Searched refs:cycle_length (Results 1 - 13 of 13) sorted by relevance

/external/tensorflow/tensorflow/python/data/kernel_tests/
H A Dinterleave_dataset_op_test.py33 def _interleave(self, lists, cycle_length, block_length):
42 for i in range(cycle_length):
50 for i in range(cycle_length):
102 cycle_length = array_ops.placeholder(dtypes.int64, shape=[])
111 cycle_length, block_length))
119 cycle_length: 1, block_length: 3})
129 cycle_length: 2, block_length: 1})
140 cycle_length: 2, block_length: 3})
151 cycle_length: 7, block_length: 2})
160 cycle_length
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H A Ddataset_from_generator_op_test.py122 .interleave(interleave_fn, cycle_length=10,
182 interleave_fn, cycle_length=num_parallel_iterators, block_length=1)
/external/fio/lib/
H A Dlfsr.h20 uint64_t cycle_length; member in struct:fio_lfsr
H A Dlfsr.c116 * This is previously calculated in `prepare_spin` and cycle_length should
120 * ii. If it reaches zero, add "+1" to the spin and reset the cycle_length
133 if (fl->cycle_length && !--fl->cycle_length) {
135 fl->cycle_length = fl->cached_cycle_length;
200 fl->cycle_length = 0; /* No cycle occurs, other than the expected */
205 fl->cycle_length = (x * i) + (y * i) / (spin + 1);
209 fl->cached_cycle_length = fl->cycle_length;
215 fl->cycle_length++;
/external/tensorflow/tensorflow/contrib/data/python/ops/
H A Dinterleave_ops.py34 def __init__(self, input_dataset, map_func, cycle_length, block_length,
73 cycle_length, dtype=dtypes.int64, name="cycle_length")
85 argument_default=2 * cycle_length)
116 cycle_length,
125 @{tf.data.Dataset.interleave}, it gets elements from `cycle_length` nested
140 cycle_length=4))
148 cycle_length: The number of input `Dataset`s to interleave from in parallel.
166 dataset, map_func, cycle_length, block_length, sloppy,
174 def sloppy_interleave(map_func, cycle_length, block_lengt
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H A Ddataset_ops.py390 cycle_length=FLAGS.num_readers, block_length=1)
530 def interleave(self, map_func, cycle_length, block_length=1):
543 cycle_length=4, block_length=16))
546 The `cycle_length` and `block_length` arguments control the order in which
547 elements are produced. `cycle_length` controls the number of input elements
548 that are processed concurrently. If you set `cycle_length` to 1, this
551 this transformation will apply `map_func` to `cycle_length` input elements,
566 cycle_length=2, block_length=4) == {
589 cycle_length: The number of elements from this dataset that will be
598 dataset_ops.InterleaveDataset(self._dataset, map_func, cycle_length,
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/external/tensorflow/tensorflow/contrib/data/python/kernel_tests/
H A Dinterleave_dataset_op_test.py44 def _build_iterator_graph(self, input_values, cycle_length, block_length):
49 cycle_length, block_length)
54 # cycle_length > 1, block_length > 1
55 cycle_length = 2
60 input_values, cycle_length, block_length),
62 input_values, cycle_length * 2, block_length * 1),
64 # cycle_length = 1
65 cycle_length = 1
69 input_values, cycle_length, block_length),
72 cycle_length
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/external/webrtc/webrtc/video/
H A Dfull_stack_plot.py213 def __init__(self, fields, data_list, cycle_length=None, frames=None,
217 self.cycle_length = cycle_length
245 if self.cycle_length:
246 line.values = average_over_cycle(line.values, self.cycle_length)
269 if self.cycle_length:
270 x = numpy.array(range(self.cycle_length))
310 "-c", "--cycle_length", nargs=1, action=CustomAction,
340 cycle_length = None
350 if key == "cycle_length"
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/external/tensorflow/tensorflow/core/kernels/data/
H A Dparallel_interleave_dataset_op.cc53 int64 cycle_length = 0; variable
55 ParseScalarArgument(ctx, "cycle_length", &cycle_length));
56 OP_REQUIRES(ctx, cycle_length > 0,
57 errors::InvalidArgument("`cycle_length` must be > 0"));
87 new Dataset(input, std::move(captured_func), cycle_length, block_length,
96 std::unique_ptr<CapturedFunction> captured_func, int64 cycle_length,
102 cycle_length_(cycle_length),
95 Dataset(const DatasetBase* input, std::unique_ptr<CapturedFunction> captured_func, int64 cycle_length, int64 block_length, bool sloppy, int64 buffer_output_elements, int64 prefetch_input_elements, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
H A Dinterleave_dataset_op.cc52 OP_REQUIRES_OK(ctx, ctx->input("cycle_length", &cycle_length_t));
54 errors::InvalidArgument("cycle_length must be a scalar."));
55 const int64 cycle_length = cycle_length_t->flat<int64>()(0); variable
57 ctx, cycle_length > 0,
58 errors::InvalidArgument("cycle_length must be greater than zero."));
74 new Dataset(ctx, input, func_, std::move(captured_func), cycle_length,
83 std::unique_ptr<CapturedFunction> captured_func, int64 cycle_length,
90 cycle_length_(cycle_length),
81 Dataset(OpKernelContext* ctx, const DatasetBase* input, const NameAttrList& func, std::unique_ptr<CapturedFunction> captured_func, int64 cycle_length, int64 block_length, const DataTypeVector& output_types, const std::vector<PartialTensorShape>& output_shapes) argument
/external/fio/t/
H A Dlfsr-test.c76 printf("Cycle length is %lu\n", (unsigned long) fl->cycle_length);
/external/tensorflow/tensorflow/python/data/ops/
H A Ddataset_ops.py688 cycle_length=FLAGS.num_readers, block_length=1)
807 def interleave(self, map_func, cycle_length, block_length=1):
820 cycle_length=4, block_length=16))
823 The `cycle_length` and `block_length` arguments control the order in which
824 elements are produced. `cycle_length` controls the number of input elements
825 that are processed concurrently. If you set `cycle_length` to 1, this
828 this transformation will apply `map_func` to `cycle_length` input elements,
843 cycle_length=2, block_length=4) == {
866 cycle_length: The number of elements from this dataset that will be
874 return InterleaveDataset(self, map_func, cycle_length, block_lengt
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/external/tensorflow/tensorflow/python/grappler/
H A Ddatasets_test.py355 make_dataset(test_case['tensor']), cycle_length=42)

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