Searched defs:dropout (Results 1 - 13 of 13) sorted by relevance

/external/tensorflow/tensorflow/python/layers/
H A Dcore.py265 rate: The dropout rate, between 0 and 1. E.g. `rate=0.1` would drop out
268 binary dropout mask that will be multiplied with the input.
270 `(batch_size, timesteps, features)`, and you want the dropout mask
300 return nn.dropout(inputs, 1 - self.rate,
311 @tf_export('layers.dropout')
312 def dropout(inputs, function
327 rate: The dropout rate, between 0 and 1. E.g. "rate=0.1" would drop out
330 binary dropout mask that will be multiplied with the input.
332 `(batch_size, timesteps, features)`, and you want the dropout mask
340 (apply dropout) o
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H A Dlayers.py42 @@dropout
79 from tensorflow.python.layers.core import dropout namespace
/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/
H A Drecurrent.py833 dropout: Float between 0 and 1.
854 dropout=0.,
874 self.dropout = min(1., max(0., dropout))
907 if 0 < self.dropout < 1 and self._dropout_mask is None:
911 self.dropout,
937 if 0 < self.dropout + self.recurrent_dropout:
968 'dropout':
969 self.dropout,
1006 dropout
1137 def dropout(self): member in class:SimpleRNN
1622 def dropout(self): member in class:GRU
2157 def dropout(self): member in class:LSTM
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/external/tensorflow/tensorflow/python/ops/
H A Dnn_ops.py2242 @tf_export("nn.dropout")
2243 def dropout(x, keep_prob, noise_shape=None, seed=None, name=None): # pylint: disable=invalid-name function
2244 """Computes dropout.
2276 with ops.name_scope(name, "dropout", [x]) as name:
H A Drnn_cell_impl.py837 # Do not perform dropout on the memory state.
846 """Operator adding dropout to inputs and outputs of the given cell."""
852 """Create a cell with added input, state, and/or output dropout.
855 then the same dropout mask is applied at every step, as described in:
860 Otherwise a different dropout mask is applied at every time step.
870 probability; if it is constant and 1, no input dropout will be added.
872 probability; if it is constant and 1, no output dropout will be added.
874 probability; if it is constant and 1, no output dropout will be added.
875 State dropout is performed on the outgoing states of the cell.
876 **Note** the state components to which dropout i
1028 def dropout(i, do_dropout, v): function in function:DropoutWrapper._dropout
1038 def dropout(i, do_dropout, v, n): function in function:DropoutWrapper._dropout
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/external/tensorflow/tensorflow/contrib/layers/python/layers/
H A Dlayers.py63 'dropout', 'elu', 'flatten', 'fully_connected', 'GDN', 'gdn',
1430 def dropout(inputs, function
1437 """Returns a dropout op applied to the input.
1444 inputs: The tensor to pass to the nn.dropout op.
1450 is in training mode. If so, dropout is applied and values scaled.
/external/tensorflow/tensorflow/contrib/cudnn_rnn/kernels/
H A Dcudnn_rnn_ops.cc489 OP_REQUIRES_OK(context, context->GetAttr("dropout", &dropout_));
514 float dropout() const { return dropout_; } function in class:tensorflow::TFRNNInputMode::CudnnRNNKernelCommon
549 rnn_mode(), ToDataType<T>::value, dropout(), seed(),
897 rnn_mode(), data_type, dropout(), seed(), dropout_state_allocator);
1101 rnn_mode(), data_type, dropout(), seed(), dropout_state_allocator);
/external/tensorflow/tensorflow/contrib/keras/api/keras/backend/
H A D__init__.py53 from tensorflow.python.keras._impl.keras.backend import dropout namespace
/external/tensorflow/tensorflow/python/keras/backend/
H A D__init__.py53 from tensorflow.python.keras._impl.keras.backend import dropout namespace
/external/tensorflow/tensorflow/stream_executor/
H A Dstream_executor_pimpl.cc347 dnn::RnnMode rnn_mode, dnn::DataType data_type, float dropout, uint64 seed,
356 data_type, dropout, seed, state_allocator);
344 createRnnDescriptor( int num_layers, int hidden_size, int input_size, dnn::RnnInputMode input_mode, dnn::RnnDirectionMode direction_mode, dnn::RnnMode rnn_mode, dnn::DataType data_type, float dropout, uint64 seed, ScratchAllocator *state_allocator) argument
H A Ddnn.h1967 // dropout: the dropout threshold between layers. When it is 0., no dropout
1969 // seed: a seed for initializing the dropout layers.
1971 // for dropout layer. The user has to maintain the memory until the model
1978 float dropout, uint64 seed,
1974 createRnnDescriptor(int num_layers, int hidden_size, int input_size, dnn::RnnInputMode input_mode, dnn::RnnDirectionMode direction_mode, dnn::RnnMode rnn_mode, dnn::DataType data_type, float dropout, uint64 seed, ScratchAllocator* state_allocator) argument
/external/tensorflow/tensorflow/python/keras/_impl/keras/
H A Dbackend.py3446 @tf_export('keras.backend.dropout')
3447 def dropout(x, level, noise_shape=None, seed=None): function
3466 return nn.dropout(x * 1., retain_prob, noise_shape, seed=seed)
/external/tensorflow/tensorflow/stream_executor/cuda/
H A Dcuda_dnn.cc979 float dropout, uint64 seed,
984 CUDNN_RETURN_IF_FAIL(status, "Failed to create dropout descriptor");
986 if (dropout == 0.f) {
995 CUDNN_RETURN_IF_FAIL(status, "Failed to query dropout state sizes");
1002 port::StrCat("Failed to allocate Cudnn dropout state memory of ",
1010 dropout, state_memory.opaque(),
1014 "Failed to set dropout descriptor with state memory size: ",
1022 CUDNN_RETURN_IF_FAIL(status, "Failed to destroy Cudnn dropout handle: ");
1081 float dropout, uint64 seed,
1092 // Create the dropout handl
978 CudnnDropoutDescriptor(CUDAExecutor* parent, cudnnHandle_t cudnn_handle, float dropout, uint64 seed, ScratchAllocator* state_allocator) argument
1076 CudnnRnnDescriptor(CUDAExecutor* parent, cudnnHandle_t cudnn_handle, int num_layers, int hidden_size, int input_size, cudnnRNNInputMode_t input_mode, cudnnDirectionMode_t direction_mode, cudnnRNNMode_t rnn_mode, cudnnDataType_t data_type, float dropout, uint64 seed, ScratchAllocator* state_allocator) argument
1755 createRnnDescriptor(int num_layers, int hidden_size, int input_size, dnn::RnnInputMode input_mode, dnn::RnnDirectionMode direction_mode, dnn::RnnMode rnn_mode, dnn::DataType data_type, float dropout, uint64 seed, ScratchAllocator* state_allocator) argument
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