HomeSort by relevance Sort by last modified time
    Searched refs:bn_op (Results 1 - 2 of 2) sorted by null

  /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/
resolve_batch_normalization.cc 33 const auto* bn_op = local
36 const auto& mean_array = model->GetArray(bn_op->inputs[1]);
37 const auto& multiplier_array = model->GetArray(bn_op->inputs[2]);
38 const auto& offset_array = model->GetArray(bn_op->inputs[3]);
40 CHECK(IsConstantParameterArray(*model, bn_op->inputs[1]) &&
41 IsConstantParameterArray(*model, bn_op->inputs[2]) &&
42 IsConstantParameterArray(*model, bn_op->inputs[3]))
56 AvailableArrayName(*model, bn_op->outputs[0] + "_mul");
58 AvailableArrayName(*model, bn_op->outputs[0] + "_add");
61 mul_op->inputs = {bn_op->inputs[0], mul_param_name}
    [all...]
  /external/tensorflow/tensorflow/contrib/quantize/python/
fold_batch_norms.py 78 # `bn_op`. The '/' (i.e. `sep`) ensures that we reuse the existing scope
86 match.variance_tensor + match.bn_op.get_attr('epsilon'))
196 bn_op = match_result.get_op(batch_norm_pattern)
197 batch_epsilon_tensor = bn_op.get_attr('epsilon')
201 output_tensor = bn_op.outputs[0]
217 # variance_tensor point to 1st and 2nd (0-based) output of bn_op,
218 # respectively; when is_training is false, they point to bn_op's inputs.
219 is_training = bn_op.get_attr('is_training')
226 bn_op._set_attr(
230 mean_tensor = bn_op.outputs[1
840 def bn_op(self): member in class:_BatchNormMatch
    [all...]

Completed in 79 milliseconds