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/aosp_15_r20/external/rust/android-crates-io/crates/libz-sys/src/zlib/contrib/puff/
Dpuff.c52 * 1.3 20 Mar 2002 - Go back to lengths for puff() parameters [Gailly]
94 #define MAXCODES (MAXLCODES+MAXDCODES) /* maximum codes lengths to read */
213 * a negative value if there is an error. If all of the lengths are zero, i.e.
220 * a simple integer ordering of codes of the same lengths. Hence below the
309 * Given the list of code lengths length[0..n-1] representing a canonical
320 * codes past the end of the incomplete lengths.
351 (h->count[length[symbol]])++; /* assumes lengths are within bounds */ in construct()
355 /* check for an over-subscribed or incomplete set of lengths */ in construct()
393 * - Literals, lengths, and the end-of-block code are combined into a single
397 * - There are 256 possible lengths (3..258), and so 29 symbols are not enough
[all …]
/aosp_15_r20/external/tensorflow/tensorflow/python/ops/ragged/
H A Dragged_tensor_shape.py42 lengths. `RaggedTensorDynamicShape` records the size of each ragged
43 dimension using an integer vector containing the slice lengths for all
291 def broadcast_dimension(self, axis, lengths): argument
292 """Returns a shape that is broadcast-compatible with self & lengths.
294 * If dimension[axis] is uniform and lengths is a scalar, the check
295 that either lengths==1 or axis==1 or lengths==axis, and tile
296 dimension[axis] with tf.where(lengths==axis, 1, axis) repeats.
298 * If dimension[axis] is uniform and lengths is a vector, then check
300 lengths repeats. (we can skip tiling if we statically know that
303 * If dimension[axis] is ragged and lengths is a scalar, then check
[all …]
H A Ddynamic_ragged_shape_test.py52 lengths: Sequence[Union[int, Sequence[int]]]) -> Sequence[RowPartition]:
59 lengths: a list of integers and lists of integers.
65 _) = dynamic_ragged_shape._to_row_partitions_and_nvals_from_lengths(lengths)
70 values, lengths: Sequence[Union[int, Sequence[int]]]) -> RaggedTensor:
71 """Specify a ragged tensor (or tensor) from lengths and values."""
72 row_partitions = _to_row_partitions_from_lengths(lengths)
102 lengths: Sequence[Union[int,
105 if not lengths:
107 next_length = lengths[0]
109 return _num_elements_of_lengths_with_rows(next_length * rows, lengths[1:])
[all …]
H A Dragged_from_tensor_op_test.py41 RaggedTensor.from_tensor(dt, lengths=[1, 0, 3]), [[5], [], [6, 0, 0]])
50 RaggedTensor.from_tensor(dt_3d, lengths=([2, 0, 3], [1, 1, 2, 0, 1])),
120 'lengths': [1],
126 'lengths': [0],
132 'lengths': [0, 1, 2],
138 'lengths': [0, 0, 0],
144 'lengths': [2, 2],
150 'lengths': [7, 8], # lengths > ncols: truncated to ncols
156 'lengths': [-2, -1], # lengths < 0: treated as zero
163 'lengths': [0, 0],
[all …]
H A Dragged_tensor.py65 dimensions whose slices may have different lengths. For example, the inner
67 since the column slices (`rt[0, :]`, ..., `rt[4, :]`) have different lengths.
71 differing slice lengths).
802 for lengths in reversed(nested_row_lengths):
803 result = cls.from_row_lengths(result, lengths, validate=validate)
1249 """Returns the lengths of the rows in this ragged tensor.
1255 axis: An integer constant indicating the axis whose row lengths should be
1269 >>> print(rt.row_lengths()) # lengths of rows in rt
1271 >>> print(rt.row_lengths(axis=2)) # lengths of axis=2 rows.
