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  /external/tensorflow/tensorflow/core/kernels/
relu_op_functor.h 42 // Computes ReluGrad backprops.
47 // backprops: gradients to backpropagate to the Relu inputs.
50 typename TTypes<T>::Tensor backprops) {
54 backprops.device(d) =
76 // Computes Relu6Grad backprops.
80 // backprops: gradients to backpropagate to the Relu6 inputs.
83 typename TTypes<T>::Tensor backprops) {
88 backprops.device(d) = gradients * ((features > static_cast<T>(0)) *
114 // Computes EluGrad backprops.
118 // backprops: gradients to backpropagate to the Elu inputs
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softsign_op.h 44 // Computes SoftsignGrad backprops.
48 // backprops: gradients to backpropagate to the Softsign inputs.
51 typename TTypes<T>::Tensor backprops) {
52 backprops.device(d) =
softplus_op.h 60 // Computes SoftplusGrad backprops.
64 // backprops: gradients to backpropagate to the Softplus inputs.
67 typename TTypes<T>::Tensor backprops) {
68 backprops.device(d) =
relu_op.cc 85 typename TTypes<T>::Tensor backprops); \
98 typename TTypes<T>::Tensor backprops); \
111 typename TTypes<T>::Tensor backprops); \
124 typename TTypes<T>::Tensor backprops); \
conv_grad_ops.h 22 // And we need to compute two backprops: one for input and one for filter. We
25 // Both backprops can be computed as straightforward conv2d.
56 // So when we have backprops for the outputs (we denote them by
59 // The backprops for the input are:
75 // The backprops for the filter are:
softplus_op.cc 109 typename TTypes<T>::Tensor backprops); \
softsign_op.cc 110 typename TTypes<T>::Tensor backprops); \
fake_quant_ops_functor.h 107 Flat<float> backprops) {
119 backprops.device(d) = gradients * between_nudged_min_max;
fake_quant_ops.cc 164 typename TTypes<float>::Flat backprops);
conv_grad_ops_3d.cc 349 // And we need to reverse the filter backprops.
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  /external/tensorflow/tensorflow/core/api_def/base_api/
api_def_EluGrad.pbtxt 17 name: "backprops"
api_def_FakeQuantWithMinMaxArgsGradient.pbtxt 16 name: "backprops"
api_def_Relu6Grad.pbtxt 18 name: "backprops"
api_def_ReluGrad.pbtxt 18 name: "backprops"
api_def_SeluGrad.pbtxt 17 name: "backprops"
api_def_SoftplusGrad.pbtxt 17 name: "backprops"
api_def_SoftsignGrad.pbtxt 17 name: "backprops"
  /external/tensorflow/tensorflow/cc/framework/
gradients.cc 118 // backprops. When pending[i] becomes zero, we collected all
406 std::map<Node*, Output>& backprops = while_backprops_[while_ctx]; local
407 DCHECK(backprops.find(exit_node) == backprops.end());
408 backprops[exit_node] = summed_grads;
410 // Wait until we have all exit nodes' backprops collected before processing
413 if (backprops.size() < while_ctx->exit_nodes().size()) return Status::OK();
416 // backprops. Create the gradient graph for the while loop.
420 for (Node* n : while_ctx->exit_nodes()) dy.push_back(backprops[n]);
438 // Initialize backprops
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  /external/tensorflow/tensorflow/core/graph/
gradients.cc 151 // backprops. When pending[i] becomes zero, we collected all
306 // Initialize backprops.
356 // Backprops along the in edges.
  /external/tensorflow/tensorflow/compiler/tests/
fake_quant_ops_test.py 214 backprops = session.run(outputs, {
219 backprops,
  /external/tensorflow/tensorflow/python/kernel_tests/
conv_ops_test.py 519 # Testing for backprops
547 # "values" consists of two tensors for two backprops
693 # Testing for backprops
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  /external/tensorflow/tensorflow/core/ops/
nn_ops.cc 966 .Output("backprops: T")
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ops.pbtxt     [all...]
  /external/tensorflow/tensorflow/core/ops/compat/
ops_history.v0.pbtxt     [all...]
ops_history.v1.pbtxt     [all...]

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