D | metrics_impl.py | 84 def _remove_squeezable_dimensions(predictions, labels, weights): argument 107 predictions = ops.convert_to_tensor(predictions) 109 labels, predictions = confusion_matrix.remove_squeezable_dimensions( 110 labels, predictions) 111 predictions.get_shape().assert_is_compatible_with(labels.get_shape()) 114 return predictions, labels, None 120 return predictions, labels, weights 122 predictions_shape = predictions.get_shape() 133 rank_diff = weights_rank_tensor - array_ops.rank(predictions) 157 return predictions, labels, weights [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/math_ops/ |
D | in_topk_op_test.py | 26 def _validateInTopK(self, predictions, target, k, expected): argument 29 precision = nn_ops.in_top_k(predictions, target, k) 35 predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]] 37 self._validateInTopK(predictions, target, 1, [True, False]) 40 predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]] 42 self._validateInTopK(predictions, target, 2, [False, True]) 46 predictions = [[0.1, 0.3, 0.2, 0.2], [0.1, 0.3, 0.2, 0.2]] 48 self._validateInTopK(predictions, target, 2, [True, True]) 51 predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]] 53 self._validateInTopK(predictions, target, 2, [False, True]) [all …]
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D | confusion_matrix_test.py | 42 labels=[1, 2, 4], predictions=[2, 2, 4]))) 44 def _testConfMatrix(self, labels, predictions, truth, weights=None, argument 47 dtype = predictions.dtype 49 labels, predictions, dtype=dtype, weights=weights, 56 predictions = np.arange(5, dtype=dtype) 66 self._testConfMatrix(labels=labels, predictions=predictions, truth=truth) 120 predictions = np.asarray([1, 2, 3], dtype=dtype) 132 self._testConfMatrix(labels=labels, predictions=predictions, truth=truth) 144 predictions = np.asarray([1, 1, 2, 3, 5, 6, 1, 2, 3, 4], dtype=dtype) 156 self._testConfMatrix(labels=labels, predictions=predictions, truth=truth) [all …]
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/external/tensorflow/tensorflow/python/keras/distribute/ |
D | dataset_creator_model_fit_test.py | 167 _, predictions = self._model_predict(strategy, steps=3) 171 self.assertTrue(all(predictions[0] == predictions[i] for i in [0, 3, 5])) 174 all(predictions[0] == predictions[i] for i in [0, 1, 2, 4])) 178 _, predictions = self._model_predict(strategy, test_data=x) 180 self.assertTrue(all(predictions[0] == predictions[i] for i in [0, 3, 5])) 182 all(predictions[0] == predictions[i] for i in [0, 1, 2, 4])) 186 _, predictions = self._model_predict(strategy, test_data=x) 187 self.assertTrue(all(predictions[0] == predictions[i] for i in [0, 3, 5])) 189 all(predictions[0] == predictions[i] for i in [0, 1, 2, 4])) 192 _, predictions = self._model_predict( [all …]
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/external/tensorflow/tensorflow/python/distribute/ |
D | metrics_v1_test.py | 152 predictions = x["predictions"] 153 return metrics.accuracy(labels, predictions) 167 predictions = x["predictions"] 169 labels, predictions, num_classes=5) 186 predictions = x["predictions"] 188 labels, predictions, num_classes=5) 223 predictions = x["predictions"] 224 return metrics.auc(labels, predictions, num_thresholds=8, curve="ROC", 237 predictions = x["predictions"] 238 return metrics.auc(labels, predictions, num_thresholds=8, curve="PR", [all …]
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | metrics_test.py | 558 predictions=array_ops.ones((10, 1)), 568 predictions=array_ops.ones((10, 1)), 577 predictions=array_ops.ones((10, 1)), 584 predictions = array_ops.ones((10, 3)) 587 metrics.accuracy(labels, predictions) 591 predictions = array_ops.ones((10, 3)) 595 metrics.accuracy(labels, predictions, weights) 599 predictions = random_ops.random_uniform( 603 accuracy, update_op = metrics.accuracy(labels, predictions) 627 predictions = preds_queue.dequeue() [all …]
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/external/tensorflow/tensorflow/python/ops/losses/ |