1577 lengths=None, argument
[all …]
/aosp_15_r20/external/pytorch/test/
H A Dtest_segment_reductions.py55 lengths = torch.tensor(lengths_arr, device=device, dtype=lengths_dtype)
56 # generate offsets from lengths
57 zeros_shape = list(lengths.shape)
59 offsets = torch.cat((lengths.new_zeros(zeros_shape), lengths), -1).cumsum_(-1)
69 for mode in ['lengths', 'offsets']:
74 if (mode == 'lengths'):
75 segment_reduce_kwargs['lengths'] = lengths
128 lengths = [1, 2, 3, 0]
170 lengths,
185 lengths = [0, 0]
[all …]
/aosp_15_r20/external/pytorch/aten/src/ATen/native/
H A DSegmentReduce.cpp133 const Tensor& lengths, in _segment_reduce_lengths_cpu_kernel() argument
136 // data and lengths should be contiguous from the call to .contiguous in segment_reduce_kernel in _segment_reduce_lengths_cpu_kernel()
138 TORCH_CHECK(lengths.is_contiguous(), "Expected lengths to be contiguous."); in _segment_reduce_lengths_cpu_kernel()
139 // reduction axis should always be the last dimension of lengths in _segment_reduce_lengths_cpu_kernel()
140 axis = lengths.dim() - 1; in _segment_reduce_lengths_cpu_kernel()
141 int64_t segment_count = lengths.size(axis); in _segment_reduce_lengths_cpu_kernel()
142 int64_t lengths_stride_axis = lengths.stride(axis); in _segment_reduce_lengths_cpu_kernel()
147 AT_DISPATCH_INDEX_TYPES(lengths.scalar_type(), "_segment_reduce_lengths_cpu_kernel1", [&]() { in _segment_reduce_lengths_cpu_kernel()
148 const auto* lengths_data = lengths.const_data_ptr<index_t>(); in _segment_reduce_lengths_cpu_kernel()
162 // data and lengths should be contiguous from the call to .contiguous in segment_reduce_kernel in _segment_reduce_offsets_cpu_kernel()
[all …]
/aosp_15_r20/external/pytorch/torch/nn/utils/
H A Drnn.py58 the batch, not the varying sequence lengths passed to
282 lengths: Union[Tensor, List[int]],
306 lengths (Tensor or list(int)): list of sequence lengths of each batch
317 if not isinstance(lengths, torch.Tensor):
321 "sequence lengths. The tracer cannot track the data flow of Python "
323 "the trace incorrect for any other combination of lengths.",
326 lengths = torch.as_tensor(lengths, dtype=torch.int64, device="cpu")
328 lengths = lengths.to(dtype=torch.int64)
333 lengths, sorted_indices = torch.sort(lengths, descending=True)
338 data, batch_sizes = _VF._pack_padded_sequence(input, lengths, batch_first)
[all …]
/aosp_15_r20/external/pytorch/test/nn/
H A Dtest_packed_sequence.py47 lengths = [len(i) for i in ordered]
49 return padded_tensor, lengths
56 padded, lengths = self._padded_sequence(input_type)
58 padded, lengths, enforce_sorted=enforce_sorted
90 padded, lengths = self._padded_sequence(torch.FloatTensor)
91 max_length = max(lengths)
92 packed = rnn_utils.pack_padded_sequence(padded, lengths)
118 self.assertEqual(lengths, lengths_out)
136 padded, lengths = self._padded_sequence(torch.IntTensor)
138 padded, lengths, enforce_sorted=enforce_sorted
[all …]
/aosp_15_r20/external/pytorch/torch/nested/_internal/
H A Dnested_tensor.py61 # tensors' varying lengths.
