| /external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
| nn.py | 26 relu6 = core.define_unary_op('relu6', nn.relu6) variable
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| nn_test.py | 38 ('relu6', nn_ops.relu6, nn.relu6),
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| /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)
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| 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)
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| quantize_test.py | 54 relu = nn_ops.relu6(inputs)
62 str(err.exception), 'Some inputs not quantized for ops: [Relu6]')
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| /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')
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| 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},
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| 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,
|