D | losses_impl.py | 218 labels, predictions, weights=1.0, scope=None, argument 257 if predictions is None: 260 (predictions, labels, weights)) as scope: 261 predictions = math_ops.cast(predictions, dtype=dtypes.float32) 263 predictions.get_shape().assert_is_compatible_with(labels.get_shape()) 264 losses = math_ops.abs(math_ops.subtract(predictions, labels)) 273 labels, predictions, axis=None, weights=1.0, scope=None, argument 312 if predictions is None: 315 (predictions, labels, weights)) as scope: 316 predictions = math_ops.cast(predictions, dtype=dtypes.float32) [all …]
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.metrics.pbtxt | 5 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle… 9 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'num_thresholds\', \'metrics_collection… 13 …argspec: "args=[\'labels\', \'predictions\', \'k\', \'weights\', \'metrics_collections\', \'update… 17 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle… 21 …argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\',… 25 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle… 29 …argspec: "args=[\'labels\', \'predictions\', \'thresholds\', \'weights\', \'metrics_collections\',… 37 …argspec: "args=[\'labels\', \'predictions\', \'weights\', \'metrics_collections\', \'updates_colle… 41 …argspec: "args=[\'labels\', \'predictions\', \'dim\', \'weights\', \'metrics_collections\', \'upda… 45 …argspec: "args=[\'labels\', \'predictions\', \'num_classes\', \'weights\', \'metrics_collections\'… [all …]
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/external/ComputeLibrary/src/core/CPP/kernels/ |
D | CPPTopKVKernel.cpp | 52 Status validate_arguments(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *… in validate_arguments() argument 55 …ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(predictions, 1, DataType::QASYMM8, DataType::… in validate_arguments() 58 ARM_COMPUTE_RETURN_ERROR_ON(predictions->num_dimensions() > 2); in validate_arguments() 60 ARM_COMPUTE_RETURN_ERROR_ON(targets->dimension(0) != predictions->dimension(1)); in validate_arguments() 99 void CPPTopKVKernel::configure(const ITensor *predictions, const ITensor *targets, ITensor *output,… in configure() argument 101 ARM_COMPUTE_ERROR_ON_NULLPTR(predictions, targets, output); in configure() 104 …ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(predictions->info(), targets->info(), output->info()… in configure() 107 _predictions = predictions; in configure() 112 _batch_size = predictions->info()->dimension(1); in configure() 113 _num_classes = predictions->info()->dimension(0); in configure() [all …]
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/external/tensorflow/tensorflow/python/keras/saving/utils_v1/ |
D | signature_def_utils.py | 24 inputs, loss, predictions=None, metrics=None): argument 27 predictions=predictions, metrics=metrics) 31 inputs, loss, predictions=None, metrics=None): argument 34 predictions=predictions, metrics=metrics) 38 method_name, inputs, loss=None, predictions=None, argument 67 for output_set in (loss, predictions, metrics):
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D | export_utils.py | 253 mode, serving_export_outputs=None, predictions=None, loss=None, argument 287 return get_export_outputs(serving_export_outputs, predictions) 290 loss=loss, predictions=predictions, metrics=metrics)} 293 loss=loss, predictions=predictions, metrics=metrics)} 296 def get_export_outputs(export_outputs, predictions): argument 312 default_output = export_output_lib.PredictOutput(predictions)
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/external/libtextclassifier/native/annotator/translate/ |
D | translate_test.cc | 104 const auto predictions = in TEST_F() local 106 EXPECT_EQ(predictions->size(), 1); in TEST_F() 107 EXPECT_EQ(predictions->Get(0)->language_tag()->str(), "cs"); in TEST_F() 108 EXPECT_GT(predictions->Get(0)->confidence_score(), 0); in TEST_F() 109 EXPECT_LE(predictions->Get(0)->confidence_score(), 1); in TEST_F() 121 const auto predictions = in TEST_F() local 123 EXPECT_EQ(predictions->size(), 2); in TEST_F() 124 EXPECT_EQ(predictions->Get(0)->language_tag()->str(), "zh"); in TEST_F() 125 EXPECT_GT(predictions->Get(0)->confidence_score(), 0); in TEST_F() 126 EXPECT_LE(predictions->Get(0)->confidence_score(), 1); in TEST_F() [all …]
