/external/tensorflow/tensorflow/core/graph/ |
D | quantize_training_test.cc | 92 Node* relu = test::graph::Relu(g, a); in TEST_F() local 94 Node* m1 = test::graph::Matmul(g, relu, identity, false, false); in TEST_F() 121 FindNode(g, strings::StrCat(relu->name(), "/QuantizeAndDequantizeV2"), in TEST_F() 143 Node* relu = test::graph::Relu(g, a); in TEST_F() local 145 Node* m1 = test::graph::Matmul(g, relu, relu6, false, false); in TEST_F() 172 FindNode(g, strings::StrCat(relu->name(), "/QuantizeAndDequantizeV2"), in TEST_F() 192 Node* relu = test::graph::Relu(g, a); in TEST_F() local 194 Node* m1 = test::graph::Matmul(g, relu, identity, false, false); in TEST_F() 223 FindNode(g, strings::StrCat(relu->name(), "/QuantizeAndDequantizeV2"), in TEST_F() 246 Node* relu = test::graph::Relu(g, a); in TEST_F() local [all …]
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/external/tensorflow/tensorflow/contrib/quantize/python/ |
D | fold_batch_norms_test.py | 53 (nn_ops.relu, 'Relu', False, False, False, None, False), 55 (nn_ops.relu, 'Relu', True, False, False, None, False), 57 (nn_ops.relu, 'Relu', False, True, False, None, False), 59 (nn_ops.relu, 'Relu', True, True, False, None, False), 62 (nn_ops.relu, 'Relu', False, True, True, 100, False), 64 (nn_ops.relu, 'Relu', True, True, True, 100, False), 66 (nn_ops.relu, 'Relu', False, True, True, 100, True), 68 (nn_ops.relu, 'Relu', True, True, True, 100, True), 74 def _TestFoldConv2d(self, relu, relu_op_name, with_bypass, has_scaling, argument 97 activation_fn = None if with_bypass else relu [all …]
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D | quantize_parameterized_test.py | 47 (nn_ops.relu, 'Relu', False, None), 50 (nn_ops.relu, 'Relu', False, 5000), 53 (nn_ops.relu, 'Relu', True, None), 56 (nn_ops.relu, 'Relu', True, 5000), 367 (nn_ops.relu, 'Relu', False, None, False), 370 (nn_ops.relu, 'Relu', False, 5000, False), 373 (nn_ops.relu, 'Relu', True, None, False), 376 (nn_ops.relu, 'Relu', True, 5000, False), 379 (nn_ops.relu, 'Relu', False, None, True), 382 (nn_ops.relu, 'Relu', False, 5000, True), [all …]
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | tensorflow_op_layer_test.py | 40 outputs = gen_nn_ops.relu(x) 55 x = gen_nn_ops.relu(x) 56 outputs = gen_nn_ops.relu(x) 63 x = gen_nn_ops.relu(x) 71 x = gen_nn_ops.relu(x) 72 x = gen_nn_ops.relu(x) 116 x = gen_nn_ops.relu(inputs) 179 outputs = gen_nn_ops.relu(inputs) 195 outputs = gen_nn_ops.relu(inputs) 215 x = gen_nn_ops.relu(x) [all …]
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D | advanced_activations.py | 59 return K.relu(inputs, alpha=self.alpha) 142 pos = K.relu(inputs) 143 neg = -self.alpha * K.relu(-inputs) 316 return K.relu(inputs,
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/external/tensorflow/tensorflow/contrib/tensorrt/custom_plugin_examples/ |
D | plugin_test.py | 45 relu = nn.relu(a, "relu") 47 relu, [1, 2, 2, 1], [1, 2, 2, 1], "VALID", name="max_pool") 53 v = nn.relu(v) 54 v = nn.relu(v)
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/external/tensorflow/tensorflow/core/grappler/optimizers/ |
D | remapper.cc | 85 const NodeDef* relu) in Conv2DWithBiasAddAndRelu() 86 : conv2d(conv2d), bias_add(bias_add), relu(relu) {} in Conv2DWithBiasAddAndRelu() 90 const NodeDef* relu = nullptr; member 122 const NodeDef* relu, float epsilon = 0.0) in Conv2DWithBatchNormAndRelu() 125 relu(relu), in Conv2DWithBatchNormAndRelu() 130 const NodeDef* relu = nullptr; member 262 bool FindConv2DWithBiasAndRelu(const RemapperContext& ctx, const NodeDef* relu, in FindConv2DWithBiasAndRelu() argument 267 if (!relu || !IsRelu(*relu) || HasControlFaninOrFanout(ctx.graph_view, relu)) in FindConv2DWithBiasAndRelu() 271 const auto input_port = GraphView::InputPort(relu, 0); in FindConv2DWithBiasAndRelu() 278 !HaveSameDataType(relu, base.bias_add) || in FindConv2DWithBiasAndRelu() [all …]
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/external/tensorflow/tensorflow/contrib/receptive_field/python/util/ |
D | receptive_field_test.py | 57 nn.relu(l1 + l3, name='output') 85 nn.relu(l1 + l3, name='output') 110 nn.relu(l1 + l3, name='output') 137 nn.relu(l1 + l3, name='output') 160 nn.relu(l2, name='output') 186 nn.relu(l1 + dropout, name='output') 214 nn.relu(l1 + l3, name='output') 242 l4 = nn.relu(l1 + l3) 249 nn.relu(l5 + l6, name='output') 274 l4 = nn.relu(l1 + l3) [all …]
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/external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
D | resnet50.py | 76 x = tf.nn.relu(x) 80 x = tf.nn.relu(x) 86 return tf.nn.relu(x) 151 x = tf.nn.relu(x) 155 x = tf.nn.relu(x) 164 return tf.nn.relu(x) 278 x = tf.nn.relu(x)
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/external/tensorflow/tensorflow/python/compiler/tensorrt/test/ |
D | vgg_block_nchw_test.py | 62 relu = nn.relu(t, "relu") 63 idty = array_ops.identity(relu, "ID")
