| /external/tensorflow/tensorflow/core/kernels/ |
| D | batch_norm_op.cc | 36 float variance_epsilon; in BatchNormOp() local
38 context->GetAttr("variance_epsilon", &variance_epsilon)); in BatchNormOp()
39 variance_epsilon_ = T(variance_epsilon); in BatchNormOp()
86 float variance_epsilon; in BatchNormGradOp() local
88 context->GetAttr("variance_epsilon", &variance_epsilon)); in BatchNormGradOp()
89 variance_epsilon_ = T(variance_epsilon); in BatchNormGradOp()
184 T variance_epsilon, bool scale_after_normalization, \
229 typename TTypes<T, 4>::ConstTensor out_backprop, T variance_epsilon, \
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| D | batch_norm_op.h | 32 typename TTypes<T>::ConstVec gamma, T variance_epsilon, in operator()
55 ((var + var.constant(variance_epsilon)).rsqrt() * gamma) in operator()
64 ((var + var.constant(variance_epsilon)).rsqrt()) in operator()
80 T variance_epsilon, bool scale_after_normalization, in operator()
117 scratch1.device(d) = (var + var.constant(variance_epsilon)).rsqrt(); in operator()
143 (var + var.constant(variance_epsilon)); in operator()
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| D | quantized_batch_norm_op.cc | 37 float variance_epsilon, bool scale_after_normalization, in ReferenceBatchNorm() argument
69 sqrtf(var_value + variance_epsilon)) * in ReferenceBatchNorm()
74 sqrtf(var_value + variance_epsilon)) + in ReferenceBatchNorm()
100 float variance_epsilon, bool scale_after_normalization, in FixedPointBatchNorm() argument
133 scale_value = (1.0f / sqrtf(var_value + variance_epsilon)) * gamma_value; in FixedPointBatchNorm()
135 scale_value = (1.0f / sqrtf(var_value + variance_epsilon)); in FixedPointBatchNorm()
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| D | quantized_instance_norm.cc | 140 float variance_epsilon, float* minimum, float* maximum) { in MinAndMax() argument
143 const float32x4_t eps = vdupq_n_f32(variance_epsilon); in MinAndMax()
196 const float* variance_ptr, float variance_epsilon, in InstanceNorm() argument
198 const float32x4_t eps = vdupq_n_f32(variance_epsilon); in InstanceNorm()
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | BatchNormWithGlobalNormalization.pbtxt | 50 name: "variance_epsilon"
112 name: "variance_epsilon"
175 name: "variance_epsilon"
238 name: "variance_epsilon"
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| D | BatchNormWithGlobalNormalizationGrad.pbtxt | 66 name: "variance_epsilon"
144 name: "variance_epsilon"
223 name: "variance_epsilon"
302 name: "variance_epsilon"
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| D | QuantizedInstanceNorm.pbtxt | 62 name: "variance_epsilon"
137 name: "variance_epsilon"
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| D | QuantizedBatchNormWithGlobalNormalization.pbtxt | 102 name: "variance_epsilon"
211 name: "variance_epsilon"
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | BatchNormWithGlobalNormalization.pbtxt | 50 name: "variance_epsilon"
112 name: "variance_epsilon"
175 name: "variance_epsilon"
238 name: "variance_epsilon"
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| D | BatchNormWithGlobalNormalizationGrad.pbtxt | 66 name: "variance_epsilon"
144 name: "variance_epsilon"
223 name: "variance_epsilon"
302 name: "variance_epsilon"
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| D | QuantizedInstanceNorm.pbtxt | 62 name: "variance_epsilon"
137 name: "variance_epsilon"
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| D | QuantizedBatchNormWithGlobalNormalization.pbtxt | 102 name: "variance_epsilon"
211 name: "variance_epsilon"
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| /external/tensorflow/tensorflow/compiler/mlir/lite/transforms/ |
| D | prepare_patterns.td | 32 …$t, $m, $v, $beta, $gamma, F32Attr:$variance_epsilon, ConstBoolAttrFalse:$scale_after_normalizatio…
34 (TF_MulOp $t, (TF_RsqrtOp:$rsqrt (TF_AddOp $v, (TF_ConstOp $variance_epsilon)))),
38 …$t, $m, $v, $beta, $gamma, F32Attr:$variance_epsilon, ConstBoolAttrTrue:$scale_after_normalization…
40 … (TF_MulOp $t, (TF_MulOp:$mul (TF_RsqrtOp (TF_AddOp $v, (TF_ConstOp $variance_epsilon))), $gamma)),
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| /external/tensorflow/tensorflow/tools/graph_transforms/ |
| D | fold_old_batch_norms.cc | 74 const float variance_epsilon = batch_norm_node.attr().at(epsilon_attr).f(); in GetScaleAndOffsetValues() local
89 (1.0f / sqrtf(variance.flat<float>()(i) + variance_epsilon)) * in GetScaleAndOffsetValues()
95 (1.0f / sqrtf(variance.flat<float>()(i) + variance_epsilon)); in GetScaleAndOffsetValues()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_impl.py | 1518 variance_epsilon, argument
1573 inv = math_ops.rsqrt(variance + variance_epsilon)
1696 variance_epsilon=None, argument
1740 else None, variance_epsilon, name)
1751 variance_epsilon, argument
1789 variance_epsilon=variance_epsilon,
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_QuantizedInstanceNorm.pbtxt | 60 name: "variance_epsilon"
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| D | api_def_BatchNormWithGlobalNormalization.pbtxt | 41 name: "variance_epsilon"
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| D | api_def_BatchNormWithGlobalNormalizationGrad.pbtxt | 70 name: "variance_epsilon"
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| D | api_def_QuantizedBatchNormWithGlobalNormalization.pbtxt | 101 name: "variance_epsilon"
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| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/ |
| D | graph-version-info.pbtxt | 159 key: "variance_epsilon"
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.nn.pbtxt | 45 …argspec: "args=[\'input\', \'mean\', \'variance\', \'beta\', \'gamma\', \'variance_epsilon\', \'sc…
49 …argspec: "args=[\'x\', \'mean\', \'variance\', \'offset\', \'scale\', \'variance_epsilon\', \'name…
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| /external/tensorflow/tensorflow/core/grappler/optimizers/ |
| D | remapper.cc | 1551 NodeDef variance_epsilon; in IsCpuCompatibleDataType() local
1555 variance_epsilon_name, TensorValue(&value), &variance_epsilon)); in IsCpuCompatibleDataType()
1556 variance_epsilon.set_device(fused_node.device()); in IsCpuCompatibleDataType()
1557 mutation->AddNode(std::move(variance_epsilon), &status); in IsCpuCompatibleDataType()
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.nn.pbtxt | 41 …argspec: "args=[\'t\', \'m\', \'v\', \'beta\', \'gamma\', \'variance_epsilon\', \'scale_after_norm…
45 …argspec: "args=[\'x\', \'mean\', \'variance\', \'offset\', \'scale\', \'variance_epsilon\', \'name…
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | normalization.py | 1241 variance_epsilon=self.epsilon)
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| /external/tensorflow/tensorflow/compiler/mlir/lite/tests/ |
| D | prepare-tf.mlir | 105 …lNormalization"(%t, %m, %v, %beta, %gamma) {T = "tfdtype$DT_FLOAT", variance_epsilon = 0.001 : f32…
120 …lNormalization"(%t, %m, %v, %beta, %gamma) {T = "tfdtype$DT_FLOAT", variance_epsilon = 0.001 : f32…
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