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/external/tensorflow/tensorflow/contrib/model_pruning/
__init__.py	15 """Model pruning implementation in tensorflow.""" 28 from tensorflow.contrib.model_pruning.python.pruning import apply_mask 29 from tensorflow.contrib.model_pruning.python.pruning import get_masked_weights 30 from tensorflow.contrib.model_pruning.python.pruning import get_masks 31 from tensorflow.contrib.model_pruning.python.pruning import get_pruning_hparams 32 from tensorflow.contrib.model_pruning.python.pruning import get_thresholds 33 from tensorflow.contrib.model_pruning.python.pruning import get_weight_sparsity 34 from tensorflow.contrib.model_pruning.python.pruning import get_weights 35 from tensorflow.contrib.model_pruning.python.pruning import Pruning     [all...]
/external/tensorflow/tensorflow/contrib/model_pruning/python/layers/
rnn_cells_test.py	21 from tensorflow.contrib.model_pruning.python import pruning 50 self.assertEqual(len(pruning.get_masks()), expected_num_masks) 51 self.assertEqual(len(pruning.get_masked_weights()), expected_num_masks) 52 self.assertEqual(len(pruning.get_thresholds()), expected_num_masks) 53 self.assertEqual(len(pruning.get_weights()), expected_num_masks) 55 for mask in pruning.get_masks(): 57 for weight in pruning.get_weights(): 74 self.assertEqual(len(pruning.get_masks()), expected_num_masks) 75 self.assertEqual(len(pruning.get_masked_weights()), expected_num_masks) 76 self.assertEqual(len(pruning.get_thresholds()), expected_num_masks     [all...]
/external/tensorflow/tensorflow/contrib/model_pruning/python/
pruning_test.py	15 """Tests for the key functions in pruning library.""" 23 from tensorflow.contrib.model_pruning.python import pruning 50 self.pruning_hparams = pruning.get_pruning_hparams().parse( 54 p = pruning.Pruning(self.pruning_hparams) 64 p = pruning.Pruning(spec=self.pruning_hparams, sparsity=self.sparsity) 71 p = pruning.Pruning(spec=self.pruning_hparams, sparsity=self.sparsity) 72 p_copy = pruning.Pruning     [all...]
/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
cifar10_train.py	50 from tensorflow.contrib.model_pruning.python import pruning 74 # Parse pruning hyperparameters 75 pruning_hparams = pruning.get_pruning_hparams().parse(FLAGS.pruning_hparams) 77 # Create a pruning object using the pruning hyperparameters 78 pruning_obj = pruning.Pruning(pruning_hparams, global_step=global_step) 83 # the pruning spec proto 146 help="""Comma separated list of pruning-related hyperparameters""")
cifar10_pruning.py	15 """Builds the CIFAR-10 network with additional variables to support pruning. 46 from tensorflow.contrib.model_pruning.python import pruning 185 # variables to the layer by calling the pruning.apply_mask() function. 193 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)),
/prebuilts/go/darwin-x86/src/runtime/pprof/internal/profile/
prune.go	56 // pruning everything.
/prebuilts/go/linux-x86/src/runtime/pprof/internal/profile/
prune.go	56 // pruning everything.
/prebuilts/go/darwin-x86/src/cmd/vendor/github.com/google/pprof/profile/
prune.go	96 // pruning everything.
/prebuilts/go/linux-x86/src/cmd/vendor/github.com/google/pprof/profile/
prune.go	96 // pruning everything.
/external/ImageMagick/www/api/
morphology.php	107 <p>AcquireKernelBuiltIn() returned one of the 'named' built-in types of kernels used for special purposes such as gaussian blurring, skeleton pruning, and edge distance determination.</p> 254 <dd> Peak:radius1,radius2 Find any peak larger than the pixels the fall between the two radii. The default ring of pixels is as per "Ring". Edges Find flat orthogonal edges of a binary shape Corners Find 90 degree corners of a binary shape Diagonals:type A special kernel to thin the 'outside' of diagonals LineEnds:type Find end points of lines (for pruning a skeletion) Two types of lines ends (default to both) can be searched for Type 0: All line ends Type 1: single kernel for 4-conneected line ends Type 2: single kernel for simple line ends LineJunctions Find three line junctions (within a skeletion) Type 0: all line junctions Type 1: Y Junction kernel Type 2: Diagonal T Junction kernel Type 3: Orthogonal T Junction kernel Type 4: Diagonal X Junction kernel Type 5: Orthogonal + Junction kernel Ridges:type Find single pixel ridges or thin lines Type 1: Fine single pixel thick lines and ridges Type 2: Find two pixel thick lines and ridges ConvexHull Octagonal Thickening Kernel, to generate convex hulls of 45 degrees Skeleton:type Traditional skeleton generating kernels. Type 1: Tradional Skeleton kernel (4 connected skeleton) Type 2: HIPR2 Skeleton kernel (8 connected skeleton) Type 3: Thinning skeleton based on a ressearch paper by Dan S. Bloomberg (Default Type) ThinSE:type A huge variety of Thinning Kernels designed to preserve conectivity. many other kernel sets use these kernels as source definitions. Type numbers are 41-49, 81-89, 481, and 482 which are based on the super and sub notations used in the source research paper. </dd>     [all...]
/prebuilts/go/darwin-x86/src/cmd/link/internal/ld/
deadcode.go	21 // This flood fill is wrapped in logic for pruning unused methods.
/prebuilts/go/linux-x86/src/cmd/link/internal/ld/
deadcode.go	21 // This flood fill is wrapped in logic for pruning unused methods.
/external/tensorflow/tensorflow/go/op/
wrappers.go	[all...]

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