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/external/ComputeLibrary/tests/validation/CPP/ |
D | TopKV.cpp | 88 Tensor predictions = create_tensor<Tensor>(TensorShape(10, 20), DataType::F32); in TEST_CASE() local 91 predictions.allocator()->allocate(); in TEST_CASE() 95 fill_tensor(Accessor(predictions), std::vector<float> in TEST_CASE() 124 topkv.configure(&predictions, &targets, &output, k); in TEST_CASE() 141 …Tensor predictions = create_tensor<Tensor>(TensorShape(10, 20), DataType::QASYMM8, 1, Quantization… in TEST_CASE() local 144 predictions.allocator()->allocate(); in TEST_CASE() 148 fill_tensor(Accessor(predictions), std::vector<uint8_t> in TEST_CASE() 177 topkv.configure(&predictions, &targets, &output, k); in TEST_CASE() 194 …Tensor predictions = create_tensor<Tensor>(TensorShape(10, 20), DataType::QASYMM8_SIGNED, 1, Quant… in TEST_CASE() local 197 predictions.allocator()->allocate(); in TEST_CASE() [all …]
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/external/tensorflow/tensorflow/python/saved_model/model_utils/ |
D | export_output_test.py | 242 predictions = {u'output1': constant_op.constant(['foo'])} 249 outputter = MockSupervisedOutput(loss, predictions, metrics) 252 outputter.predictions['predictions/output1'], predictions['output1']) 260 loss['my_loss'], predictions['output1'], metrics['metrics']) 263 outputter.predictions, {'predictions': predictions['output1']}) 271 self.assertIsNone(outputter.predictions) 288 predictions = {(u'output1', '2'): constant_op.constant(['foo'])} 296 outputter = MockSupervisedOutput(loss, predictions, metrics) 298 self.assertEqual(set(outputter.predictions.keys()), 311 predictions = {u'predictions': constant_op.constant(['foo'])} [all …]
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/external/tensorflow/tensorflow/python/keras/utils/ |
D | losses_utils.py | 92 labels, predictions, expected_rank_diff=0, name=None): argument 118 if not isinstance(predictions, ragged_tensor.RaggedTensor): 119 predictions = ops.convert_to_tensor_v2_with_dispatch(predictions) 122 predictions_shape = predictions.shape 131 predictions = array_ops.squeeze(predictions, [-1]) 135 return labels, predictions 138 rank_diff = array_ops.rank(predictions) - array_ops.rank(labels) 141 predictions = control_flow_ops.cond( 143 lambda: array_ops.squeeze(predictions, [-1]), 144 lambda: predictions) [all …]
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/external/tensorflow/tensorflow/core/kernels/ |
D | in_topk_op.h | 48 typename TTypes<T, 2>::ConstTensor predictions, in operator() 56 typename TTypes<T, 2>::ConstTensor predictions, 59 const Eigen::Index num_targets = predictions.dimension(0); 60 const Eigen::Index num_classes = predictions.dimension(1); 75 !std::isfinite(predictions(batch_idx, target)); 79 const T target_prediction = predictions(batch_idx, target); 82 T pred = predictions(batch_idx, class_idx);
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D | in_topk_op_gpu.cu.cc | 40 const T* __restrict__ predictions, // dims: [ num_targets x num_classes ] in ComputePredictionMaskKernel() argument 53 T prediction = ldg(predictions + i); in ComputePredictionMaskKernel() 55 ldg(predictions + batch_index * num_classes + target_idx); in ComputePredictionMaskKernel() 92 typename TTypes<T, 2>::ConstTensor predictions, in operator ()() 95 const Eigen::Index num_targets = predictions.dimension(0); in operator ()() 96 const Eigen::Index num_classes = predictions.dimension(1); in operator ()() 131 d.stream(), predictions.data(), targets.data(), in operator ()()
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/external/ComputeLibrary/src/runtime/CPP/functions/ |
