| /external/tensorflow/tensorflow/python/layers/ |
| D | pooling.py | 22 from tensorflow.python.keras.legacy_tf_layers import pooling
25 AveragePooling1D = pooling.AveragePooling1D
26 average_pooling1d = pooling.average_pooling1d
27 MaxPooling1D = pooling.MaxPooling1D
28 max_pooling1d = pooling.max_pooling1d
29 AveragePooling2D = pooling.AveragePooling2D
30 average_pooling2d = pooling.average_pooling2d
31 MaxPooling2D = pooling.MaxPooling2D
32 max_pooling2d = pooling.max_pooling2d
33 AveragePooling3D = pooling.AveragePooling3D
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| D | layers.py | 61 from tensorflow.python.layers.pooling import AveragePooling1D
62 from tensorflow.python.layers.pooling import MaxPooling1D
63 from tensorflow.python.layers.pooling import AveragePooling2D
64 from tensorflow.python.layers.pooling import MaxPooling2D
65 from tensorflow.python.layers.pooling import AveragePooling3D
66 from tensorflow.python.layers.pooling import MaxPooling3D
68 from tensorflow.python.layers.pooling import average_pooling1d
69 from tensorflow.python.layers.pooling import max_pooling1d
70 from tensorflow.python.layers.pooling import average_pooling2d
71 from tensorflow.python.layers.pooling import max_pooling2d
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_FractionalAvgPool.pbtxt | 12 output tensor after fractional avg pooling.
18 row pooling sequence, needed to calculate gradient.
24 column pooling sequence, needed to calculate gradient.
32 pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
33 must be 1.0 because we don't allow pooling on batch and channels
34 dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
41 When set to True, generates the pooling sequence in a
50 When set to True, it means when pooling, the values at the boundary
51 of adjacent pooling cells are used by both cells. For example:
57 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
[all …]
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| D | api_def_FractionalMaxPool.pbtxt | 12 output tensor after fractional max pooling.
18 row pooling sequence, needed to calculate gradient.
24 column pooling sequence, needed to calculate gradient.
32 pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements
33 must be 1.0 because we don't allow pooling on batch and channels
34 dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions
41 When set to True, generates the pooling sequence in a
50 When set to True, it means when pooling, the values at the boundary
51 of adjacent pooling cells are used by both cells. For example:
57 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
[all …]
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| D | api_def_FractionalAvgPoolGrad.pbtxt | 20 row pooling sequence, form pooling region with
27 column pooling sequence, form pooling region with
40 When set to True, it means when pooling, the values at the boundary
41 of adjacent pooling cells are used by both cells. For example:
47 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
48 The result would be [41/3, 26/3] for fractional avg pooling.
55 out_backprop to those indices that form the same pooling cell. Therefore, we
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| D | api_def_FractionalMaxPoolGrad.pbtxt | 26 row pooling sequence, form pooling region with
33 column pooling sequence, form pooling region with
46 When set to True, it means when pooling, the values at the boundary
47 of adjacent pooling cells are used by both cells. For example:
