| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| linear_test.py | 104 """Tests that loss goes down with training with joint weights."""
582 # weights, it learns y=x.
585 # then accuracy would be zero. Because of weights, accuracy should be close
590 # Considering weights, the mean label should be close to 1.0.
591 # If weights were ignored, it would be 0.25.
599 """Test ensures that you can specify per-example weights for loss."""
604 'weights': constant_op.constant([[100], [1], [1]]),
616 feature_columns=[age], weight_column_name='weights')
739 'weights': constant_op.constant([[1.0], [1.0]])
748 weight_column_name='weights',
[all...] |
| stability_test.py | 150 weights1 = ([regressor1.get_variable_value('dnn/hiddenlayer_0/weights')] +
151 [regressor1.get_variable_value('dnn/logits/weights')])
152 weights2 = ([regressor2.get_variable_value('dnn/hiddenlayer_0/weights')] +
153 [regressor2.get_variable_value('dnn/logits/weights')])
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| feature_column_test.py | 102 weighted_ids = fc.weighted_sparse_column(ids, "weights")
108 weighted_ids = fc.weighted_sparse_column(ids, "weights")
117 weighted = fc.weighted_sparse_column(ids, "weights")
120 self.assertEqual(weighted_copy.weight_column_name, "weights")
221 weighted_sparse_col = fc.weighted_sparse_column(ids, "weights")
327 weighted_ids = fc.weighted_sparse_column(ids, "weights")
384 weighted_ids = fc.weighted_sparse_column(ids, "weights")
388 "weights": constant_op.constant([[2., 4., 6.]])
659 weighted_ids = fc.weighted_sparse_column(ids, "weights")
662 "weights": parsing_ops.VarLenFeature(dtypes.float32
[all...] |
| feature_column_ops_test.py | 301 weighted_ids = feature_column.weighted_sparse_column(ids, "weights")
306 features = {"ids": ids_tensor, "weights": weights_tensor}
498 weights = column_to_variable[country_price][0]
500 gradients_impl.gradients(output, weights)[0].values)
[all...] |
| embedding_ops_test.py | 70 weights = [1.0, 2.0, 1.0, 1.0, 3.0, 0.0, -0.5]
80 constant_op.constant(weights, dtypes.float32),
96 weights = [1.0, 2.0, 1.0, 1.0, 3.0, 0.0, -0.5]
106 constant_op.constant(weights, dtypes.float32),
312 # Large embedding dimension to cover the full range of weights.
415 # embedding weights will be equal.
610 weights = []
649 weights.append(weight_aggregation)
652 weights = np.array(weights).astype(np.float32
[all...] |
| /device/google/marlin/ |
| thermal-engine-marlin.conf | 82 weights 1 -1
|
| /device/google/muskie/ |
| thermal-engine.conf | 38 weights 1 -1
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/ode/nonstiff/ |
| RungeKuttaIntegrator.java | 60 /** Internal weights from Butcher array (without the first empty row). */
63 /** External weights for the high order method from Butcher array. */
77 * @param a internal weights from Butcher array (without the first empty row)
78 * @param b propagation weights for the high order method from Butcher array
|
| /external/libopus/src/ |
| mlp.h | 36 const float *weights; member in struct:__anon25624
|
| /external/libxcam/modules/ocl/ |
| cv_image_process_helper.h | 43 void normalize_weights (cv::Mat &weights);
|
| /external/llvm/test/Transforms/JumpThreading/ |
| update-edge-weight.ll | 3 ; Test if edge weights are properly updated after jump threading.
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| lstm_layer_inference.config.pbtxt | 12 feed{ id{node_name:"weights/read"} shape{dim{size:2048}dim{size:4096}} }
|
| /external/tensorflow/tensorflow/contrib/layers/ |
| README.md | 27 Weights and biases are added to `tf.GraphKeys.GLOBAL_VARIABLES` and
|
| /external/tensorflow/tensorflow/contrib/losses/ |
| README.md | 23 non-zero weights.
|
| /external/tensorflow/tensorflow/contrib/metrics/ |
| README.md | 21 losses with non-zero weights.
|
| /external/tensorflow/tensorflow/contrib/metrics/python/metrics/ |
| classification_test.py | 86 weights = array_ops.placeholder(dtypes.float32, shape=[None])
92 weights: [3.0, 1.0, 2.0, 0.0]
100 weights = array_ops.placeholder(dtypes.float32, shape=[])
106 weights: 3.0,
|
| /external/tensorflow/tensorflow/contrib/mpi_collectives/ |
| mpi_allreduce_test.py | 68 weights = []
71 weights.append(tf.get_variable("weights_{}".format(i),
79 inter_output = tf.add(stage_input, weights[i],
89 inter_output = tf.add(local_input, weights[i],
|
| /external/tensorflow/tensorflow/contrib/tensorrt/ |
| tensorrt_test.cc | 55 const nvinfer1::Weights& get() { return w; }
59 nvinfer1::Weights w;
69 ScopedWeights weights(2.0);
78 auto layer = network->addFullyConnected(*input, 1, weights.get(), bias.get());
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_ComputeAccidentalHits.pbtxt | 29 name: "weights"
|
| /external/tensorflow/tensorflow/tools/api/golden/ |
| tensorflow.keras.optimizers.-adadelta.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
| tensorflow.keras.optimizers.-adagrad.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
| tensorflow.keras.optimizers.-adam.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
| tensorflow.keras.optimizers.-adamax.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
| tensorflow.keras.optimizers.-nadam.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
| tensorflow.keras.optimizers.-r-m-sprop.pbtxt | 32 argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
|
