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  /external/tensorflow/tensorflow/python/layers/
maxout.py 47 axis: The dimension where max pooling will be performed. Default is the
52 A `Tensor` representing the results of the pooling operation.
77 axis: The dimension where max pooling will be performed. Default is the
82 A `Tensor` representing the results of the pooling operation.
  /frameworks/base/core/java/android/os/
PooledStringReader.java 20 * Helper class for reading pooling strings from a Parcel. It must be used
  /external/tensorflow/tensorflow/python/keras/_impl/keras/applications/
vgg16.py 59 pooling=None,
89 pooling: Optional pooling mode for feature extraction
94 - `avg` means that global average pooling
98 - `max` means that global max pooling will
197 if pooling == 'avg':
199 elif pooling == 'max':
vgg19.py 59 pooling=None,
89 pooling: Optional pooling mode for feature extraction
94 - `avg` means that global average pooling
98 - `max` means that global max pooling will
206 if pooling == 'avg':
208 elif pooling == 'max':
nasnet_test.py 38 pooling='avg')
63 pooling='avg')
  /external/tensorflow/tensorflow/core/kernels/
pooling_ops_common.cc 58 // We only support 2D pooling across width/height and depthwise
59 // pooling, not a combination.
63 "MaxPooling supports exactly one of pooling across depth "
64 "or pooling across width/height."));
76 // Our current version of depthwise max pooling does not support
81 errors::Unimplemented("Depthwise max pooling requires the depth "
85 errors::Unimplemented("Depthwise max pooling requires the depth "
93 errors::Unimplemented("Depthwise max pooling is currently "
103 // Spatial pooling
107 // Depthwise pooling
    [all...]
mkl_maxpooling_op.cc 65 errors::Unimplemented("Pooling is not yet supported on the "
89 errors::Unimplemented("Depthwise max pooling not supported by MKL"));
96 // Extract the parameters for the op from the pooling specs
224 "Pooling is not yet supported on the batch dimension."));
255 errors::Unimplemented("Depthwise max pooling not supported by MKL"));
262 // Extract the parameters for the op from the pooling specs
330 // primitives for the max pooling fwd prop
431 // We create the layout for max pooling fwd prop tmp output here
505 // In Max Pooling, MKLDNN does not allow passing workspace as NULL.
524 // initialize variables for the pooling o
    [all...]
eigen_pooling_test.cc 44 // Max pooling using a 4x4 window and a stride of 1.
93 // Max pooling using a 4x4 window and a stride of 1.
146 // Max pooling using a 4x3x2 window and a stride of 1.
206 // Max pooling using a 4x3x2 window and a stride of 1.
266 // Max pooling using a 4x3x2 window and a stride of 1.
328 // Max pooling using a 4x3x2 window and a stride of 1.
390 // Max pooling using a 4x3x2 window and a stride of 1.
468 // Max pooling using a 4x3x2 window and a stride of 1.
540 // Max pooling using a 3x3 window and a stride of 2.
589 // Max pooling using a 3x3 window and a stride of 2
    [all...]
fractional_pool_common.cc 29 // pseudo random pooling region:
48 // In addition, when extending the pooling sequence generation process for
104 // This is a case that regular pooling can handle, just return diff with
  /external/tensorflow/tensorflow/docs_src/tutorials/
layers.md 56 * **Pooling layers**, which
59 feature map in order to decrease processing time. A commonly used pooling
60 algorithm is max pooling, which extracts subregions of the feature map
66 pooling layers. In a dense layer, every node in the layer is connected to
71 pooling layer. The last convolutional module is followed by one or more dense
92 2. **Pooling Layer #1**: Performs max pooling with a 2x2 filter and stride of 2
96 4. **Pooling Layer #2**: Again, performs max pooling with a 2x2 filter and
109 * `max_pooling2d()`. Constructs a two-dimensional pooling layer using th
    [all...]
  /external/tensorflow/tensorflow/compiler/tests/
pooling_ops_3d_test.py 15 """Functional tests for 3d pooling operations."""
35 del outputs # Unused by average-pooling gradients.
48 """Verifies the output values of the pooling function.
137 # Test pooling on a larger input, with different stride and kernel
140 # Simulate max pooling in numpy to get the expected output.
192 """Verifies the output values of the pooling gradient function.
195 pool_func: Forward pooling function
196 pool_grad_func: Pooling gradient function for pool_grad_func
222 # Use the Tensorflow CPU pooling gradient to compute the expected input
  /external/tensorflow/tensorflow/python/profiler/internal/
flops_registry.py 36 # Convolution and pooling
288 # Convolution and pooling
294 """Verifies data format for pooling and convolutional operations."""
301 """Common code which compute flops for pooling operations."""
302 # compute flops for average and max pooling
305 # Pooling declaration:
316 # Pooling implenetation:
340 # Pooling gradient implementation:
346 # TensorFlow multiply each element of pooling window by coefficient,
  /external/tensorflow/tensorflow/python/kernel_tests/
pool_test.py 15 """Tests for unified pooling functionality in tensorflow.ops.nn."""
41 """Numpy implementation of pooling along a single axis.
49 axis: axis along which to perform pooling.
50 window_size: int >= 1. Size of pooling window within axis.
58 pooling output array of rank N+2.
85 raise ValueError("Unsupported pooling type: %r" % (pooling_type,))
106 """Numpy implementation of pooling.
123 pooling output array of rank N+2.
  /external/tensorflow/tensorflow/tools/api/golden/
tensorflow.layers.-average-pooling1-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling1D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling1D\'>"
tensorflow.layers.-average-pooling2-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling2D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling2D\'>"
tensorflow.layers.-average-pooling3-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling3D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling3D\'>"
tensorflow.layers.-max-pooling1-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.MaxPooling1D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling1D\'>"
tensorflow.layers.-max-pooling2-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.MaxPooling2D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling2D\'>"
tensorflow.layers.-max-pooling3-d.pbtxt 3 is_instance: "<class \'tensorflow.python.layers.pooling.MaxPooling3D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling3D\'>"
tensorflow.keras.layers.-average-pooling1-d.pbtxt 3 is_instance: "<class \'tensorflow.python.keras._impl.keras.layers.pooling.AveragePooling1D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling1D\'>"
5 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling1D\'>"
tensorflow.keras.layers.-average-pooling2-d.pbtxt 3 is_instance: "<class \'tensorflow.python.keras._impl.keras.layers.pooling.AveragePooling2D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling2D\'>"
5 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling2D\'>"
tensorflow.keras.layers.-average-pooling3-d.pbtxt 3 is_instance: "<class \'tensorflow.python.keras._impl.keras.layers.pooling.AveragePooling3D\'>"
4 is_instance: "<class \'tensorflow.python.layers.pooling.AveragePooling3D\'>"
5 is_instance: "<class \'tensorflow.python.layers.pooling._Pooling3D\'>"
  /libcore/ojluni/src/main/java/javax/sql/
ConnectionEventListener.java 34 * connection pooling component. A connection pooling component will
PooledConnection.java 41 * that manages the pooling of connections.
44 * it gets back a <code>Connection</code> object. If connection pooling is
60 * method <code>close</code>. When connection pooling is being done,
80 * method <code>close</code>. When <code>Statement</code> pooling is being done,
  /external/apache-xml/src/main/java/org/apache/xml/utils/
StringBufferPool.java 25 * String buffers are good candidates for pooling, because of

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