53 If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice.
54 The result would be [20, 16] for fractional max pooling.
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.applications.pbtxt | 65 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
69 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
73 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
77 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
81 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
85 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
89 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
93 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
97 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
101 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
[all …]
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| D | tensorflow.keras.applications.efficientnet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
17 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
21 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
25 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
29 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
33 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.resnet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.densenet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.resnet_v2.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.applications.pbtxt | 65 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
69 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
73 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
77 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
81 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
85 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
89 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
93 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
97 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
101 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
[all …]
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| D | tensorflow.keras.applications.efficientnet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
17 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
21 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
25 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
29 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
33 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.densenet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.resnet.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| D | tensorflow.keras.applications.resnet_v2.pbtxt | 5 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
9 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
13 …argspec: "args=[\'include_top\', \'weights\', \'input_tensor\', \'input_shape\', \'pooling\', \'cl…
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| /external/tensorflow/tensorflow/python/keras/applications/ |
| D | efficientnet.py | 208 pooling=None, argument
378 if pooling == 'avg':
380 elif pooling == 'max':
527 pooling=None, argument
541 pooling=pooling,
553 pooling=None, argument
567 pooling=pooling,
579 pooling=None, argument
593 pooling=pooling,
605 pooling=None, argument
[all …]
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| D | resnet_v2.py | 38 pooling=None, argument
57 pooling,
69 pooling=None, argument
88 pooling,
100 pooling=None, argument
119 pooling,
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| D | densenet.py | 135 pooling=None, argument
252 if pooling == 'avg':
254 elif pooling == 'max':
327 pooling=None, argument
331 input_shape, pooling, classes)
340 pooling=None, argument
344 input_shape, pooling, classes)
353 pooling=None, argument
357 input_shape, pooling, classes)
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| D | resnet.py | 68 pooling=None, argument
191 if pooling == 'avg':
193 elif pooling == 'max':
460 pooling=None, argument
472 input_tensor, input_shape, pooling, classes, **kwargs)
481 pooling=None, argument
493 input_tensor, input_shape, pooling, classes, **kwargs)
502 pooling=None, argument
514 input_tensor, input_shape, pooling, classes, **kwargs)
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| D | nasnet.py | 74 pooling=None, argument
265 if pooling == 'avg':
267 elif pooling == 'max':
327 pooling=None, argument
393 pooling=pooling,
404 pooling=None, argument
470 pooling=pooling,
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | pooling.cc | 38 namespace pooling { namespace
461 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_AVERAGE_POOL_REF()
462 pooling::GenericPrepare<pooling::kAverage>, in Register_AVERAGE_POOL_REF()
463 pooling::AverageEval<pooling::kReference>}; in Register_AVERAGE_POOL_REF()
468 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_MAX_POOL_REF()
469 pooling::GenericPrepare<pooling::kMax>, in Register_MAX_POOL_REF()
470 pooling::MaxEval<pooling::kReference>}; in Register_MAX_POOL_REF()
475 static TfLiteRegistration r = {pooling::Init, pooling::Free, in Register_L2_POOL_REF()
476 pooling::GenericPrepare<pooling::kL2>, in Register_L2_POOL_REF()
477 pooling::L2Eval<pooling::kReference>}; in Register_L2_POOL_REF()
[all …]
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | __init__.py | 188 from tensorflow.python.keras.layers.pooling import MaxPooling1D
189 from tensorflow.python.keras.layers.pooling import MaxPooling2D
190 from tensorflow.python.keras.layers.pooling import MaxPooling3D
191 from tensorflow.python.keras.layers.pooling import AveragePooling1D
192 from tensorflow.python.keras.layers.pooling import AveragePooling2D
193 from tensorflow.python.keras.layers.pooling import AveragePooling3D
194 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling1D
195 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling2D
196 from tensorflow.python.keras.layers.pooling import GlobalAveragePooling3D
197 from tensorflow.python.keras.layers.pooling import GlobalMaxPooling1D
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| D | pooling_test.py | 38 keras.layers.pooling.GlobalMaxPooling1D, input_shape=(3, 4, 5))
40 keras.layers.pooling.GlobalMaxPooling1D,
44 keras.layers.pooling.GlobalAveragePooling1D, input_shape=(3, 4, 5))
46 keras.layers.pooling.GlobalAveragePooling1D,
116 keras.layers.pooling.GlobalMaxPooling2D,
120 keras.layers.pooling.GlobalMaxPooling2D,
124 keras.layers.pooling.GlobalAveragePooling2D,
128 keras.layers.pooling.GlobalAveragePooling2D,
134 keras.layers.pooling.GlobalMaxPooling3D,
138 keras.layers.pooling.GlobalMaxPooling3D,
[all …]
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| /external/tensorflow/tensorflow/lite/micro/kernels/ |
| D | pooling.cc | 27 namespace pooling { namespace
246 return {/*init=*/pooling::Init, in Register_AVERAGE_POOL_2D()
248 /*prepare=*/pooling::Prepare, in Register_AVERAGE_POOL_2D()
249 /*invoke=*/pooling::AverageEval, in Register_AVERAGE_POOL_2D()
257 return {/*init=*/pooling::Init, in Register_MAX_POOL_2D()
259 /*prepare=*/pooling::Prepare, in Register_MAX_POOL_2D()
260 /*invoke=*/pooling::MaxEval, in Register_MAX_POOL_2D()
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