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Searched refs:apply_mask (Results 1 – 8 of 8) sorted by relevance

/external/tensorflow/tensorflow/contrib/model_pruning/python/
Dpruning_test.py93 masked_weights = pruning.apply_mask(weights,
104 masked_weights = pruning.apply_mask(weights)
175 masked_weights = pruning.apply_mask(
195 masked_weights = pruning.apply_mask(weights)
227 _ = pruning.apply_mask(w1)
231 _ = pruning.apply_mask(w2)
Dpruning.py88 def apply_mask(x, scope=''): function
/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
Dcifar10_pruning.py193 images, pruning.apply_mask(kernel, scope), [1, 1, 1, 1], padding='SAME')
215 norm1, pruning.apply_mask(kernel, scope), [1, 1, 1, 1], padding='SAME')
241 tf.matmul(reshape, pruning.apply_mask(weights, scope)) + biases,
251 tf.matmul(local3, pruning.apply_mask(weights, scope)) + biases,
265 tf.matmul(local4, pruning.apply_mask(weights, scope)),
/external/tensorflow/tensorflow/contrib/model_pruning/
D__init__.py28 from tensorflow.contrib.model_pruning.python.pruning import apply_mask
DREADME.md21 the layer with the `apply_mask` function provided in
26 conv = tf.nn.conv2d(images, pruning.apply_mask(weights), stride, padding)
/external/tensorflow/tensorflow/python/keras/engine/
Dpartial_batch_padding_handler.py89 def apply_mask(self, prediction_result): member in PartialBatchPaddingHandler
Dtraining_distributed.py716 prediction_result = padding_handler.apply_mask(prediction_result)
/external/ImageMagick/coders/
Dxcf.c148 apply_mask, member
937 outLayer->apply_mask = ReadBlobMSBLong(image); in ReadOneLayer()
1079 layer->mask->apply_mask = apply_mask; in ReadOneLayer()