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/external/tensorflow/tensorflow/contrib/cudnn_rnn/python/kernel_tests/
Dcudnn_rnn_ops_benchmark.py68 seq_length = config["seq_length"]
70 return "y%d_u%d_b%d_q%d" % (num_layers, num_units, batch_size, seq_length)
94 seq_length = config["seq_length"]
100 array_ops.ones([seq_length, batch_size, num_units]))
126 seq_length = config["seq_length"]
129 inputs = array_ops.zeros([batch_size, seq_length, num_units],
150 seq_length = config["seq_length"]
153 inputs = array_ops.zeros([batch_size, seq_length, num_units],
Dcudnn_rnn_test.py164 def SynthesizeInput(self, seq_length, batch_size, seed=1234): argument
173 inputs = np.random.randn(seq_length, batch_size,
629 seq_length = 8
654 inputs, initial_state = model.SynthesizeInput(seq_length, batch_size)
910 def _TestCudnnCompatibleRnnCells(self, num_layers, seq_length, num_units, argument
938 inputs, _ = model.SynthesizeInput(seq_length, batch_size, seed)
967 inference_input = np.random.rand(seq_length, batch_size,
980 dtype, shape=[seq_length, batch_size, input_size])
1204 batch_size, seq_length, dir_count, dropout, dtype, argument
1235 random_ops.random_uniform([seq_length, batch_size, input_size],
/external/tensorflow/tensorflow/python/feature_column/
Dutils.py38 seq_length = math_ops.segment_max(column_ids, segment_ids=row_ids)
45 seq_length = math_ops.cast(
46 math_ops.ceil(seq_length / num_elements), dtypes.int64)
50 n_pad = array_ops.shape(sp_tensor)[:1] - array_ops.shape(seq_length)[:1]
51 padding = array_ops.zeros(n_pad, dtype=seq_length.dtype)
52 return array_ops.concat([seq_length, padding], axis=0, name=name_scope)
Dsequence_feature_column.py568 seq_length = fc_utils.sequence_length_from_sparse_tensor(
572 dense_tensor=dense_tensor, sequence_length=seq_length)
/external/tensorflow/tensorflow/core/ops/
Dcudnn_rnn_ops_test.cc42 int seq_length = 2; in TEST() local
47 std::vector<int> input_shape = {seq_length, batch_size, num_units}; in TEST()
50 std::vector<int> output_shape = {seq_length, batch_size, in TEST()
74 int seq_length = 2; in TEST() local
79 std::vector<int> input_shape = {seq_length, batch_size, num_units}; in TEST()
82 std::vector<int> output_shape = {seq_length, batch_size, in TEST()
Dcudnn_rnn_ops.cc85 auto seq_length = c->Dim(input_shape, 0); in __anone1d60d010302() local
95 auto output_shape = c->MakeShape({seq_length, batch_size, output_size}); in __anone1d60d010302()
128 auto seq_length = c->Dim(input_shape, 0); in __anone1d60d010402() local
138 auto output_shape = c->MakeShape({seq_length, batch_size, output_size}); in __anone1d60d010402()
/external/v8/src/heap/
Dmarking.cc152 CellPrinter() : seq_start(0), seq_type(0), seq_length(0) {} in CellPrinter()
156 seq_length++; in Print()
164 seq_length = 0; in Print()
175 if (seq_length > 0) { in Flush()
177 seq_length * Bitmap::kBitsPerCell); in Flush()
178 seq_length = 0; in Flush()
187 uint32_t seq_length; member in v8::internal::__anon522e25580111::CellPrinter
/external/icu/icu4c/source/i18n/
Dcsr2022.cpp49 int32_t seq_length = (int32_t)uprv_strlen((const char *) seq); in match_2022() local
51 if (textLen-i >= seq_length) { in match_2022()
53 while(j < seq_length) { in match_2022()
62 i += seq_length-1; in match_2022()
/external/tensorflow/tensorflow/compiler/tests/
Dlstm.py124 def RandomInputs(batch_size, seq_length, num_inputs): argument
129 for seq in range(seq_length):
137 def BuildLSTMLayer(batch_size, seq_length, num_inputs, num_nodes): argument
155 x_seq, pad_seq = RandomInputs(batch_size, seq_length, num_inputs)
Dlstm_test.py142 seq_length = 3
147 x_seq = [constant_op.constant(self._inputs)] * seq_length
162 seq_length = 3
167 x_seq = [constant_op.constant(self._inputs)] * seq_length
169 ] * seq_length
242 out_seq, weights = lstm.BuildLSTMLayer(FLAGS.batch_size, FLAGS.seq_length,
252 '%s_%d_%d_%d_%d' % (name, FLAGS.batch_size, FLAGS.seq_length,
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_CudnnRNNV3.pbtxt20 [seq_length, batch_size, input_size]. If time_major is false, the shape is
21 [batch_size, seq_length, input_size].
