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  /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/
halton_sequence_impl.py 152 # weights of the starting integer when expressed in the (prime) base for
176 weights = radixes ** capped_exponents
177 coeffs = math_ops.floor_div(indices, weights)
180 return math_ops.reduce_sum(coeffs / weights, axis=-1)
  /external/tensorflow/tensorflow/contrib/boosted_trees/proto/
learner.proto 55 // weights updates in functional space, and thus we can use averaging of weight
  /external/tensorflow/tensorflow/contrib/eager/python/examples/gan/
mnist_test.py 94 # Using random weights. This will generate garbage.
  /external/tensorflow/tensorflow/contrib/factorization/g3doc/
wals.md 31 \Rbb^n$$ and $$C \in \Rbb^m$$ are the row and column weights respectively.
  /external/tensorflow/tensorflow/contrib/kfac/examples/
mlp.py 53 params: Tuple of (weights, bias), parameters for this layer.
63 # layer.weights is a list. This converts it a (hashable) tuple.
83 # activations, weights, and bias.
137 # - train_op: Update the weights with the minibatch's gradient.
  /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ops/
sparse_feature_column.py 32 Feature weights are optional, and are treated as `1.0f` if missing.
  /external/tensorflow/tensorflow/contrib/lite/models/smartreply/ops/
extract_feature.cc 22 // Output[1]: Weights. float[num of input]
  /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/
decision_node_evaluator.cc 77 feature_weights_.push_back(test.oblique().weights(i));
  /external/tensorflow/tensorflow/core/kernels/
squared-loss.h 27 // the update rule when the example weights are equal to 1.0.
  /external/tensorflow/tensorflow/core/ops/
sdca_ops.cc 72 .Input("weights: Ref(num_features * float)")
  /external/tensorflow/tensorflow/examples/label_image/
README.md 16 The TensorFlow `GraphDef` that contains the model definition and weights is not
  /external/tensorflow/tensorflow/examples/multibox_detector/
README.md 15 The TensorFlow `GraphDef` that contains the model definition and weights is not
  /external/tensorflow/tensorflow/python/estimator/canned/
baseline.py 87 weights. It will be multiplied by the loss of the example.
149 weights. It will be multiplied by the loss of the example.
240 weights. It will be multiplied by the loss of the example.
336 weights. It will be multiplied by the loss of the example.
  /external/tensorflow/tensorflow/tools/api/golden/
tensorflow.layers.-average-pooling1-d.pbtxt 80 name: "weights"
tensorflow.layers.-average-pooling2-d.pbtxt 80 name: "weights"
tensorflow.layers.-average-pooling3-d.pbtxt 80 name: "weights"
tensorflow.layers.-batch-normalization.pbtxt 79 name: "weights"
tensorflow.layers.-conv1-d.pbtxt 80 name: "weights"
tensorflow.layers.-conv2-d-transpose.pbtxt 81 name: "weights"
tensorflow.layers.-conv2-d.pbtxt 80 name: "weights"
tensorflow.layers.-conv3-d-transpose.pbtxt 81 name: "weights"
tensorflow.layers.-conv3-d.pbtxt 80 name: "weights"
tensorflow.layers.-dense.pbtxt 79 name: "weights"
tensorflow.layers.-dropout.pbtxt 79 name: "weights"
tensorflow.layers.-flatten.pbtxt 79 name: "weights"

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