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D | const_broadcast_test.py | 46 z1 = nn.relu(y1, name='z1') 50 z2 = nn.relu(y2, name='z') 57 nn.relu(y3, name=output_name)
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D | vgg_block_test.py | 56 relu = nn.relu(t, "relu") 57 idty = array_ops.identity(relu, "ID")
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/external/tensorflow/tensorflow/contrib/eager/python/examples/densenet/ |
D | densenet.py | 73 output = self.conv1(tf.nn.relu(output)) 76 output = self.conv2(tf.nn.relu(output)) 109 output = self.conv(tf.nn.relu(output)) 280 output = tf.nn.relu(output) 290 output = tf.nn.relu(output)
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/external/tensorflow/tensorflow/python/kernel_tests/ |
D | relu_op_test.py | 62 tf_relu = nn_ops.relu(np_features) 85 tf_relu = nn_ops.relu(constant_op.constant(inputs, dtypes.qint8)) 98 self.evaluate(nn_ops.relu(inputs)) 106 self.evaluate(nn_ops.relu(inputs)) 117 *gradient_checker_v2.compute_gradient(nn_ops.relu, [x])) 128 y = nn_ops.l2_loss(nn_ops.relu(x)) 166 *gradient_checker_v2.compute_gradient(nn_ops.relu, [x])) 177 y = nn_ops.relu(x) 196 y = nn_ops.relu(x) 212 return nn_ops.relu(x)**2
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/external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/ |
D | nn.py | 25 relu = core.define_unary_op('relu', nn.relu) variable
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D | nn_test.py | 37 ('relu', nn_ops.relu, nn.relu),
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/external/tensorflow/tensorflow/python/layers/ |
D | core_test.py | 46 dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense') 48 self.assertEqual(dense.activation, nn_ops.relu) 55 dense = core_layers.Dense(2, activation=nn_ops.relu) 58 dense = core_layers.Dense(2, activation=nn_ops.relu) 73 dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense') 93 core_layers.Dense(2, activation=nn_ops.relu, name='my_dense')(inputs) 97 dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense') 131 dense = core_layers.Dense(7, activation=nn_ops.relu, name='my_dense') 172 dense = core_layers.Dense(2, activation=nn_ops.relu, name='dense1') 236 inputs, 2, activation=nn_ops.relu, name='my_dense') [all …]
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D | convolutional_test.py | 67 layer = conv_layers.Conv2D(32, [3, 3], activation=nn_ops.relu) 78 output = conv_layers.conv2d(images, 32, [3, 3], activation=nn_ops.relu) 106 layer = conv_layers.Conv2D(32, [3, 3], activation=nn_ops.relu) 151 layer = conv_layers.Conv1D(32, 3, activation=nn_ops.relu) 161 output = conv_layers.conv1d(data, 32, 3, activation=nn_ops.relu) 177 layer = conv_layers.Conv1D(32, 3, activation=nn_ops.relu) 194 layer = conv_layers.Conv3D(32, [3, 3, 3], activation=nn_ops.relu) 205 layer = conv_layers.Conv3D(32, [3, 3, 3], activation=nn_ops.relu) 240 32, [3, 3], activation=nn_ops.relu, use_bias=False) 382 layer = conv_layers.SeparableConv1D(32, 3, activation=nn_ops.relu) [all …]
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/external/tensorflow/tensorflow/examples/tutorials/layers/ |
D | cnn_mnist.py | 43 activation=tf.nn.relu) 61 activation=tf.nn.relu) 78 dense = tf.layers.dense(inputs=pool2_flat, units=1024, activation=tf.nn.relu)
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/external/tensorflow/tensorflow/contrib/specs/python/ |
D | specs_ops.py | 83 Cr = Fun(layers.conv2d, activation_fn=nn_ops.relu) 92 Fr = Fun(layers.fully_connected, activation_fn=nn_ops.relu) 118 Relu = Fun(nn_ops.relu)
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/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
D | cifar10_pruning.py | 196 conv1 = tf.nn.relu(pre_activation, name=scope.name) 218 conv2 = tf.nn.relu(pre_activation, name=scope.name) 240 local3 = tf.nn.relu( 250 local4 = tf.nn.relu(
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/external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
D | mnist_eager_multigpu.py | 55 tf.keras.layers.Conv2D(2, 5, padding="same", activation=tf.nn.relu), 57 tf.keras.layers.Conv2D(4, 5, padding="same", activation=tf.nn.relu), 60 tf.keras.layers.Dense(32, activation=tf.nn.relu),
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/external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/ |
D | neural_nets.py | 63 h = tf.nn.relu(h) 65 h = tf.nn.relu(h)
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/external/tensorflow/tensorflow/examples/tutorials/mnist/ |
D | mnist.py | 64 hidden1 = tf.nn.relu(tf.matmul(images, weights) + biases) 73 hidden2 = tf.nn.relu(tf.matmul(hidden1, weights) + biases)
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/external/tensorflow/tensorflow/python/keras/ |
D | activations.py | 144 def relu(x, alpha=0., max_value=None, threshold=0): function 163 return K.relu(x, alpha=alpha, max_value=max_value, threshold=threshold)
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