78 lengths=None, argument
90 # Query cache for the symint associated with offsets or lengths
92 ragged_source = offsets if lengths is None else lengths
96 if lengths is not None:
97 assert B == lengths.shape[0]
129 def __init__(self, values, offsets, *, lengths=None, **kwargs): argument
134 self._lengths = lengths
158 def lengths(self): member in NestedTensor
257 lengths = inner_tensors.get("_lengths", None)
[all …]
/aosp_15_r20/external/toybox/toys/posix/
H A Dwc.c35 static void show_lengths(unsigned long *lengths, char *name)
51 printf(" %*ld"+first, space, lengths[i]);
54 if (i==4) TT.totals[i] = maxof(TT.totals[i], lengths[i]);
55 else TT.totals[i] += lengths[i];
64 unsigned long word = 0, lengths[ARRAY_LEN(TT.totals)] = {0}, line = 0; in do_wc() local
72 lengths[3] = st.st_size; in do_wc()
86 if (toybuf[pos]=='\n') lengths[0]++; in do_wc()
87 lengths[3]++; in do_wc()
96 lengths[2]++; in do_wc()
100 if (line>lengths[4]) lengths[4] = line; in do_wc()
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/aosp_15_r20/external/mbedtls/tests/suites/
H A Dtest_suite_nist_kw.data27 NIST KW lengths #1 KW plaintext OK (2 to 2^54 - 1 semiblocks)
30 NIST KW lengths #2 KWP plaintext OK (1 to 2^32 - 1 octets)
33 NIST KW lengths #3 KW ciphertext OK (3 to 2^54 semiblocks)
36 NIST KW lengths #4 KWP ciphertext OK (2 to 2^29 semiblocks)
39 NIST KW lengths #5 KW plaintext too short (2 to 2^54 - 1 semiblocks)
42 NIST KW lengths #6 KWP plaintext too short (1 to 2^32 - 1 octets)
45 NIST KW lengths #8 KW ciphertext too short (3 to 2^54 semiblocks)
48 NIST KW lengths #9 KWP ciphertext too short (2 to 2^29 semiblocks)
51 NIST KW lengths #10 KW plaintext not a multiple of semiblocks.
54 NIST KW lengths #11 KW ciphertext not a multiple of semiblocks.
[all …]
/aosp_15_r20/external/openthread/third_party/mbedtls/repo/tests/suites/
H A Dtest_suite_nist_kw.data27 NIST KW lengths #1 KW plaintext OK (2 to 2^54 - 1 semiblocks)
30 NIST KW lengths #2 KWP plaintext OK (1 to 2^32 - 1 octets)
33 NIST KW lengths #3 KW ciphertext OK (3 to 2^54 semiblocks)
36 NIST KW lengths #4 KWP ciphertext OK (2 to 2^29 semiblocks)
39 NIST KW lengths #5 KW plaintext too short (2 to 2^54 - 1 semiblocks)
42 NIST KW lengths #6 KWP plaintext too short (1 to 2^32 - 1 octets)
45 NIST KW lengths #8 KW ciphertext too short (3 to 2^54 semiblocks)
48 NIST KW lengths #9 KWP ciphertext too short (2 to 2^29 semiblocks)
51 NIST KW lengths #10 KW plaintext not a multiple of semiblocks.
54 NIST KW lengths #11 KW ciphertext not a multiple of semiblocks.
[all …]
/aosp_15_r20/external/chromium-trace/catapult/third_party/polymer/components/web-animations-js/src/
H A Dshadow-handler.js20 lengths: [], property
31 shadow.lengths.push(result[0]);
54 while (left.lengths.length < Math.max(left.lengths.length, right.lengths.length))
55 left.lengths.push({px: 0});
56 while (right.lengths.length < Math.max(left.lengths.length, right.lengths.length))
57 right.lengths.push({px: 0});
66 for (var i = 0; i < left.lengths.length; i++) {
67 var mergedDimensions = scope.mergeDimensions(left.lengths[i], right.lengths[i], i == 2);
94 return {inset: inset, color: [0, 0, 0, 0], lengths: [{px: 0}, {px: 0}, {px: 0}, {px: 0}]};
/aosp_15_r20/external/puffin/src/
H A Dhuffman_table.h23 // Permutations of input Huffman code lengths (used only to read
35 // same as |kLengthBases| except for the the distances instead of lengths.
39 // Same as |kLengthExtraBits| except for distances instead of lengths.
47 // Checks the lengths of Huffman length arrays for correctness
49 // |num_lit_len| IN The number of literal/lengths code lengths
50 // |num_distance| IN The number of distance code lengths
51 // |num_codes| IN The number of code lengths for reading Huffman table.