D | CPPTopKV.cpp | 32 void CPPTopKV::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const… in configure() argument 34 ARM_COMPUTE_LOG_PARAMS(predictions, targets, output, k); in configure() 37 kernel->configure(predictions, targets, output, k); in configure() 41 Status CPPTopKV::validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *… in validate() argument 43 return CPPTopKVKernel::validate(predictions, targets, output, k); in validate()
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/external/tensorflow/tensorflow/python/saved_model/ |
D | signature_def_utils_impl.py | 67 def regression_signature_def(examples, predictions): argument 89 if predictions is None: 98 output_tensor_info = utils.build_tensor_info(predictions) 217 inputs, loss, predictions=None, metrics=None): argument 220 predictions=predictions, metrics=metrics) 224 inputs, loss, predictions=None, metrics=None): argument 227 predictions=predictions, metrics=metrics) 231 method_name, inputs, loss=None, predictions=None, argument 260 for output_set in (loss, predictions, metrics):
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/external/tensorflow/tensorflow/python/kernel_tests/nn_ops/ |
D | losses_test.py | 108 predictions = constant_op.constant([4, 8, 12, 8, 1, 3], shape=(2, 3)) 110 losses.absolute_difference(labels, predictions) 657 predictions = np.asarray([.9, .2, .2, .8, .4, .6]).reshape((2, 3)) 660 self._np_predictions = predictions 665 labels, np.log(predictions + epsilon)) + np.multiply( 666 1 - labels, np.log(1 - predictions + epsilon)) 668 self._predictions = constant_op.constant(predictions) 868 predictions = constant_op.constant([[-1.0], [2.1]]) 871 _ = losses.huber_loss(labels, predictions).eval() 876 predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0]) [all …]
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/external/libtextclassifier/native/lang_id/ |
D | lang-id.cc | 103 if (lang_id_result.predictions.empty()) { in FindLanguage() 107 const std::string &language = lang_id_result.predictions[0].first; in FindLanguage() 108 const float probability = lang_id_result.predictions[0].second; in FindLanguage() 134 result->predictions.clear(); in FindLanguages() 136 result->predictions.emplace_back(LangId::kUnknownLanguageCode, 1); in FindLanguages() 147 result->predictions.emplace_back(LangId::kUnknownLanguageCode, 1); in FindLanguages() 165 result->predictions.emplace_back(language, probability); in FindLanguages() 173 result->predictions.emplace_back(GetLanguageForSoftmaxLabel(index), in FindLanguages()
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/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_InTopKV2.pbtxt | 4 name: "predictions" 27 summary: "Says whether the targets are in the top `K` predictions." 30 prediction for the target class is among the top `k` predictions among 31 all predictions for example `i`. Note that the behavior of `InTopK` differs 38 \\(predictions_i\\) be the predictions for all classes for example `i`,
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D | api_def_InTopK.pbtxt | 4 name: "predictions" 27 summary: "Says whether the targets are in the top `K` predictions." 30 prediction for the target class is among the top `k` predictions among 31 all predictions for example `i`. Note that the behavior of `InTopK` differs 38 \\(predictions_i\\) be the predictions for all classes for example `i`,
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/external/tensorflow/tensorflow/python/feature_column/ |
D | feature_column_test.py | 348 predictions = fc.linear_model(features, [price]) 354 self.assertAllClose([[0.], [0.]], self.evaluate(predictions)) 356 self.assertAllClose([[10.], [50.]], self.evaluate(predictions)) 362 predictions = get_keras_linear_model_predictions(features, [price]) 368 self.assertAllClose([[0.], [0.]], self.evaluate(predictions)) 370 self.assertAllClose([[10.], [50.]], self.evaluate(predictions)) 535 predictions = fc.linear_model(features, [bucketized_price]) 544 self.evaluate(predictions)) 552 self.evaluate(predictions)) 555 self.evaluate(predictions)) [all …]
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