33 [seq_length, batch_size, dir * num_units]. If time_major is false, the
34 shape is [batch_size, seq_length, dir * num_units].
Dapi_def_CudnnRNNBackpropV3.pbtxt20 [seq_length, batch_size, input_size]. If time_major is false, the shape is
21 [batch_size, seq_length, input_size].
33 [seq_length, batch_size, dir * num_units]. If time_major is false, the
34 shape is [batch_size, seq_length, dir * num_units].
Dapi_def_CudnnRNN.pbtxt18 input: A 3-D tensor with the shape of [seq_length, batch_size, input_size].
27 output: A 3-D tensor with the shape of [seq_length, batch_size,
Dapi_def_CudnnRNNV2.pbtxt19 input: A 3-D tensor with the shape of [seq_length, batch_size, input_size].
28 output: A 3-D tensor with the shape of [seq_length, batch_size,
Dapi_def_CudnnRNNBackprop.pbtxt17 input: A 3-D tensor with the shape of [seq_length, batch_size, input_size].
26 output: A 3-D tensor with the shape of [seq_length, batch_size,
Dapi_def_CudnnRNNBackpropV2.pbtxt20 input: A 3-D tensor with the shape of [seq_length, batch_size, input_size].
29 output: A 3-D tensor with the shape of [seq_length, batch_size,
/external/tensorflow/tensorflow/python/ops/
Dctc_ops.py788 def collapse_repeated(labels, seq_length, name=None): argument
806 [labels, seq_length]):
808 seq_length = ops.convert_to_tensor(seq_length, name="seq_length")
818 seq_mask = array_ops.sequence_mask(seq_length, maxlen=maxlen)
846 math_ops.cast(new_seq_len, seq_length.dtype))
/external/tensorflow/tensorflow/python/data/experimental/ops/
Dgrouping.py185 seq_length = element_length_func(*args)
191 math_ops.less_equal(buckets_min, seq_length),
192 math_ops.less(seq_length, buckets_max))
/external/tensorflow/tensorflow/python/kernel_tests/
Dctc_loss_op_test.py572 seq_length=[4, 5, 5])
587 seq_length=constant_op.constant([4, 5, 5], dtype=dtypes.int64))
602 seq_length=[4, 5, 5])
615 seq_length=[5, 4, 3])
628 seq_length=[4, 5, 1])
/external/tensorflow/tensorflow/contrib/feature_column/python/feature_column/
Dsequence_feature_column.py510 seq_length = fc_utils.sequence_length_from_sparse_tensor(
514 dense_tensor=dense_tensor, sequence_length=seq_length)
/external/tensorflow/tensorflow/stream_executor/rocm/
Drocm_dnn.cc1783 MIOpenRnnSequenceTensorDescriptor(int seq_length, int batch_size, in MIOpenRnnSequenceTensorDescriptor() argument
1785 : seq_length_(seq_length), in MIOpenRnnSequenceTensorDescriptor()
1790 if (seq_length <= 0) { in MIOpenRnnSequenceTensorDescriptor()
1792 absl::StrCat("sequence length must be positive: ", seq_length); in MIOpenRnnSequenceTensorDescriptor()
1805 handles_.assign(seq_length, handle); in MIOpenRnnSequenceTensorDescriptor()
1821 int seq_length() const { return seq_length_; } in seq_length() function in stream_executor::gpu::MIOpenRnnSequenceTensorDescriptor
1884 int seq_length = 0; member
1908 model_dims->seq_length = input_desc.seq_length(); in ExtractAndCheckRnnForward()
1928 if (!(output_desc.seq_length() == model_dims->seq_length && in ExtractAndCheckRnnForward()
1976 input_desc.seq_length() /*seqLength*/, input_desc.handles() /*xDesc*/, in CreateRnnWorkspace()
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Drocm_dnn.h56 createRnnSequenceTensorDescriptor(int seq_length, int batch_size,
/external/tensorflow/tensorflow/tools/api/golden/v2/
Dtensorflow.nn.pbtxt61 …argspec: "args=[\'labels\', \'seq_length\', \'name\'], varargs=None, keywords=None, defaults=[\'No…
/external/tensorflow/tensorflow/tools/api/golden/v1/
Dtensorflow.nn.pbtxt61 …argspec: "args=[\'labels\', \'seq_length\', \'name\'], varargs=None, keywords=None, defaults=[\'No…