Searched refs:Attention (Results 1 – 25 of 26) sorted by relevance
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | dense_attention_test.py | 183 attention_layer = dense_attention.Attention()
199 attention_layer = dense_attention.Attention()
219 attention_layer = dense_attention.Attention()
235 attention_layer = dense_attention.Attention(use_scale=True)
254 attention_layer = dense_attention.Attention()
273 attention_layer = dense_attention.Attention()
286 attention_layer = dense_attention.Attention()
314 attention_layer = dense_attention.Attention()
346 attention_layer = dense_attention.Attention()
386 attention_layer = dense_attention.Attention()
[all …]
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| D | dense_attention.py | 225 class Attention(BaseDenseAttention): class
326 super(Attention, self).__init__(**kwargs)
340 super(Attention, self).build(input_shape)
358 base_config = super(Attention, self).get_config()
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| D | __init__.py | 133 from tensorflow.python.keras.layers.dense_attention import Attention
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| /external/libcups/templates/fr/ |
| D | class-confirm.tmpl | 3 <P><B>Attention:</B> Êtes-vous sur(e) de vouloir supprimer la classe
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| /external/tensorflow/tensorflow/python/keras/mixed_precision/ |
| D | layer_correctness_test.py | 103 ('Attention', dense_attention.Attention, [(2, 2, 3), (2, 3, 3),
143 ('AttentionLayerCausal', lambda: dense_attention.Attention(causal=True), [
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.layers.-attention.pbtxt | 1 path: "tensorflow.keras.layers.Attention"
3 is_instance: "<class \'tensorflow.python.keras.layers.dense_attention.Attention\'>"
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| D | tensorflow.keras.layers.pbtxt | 28 name: "Attention"
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.layers.-attention.pbtxt | 1 path: "tensorflow.keras.layers.Attention"
3 is_instance: "<class \'tensorflow.python.keras.layers.dense_attention.Attention\'>"
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| D | tensorflow.keras.layers.pbtxt | 28 name: "Attention"
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| /external/mesa3d/docs/ |
| D | license.rst | 60 Attention, Contributors
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| /external/tensorflow/tensorflow/python/keras/benchmarks/layer_benchmarks/ |
| D | layer_benchmarks_test.py | 166 ("Attention_small_shape", tf.keras.layers.Attention,
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| /external/llvm-project/clang/include/clang/AST/ |
| D | CommentCommands.td | 130 def Attention : BlockCommand<"attention">;
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| /external/clang/include/clang/AST/ |
| D | CommentCommands.td | 128 def Attention : BlockCommand<"attention">;
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| /external/aac/ |
| D | NOTICE | 86 Attention: Audio and Multimedia Departments - FDK AAC LL
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| /external/ltp/testcases/network/stress/ |
| D | README | 60 Attention for HTTP/FTP stress tests
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| /external/python/cpython2/Doc/library/ |
| D | turtle.rst | 586 Attention: *speed* = 0 means that *no* animation takes
1712 "world coordinates". **Attention**: in this mode angles appear distorted if
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| /external/python/cpython3/Doc/library/ |
| D | turtle.rst | 626 Attention: *speed* = 0 means that *no* animation takes
1918 "world coordinates". **Attention**: in this mode angles appear distorted if
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| /external/llvm-project/llvm/docs/ |
| D | Coroutines.rst | 1719 Areas Requiring Attention
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| /external/selinux/policycoreutils/po/ |
| D | fr.po | 1139 msgstr "Attention ! Impossible de restaurer le contexte pour %s\n"
1241 "Attention ! Impossible de récupérer les informations liées au terminal\n"
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| /external/mtools/ |
| D | mtools.info | 468 *Caution / Attention distributors*: If mtools is compiled on a Linux
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| D | mtools.texi | 515 @strong{Caution / Attention distributors}: If mtools is compiled on a
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| /external/openssh/ |
| D | configure.ac | 1087 # Attention: always take care to bind libsocket and libnsl before libc,
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| /external/cpuinfo/test/dmesg/ |
| D | huawei-mate-9.log | 1350 [ 8.368682s][pid:0,cpu6,in irq]sd 0:0:0:0: tag#0 Sense Key : Unit Attention [current]
1356 [ 8.369232s][pid:0,cpu6,in irq]sd 0:0:0:1: tag#0 Sense Key : Unit Attention [current]
1396 [ 8.371551s][pid:0,cpu6,in irq]sd 0:0:0:2: tag#0 Sense Key : Unit Attention [current]
1409 [ 8.375000s][pid:0,cpu6,in irq]sd 0:0:0:3: tag#0 Sense Key : Unit Attention [current]
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| /external/tensorflow/ |
| D | RELEASE.md | 612 …* In `Attention` and `AdditiveAttention` layers, the `call()` method now accepts a `return_attenti…
3716 * Monotonic Attention wrappers added to `tf.contrib.seq2seq`.
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| /external/one-true-awk/testdir/ |
| D | funstack.in | 4828 …tion of the field equations in the presence of matter in a simple case. Attention is drawn to the …
19666 …abstract = "Attention is first given to some of the general problems of multidimensional table…
23746 …continuous-flow and preempt-resume scheduling of input-output activity. Attention is given to the …
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