56 LOG(ERROR) << "The lengths of the dynamic Huffman table are invalid: " in CheckHuffmanArrayLengths()
201 // Initializes the Huffman codes from an array of lengths.
203 // |lens| IN The input array of code lengths.
[all …]
/aosp_15_r20/external/tensorflow/tensorflow/python/data/kernel_tests/
H A Dbucket_by_sequence_length_test.py85 lengths = [8, 13, 25, 35]
90 # Expected sequence lengths of the individual batches.
101 for length, batch_size, bucket_elements in zip(lengths, batch_sizes,
110 # Calculate the expected occurrence of individual sequence lengths.
118 for bucket_elements, length in zip(n_bucket_elements, lengths):
161 for length, batch_size, bucket_elements in zip(lengths, batch_sizes,
179 for l in lengths:
181 # sequence lengths.
194 # Make sure the generated sequence lengths appear as often as expected.
197 "The generated sequence lengths did not match! "
[all …]
/aosp_15_r20/external/pytorch/torch/csrc/api/include/torch/nn/utils/
H A Drnn.h35 /// the batch, not the varying sequence lengths passed to
170 /// longest sequence (equal to ``lengths[0]``), ``B`` is the batch size, and
188 /// lengths (Tensor): list of sequences lengths of each batch element.
200 Tensor lengths,
203 lengths = lengths.to(kInt64);
208 std::tie(lengths, sorted_indices) =
209 torch::sort(lengths, /*dim=*/-1, /*descending=*/true);
216 torch::_pack_padded_sequence(input, lengths, batch_first);
245 /// containing the list of lengths of each sequence in the batch.
264 auto [padded_output, lengths] = torch::_pad_packed_sequence(
[all …]
/aosp_15_r20/external/pytorch/torch/utils/data/
H A Ddataset.py428 lengths: Sequence[Union[int, float]],
432 Randomly split a dataset into non-overlapping new datasets of given lengths.
435 the lengths will be computed automatically as
438 After computing the lengths, if there are any remainders, 1 count will be
439 distributed in round-robin fashion to the lengths
453 lengths (sequence): lengths or fractions of splits to be produced
456 if math.isclose(sum(lengths), 1) and sum(lengths) <= 1:
458 for i, frac in enumerate(lengths):
466 # add 1 to all the lengths in round-robin fashion until the remainder is 0
470 lengths = subset_lengths
[all …]
/aosp_15_r20/frameworks/base/libs/hwui/jni/
H A DPath.cpp253 static void addMove(std::vector<SkPoint>& segmentPoints, std::vector<float>& lengths, in addMove() argument
256 if (!lengths.empty()) { in addMove()
257 length = lengths.back(); in addMove()
260 lengths.push_back(length); in addMove()
263 static void addLine(std::vector<SkPoint>& segmentPoints, std::vector<float>& lengths, in addLine() argument
267 lengths.push_back(0); in addLine()
271 float length = lengths.back() + SkPoint::Distance(segmentPoints.back(), toPoint); in addLine()
273 lengths.push_back(length); in addLine()
330 std::vector<float>& lengths, float errorSquared, bool doubleCheckDivision) { in addBezier() argument
367 addLine(segmentPoints, lengths, iter->second); in addBezier()
[all …]
/aosp_15_r20/external/mesa3d/src/gallium/frontends/rusticl/api/
H A Dprogram.rs101 lengths: *const usize, in create_program_with_source()
116 // "lengths argument is an array with the number of chars in each string in create_program_with_source()
117 // (the string length). If an element in lengths is zero, its accompanying in create_program_with_source()
118 // string is null-terminated. If lengths is NULL, all strings in the in create_program_with_source()
126 // Take either an iterator over the given slice or - if the `lengths` in create_program_with_source()
137 let lengths: Box<dyn Iterator<Item = _>> = if lengths.is_null() { in create_program_with_source() localVariable
142 let lengths = lengths as *const Option<NonZeroUsize>; in create_program_with_source() localVariable
143 Box::new(unsafe { slice::from_raw_parts(lengths, count as usize) }.iter()) in create_program_with_source()
149 for (&string_ptr, len_opt) in iter::zip(srcs, lengths) { in create_program_with_source()
180 lengths: *const usize, in create_program_with_binary()
[all …]
/aosp_15_r20/external/rust/android-crates-io/crates/libz-sys/src/zlib/doc/
Drfc1951.txt207 "deflate" format limits distances to 32K bytes and lengths to 258
211 Each type of value (literals, distances, and lengths) in the
213 tree for literals and lengths and a separate code tree for distances.
