/external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
nn.py | 26 relu6 = core.define_unary_op('relu6', nn.relu6) variable
|
nn_test.py | 38 ('relu6', nn_ops.relu6, nn.relu6),
|
/external/tensorflow/tensorflow/contrib/quantize/python/ |
input_to_ops_test.py | 45 output_tensor = nn_ops.relu6(input_tensor) 56 output_tensor_1 = nn_ops.relu6(input_tensor)
|
quantize_parameterized_test.py | 45 (nn_ops.relu6, 'Relu6', False, None), 48 (nn_ops.relu6, 'Relu6', False, 5000), 51 (nn_ops.relu6, 'Relu6', True, None), 54 (nn_ops.relu6, 'Relu6', True, 5000), 294 (nn_ops.relu6, 'Relu6', False, None, False) [all...] |
fold_batch_norms_test.py | 51 (nn_ops.relu6, 'Relu6', False, False, False, 100), 53 (nn_ops.relu6, 'Relu6', True, False, False, 100), 55 (nn_ops.relu6, 'Relu6', False, True, False, 100), 57 (nn_ops.relu6, 'Relu6', True, True, False, 100), 60 (nn_ops.relu6, 'Relu6', False, True, True, None) [all...] |
quantize_graph_test.py | 227 _ = nn_ops.relu6(conv)
|
quantize_test.py | 54 relu = nn_ops.relu6(inputs) 62 str(err.exception), 'Some inputs not quantized for ops: [Relu6]')
|
/external/tensorflow/tensorflow/core/graph/ |
quantize_training_test.cc | 132 Relu Relu6 143 Node* relu6 = test::graph::Relu6(g, b); local 144 Node* m1 = test::graph::Matmul(g, relu, relu6, false, false); 152 Relu Relu6 161 // Quantize_and_dequantize node for relu6 should have range_given==true. 164 FindNode(g, strings::StrCat(relu6->name(), "/QuantizeAndDequantizeV2"), 361 Relu Relu6 373 Node* relu6 = test::graph::Relu6(g, c) local 467 Node* relu6 = test::graph::Relu6(g, c); local [all...] |
/external/tensorflow/tensorflow/python/ops/ |
nn_grad_test.py | 38 r = nn_ops.relu6(inputs)
|
nn_ops.py | 1567 def relu6(features, name=None): function [all...] |
/external/tensorflow/tensorflow/python/kernel_tests/ |
relu_op_test.py | 172 relu6 = nn_ops.relu6(np_features) 173 tf_relu6 = relu6.eval() 175 self.assertShapeEqual(np_relu6, relu6) 187 # The gradient test for ReLU6 is a bit tricky as the derivative is 196 y = nn_ops.relu6(x, name="relu6") 203 print("relu6 (float32) gradient err = ", err) 213 y = nn_ops.relu6(x, name="relu6") [all...] |
/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
summaries_test.py | 69 op = nn_ops.relu6(var, name='SummaryTest')
|
layers.py | 65 'max_pool3d', 'one_hot_encoding', 'relu', 'relu6', 'repeat', 3120 relu6 = functools.partial(fully_connected, activation_fn=nn.relu6) variable [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/applications/ |
mobilenet.py | 102 def relu6(x): function 327 objects `relu6` and `DepthwiseConv2D` and pass them to the 331 'relu6': mobilenet.relu6, 554 """Adds an initial convolution layer (with batch normalization and relu6). 610 return Activation(relu6, name='conv1_relu')(x) 622 batch normalization, relu6, pointwise convolution, 623 batch normalization and relu6 activation. 678 x = Activation(relu6, name='conv_dw_%d_relu' % block_id)(x) 688 return Activation(relu6, name='conv_pw_%d_relu' % block_id)(x [all...] |
/external/tensorflow/tensorflow/contrib/lite/testing/ |
generated_examples_zip_test.cc | 258 INSTANTIATE_TESTS(relu6)
|
/hardware/qcom/neuralnetworks/hvxservice/1.0/ |
HexagonOperationsCheck.cpp | 354 bool relu6(const std::vector<uint32_t>& ins, const std::vector<uint32_t>& outs, function in namespace:android::hardware::neuralnetworks::V1_0::implementation::hexagon::__anon52541 356 return activation(ins, outs, model, 1, OperationType::RELU6); 447 {{OperationType::RELU6, OperandType::TENSOR_FLOAT32}, relu6}, 474 {{OperationType::RELU6, OperandType::TENSOR_QUANT8_ASYMM}, relu6},
|
HexagonOperationsPrepare.cpp | 412 bool relu6(const std::vector<uint32_t>& ins, const std::vector<uint32_t>& outs, function in namespace:android::hardware::neuralnetworks::V1_0::implementation::hexagon::__anon52542::float32 414 HEXAGON_SOFT_ASSERT_EQ(1, ins.size(), "Need 1 input for float32::relu6"); 415 HEXAGON_SOFT_ASSERT_EQ(1, outs.size(), "Need 1 output for float32::relu6"); 859 bool relu6(const std::vector<uint32_t>& ins, const std::vector<uint32_t>& outs, function in namespace:android::hardware::neuralnetworks::V1_0::implementation::hexagon::__anon52542::quant8_asym [all...] |
/external/tensorflow/tensorflow/contrib/training/python/training/ |
hparam_test.py | 41 hparams = hparam.HParams(aaa=1, b=2.0, c_c='relu6') 42 self.assertDictEqual({'aaa': 1, 'b': 2.0, 'c_c': 'relu6'}, hparams.values()) 43 expected_str = '[(\'aaa\', 1), (\'b\', 2.0), (\'c_c\', \'relu6\')]' 48 self.assertEqual('relu6', hparams.c_c) 53 'c_c': 'relu6' 57 self.assertEqual('relu6', hparams.c_c) 132 hparams = hparam.HParams(aaa=[1], b=[2.0, 3.0], c_c=['relu6']) 136 'c_c': ['relu6'] 140 self.assertEqual(['relu6'], hparams.c_c) 266 hparams = hparam.HParams(aaa=1, b=2.0, c_c='relu6', d=True [all...] |
/external/tensorflow/tensorflow/python/keras/_impl/keras/ |
estimator_test.py | 340 'relu6': mobilenet.relu6, 343 with self.assertRaisesRegexp(ValueError, 'relu6'):
|
/external/tensorflow/tensorflow/compiler/tests/ |
unary_ops_test.py | 347 nn_ops.relu6,
|