289 lengths, not a sequence of bytes. We must therefore specify
318 sequences of different lengths, but a parser can always parse
367 various alphabets must not exceed certain maximum code lengths.
369 lengths from symbol frequencies. Again, see Chapter 5,
413 just by giving the bit lengths of the codes for each symbol of
416 by the sequence of bit lengths (2, 1, 3, 3). The following
418 from most- to least-significant bit. The code lengths are
[all …]
/aosp_15_r20/external/rust/android-crates-io/crates/libz-sys/src/zlib-ng/doc/
Drfc1951.txt207 "deflate" format limits distances to 32K bytes and lengths to 258
211 Each type of value (literals, distances, and lengths) in the
213 tree for literals and lengths and a separate code tree for distances.
289 lengths, not a sequence of bytes. We must therefore specify
318 sequences of different lengths, but a parser can always parse
367 various alphabets must not exceed certain maximum code lengths.
369 lengths from symbol frequencies. Again, see Chapter 5,
413 just by giving the bit lengths of the codes for each symbol of
416 by the sequence of bit lengths (2, 1, 3, 3). The following
418 from most- to least-significant bit. The code lengths are
[all …]
/aosp_15_r20/external/google-java-format/core/src/main/java/com/google/googlejavaformat/java/
H A DCommandLineOptions.java33 private final ImmutableList<Integer> lengths; field in CommandLineOptions
52 ImmutableList<Integer> lengths, in CommandLineOptions() argument
69 this.lengths = lengths; in CommandLineOptions()
99 /** Character offsets for partial formatting, paired with {@code lengths}. */
104 /** Partial formatting region lengths, paired with {@code offsets}. */
105 ImmutableList<Integer> lengths() { in lengths() method in CommandLineOptions
106 return lengths; in lengths()
167 return !lines().isEmpty() || !offsets().isEmpty() || !lengths().isEmpty(); in isSelection()
183 private final ImmutableList.Builder<Integer> lengths = ImmutableList.builder(); field in CommandLineOptions.Builder
217 lengths.add(length); in addLength()
[all …]
/aosp_15_r20/external/pytorch/torch/nested/
H A D__init__.py280 >>> lengths = torch.tensor([3, 2, 2, 1, 5], dtype=torch.int64)
282 >>> nt_narrowed = torch.nested.narrow(narrow_base, 1, starts, lengths, layout=torch.jagged)
319 lengths: Optional[Tensor] = None,
327 The offsets / lengths metadata determines how this dimension is split into batch elements
335 * lengths: Lengths of the individual batch elements; shape == batch_size. Example: [2, 1, 3]
339 Note that it can be useful to provide both offsets and lengths. This describes a nested tensor
348 with the offsets / lengths metadata used to distinguish batch elements.
350 lengths (optional :class:`torch.Tensor`): Lengths of the batch elements of shape B.
375 >>> lengths = torch.tensor([1, 1, 2])
377 >>> nt = nested_tensor_from_jagged(values, offsets, lengths)
[all …]
/aosp_15_r20/prebuilts/go/linux-x86/src/strings/
Dcompare_test.go63 lengths := make([]int, 0) // lengths to test in ascending order
65 lengths = append(lengths, i)
67 lengths = append(lengths, 256, 512, 1024, 1333, 4095, 4096, 4097)
70 lengths = append(lengths, 65535, 65536, 65537, 99999)
73 n := lengths[len(lengths)-1]
77 for _, len := range lengths {

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