| /external/rust/android-crates-io/crates/plotters/src/coord/ranged1d/combinators/ |
| D | linspace.rs | 12 /// for the linspace coord for how to treat the non-grid-point values.
22 /// This type marker means linspace do the exact match for searching
163 /// The linspace decorate abstracting this method. For example, we can have a discrete coordinate:
166 /// Linspace also supports different types of bucket matching method - This configuration alters th…
167 /// [DiscreteCoord::index_of](../trait.DiscreteCoord.html#tymethod.index_of) for Linspace coord spec
168 … value falls into the nearst bucket smaller than it. See [Linspace::use_floor](struct.Linspace.htm…
169 …value falls into the nearst bucket. See [Linearspace::use_round](struct.Linspace.html#method.use_r…
170 …alue falls into the nearst bucket larger than itself. See [Linspace::use_ceil](struct.Linspace.htm…
171 …he value must be exactly same as the butcket value. See [Linspace::use_exact](struct.Linspace.htm…
173 pub struct Linspace<T: Ranged, S: Clone, R: LinspaceRoundingMethod<T::ValueType>> struct
[all …]
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| D | mod.rs | 7 mod linspace; module
8 pub use linspace::{IntoLinspace, Linspace};
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| /external/pytorch/torch/csrc/jit/operator_upgraders/ |
| D | README.md | 44 c = torch.linspace(a, b, steps=5)
45 d = torch.linspace(a, b)
48 …rch.org/docs/stable/index.html), like [linspace operator](https://pytorch.org/docs/stable/generate…
54 TestVersionedLinspaceV7(): "aten::linspace",
69 …ersions.h#L82) within the range `[start, end]`. Let's take an operator `linspace` with the overloa…
71 … exist in `upgraders_entry.cpp`, for example `linspace_out_0_7` (means `linspace.out` operator is …
72 …1. If it's possible to write an upgrader valid for `linspace` before versioning bumping to 8, afte…
73 …linspace` before versioning bumping to 8, check the date when the version is bumped to 8 at [`ver…
75 … the new runtime with the new `linspace` operator can handle an old model with the old `linspace` …
77 …linspace(start: Union[int, float, complex], end: Union[int, float, complex], steps: Optional[int],…
[all …]
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| D | version_map.cpp | 26 {"aten::linspace",
29 …"aten::linspace(Scalar start, Scalar end, int? steps=None, *, ScalarType? dtype=None, Layout? layo…
30 {"aten::linspace.out",
33 …"aten::linspace.out(Scalar start, Scalar end, int? steps=None, *, Tensor(a!) out) -> Tensor(a!)"}}…
|
| D | upgraders_entry.cpp | 34 …return torch.linspace(start=start, end=end, steps=100, dtype=dtype, layout=layout, device=device, …
35 …return torch.linspace(start=start, end=end, steps=steps, dtype=dtype, layout=layout, device=device…
40 return torch.linspace(start=start, end=end, steps=100, out=out)
41 return torch.linspace(start=start, end=end, steps=steps, out=out)
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| /external/tensorflow/tensorflow/python/kernel_tests/math_ops/ |
| D | basic_gpu_test.py | 53 …x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-many-functi…
54 …y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-many-functi…
63 x = np.linspace(-5, 20, 15).reshape(3, 5).astype(np.float32)
64 …y = np.linspace(20, -5, 30).reshape(2, 3, 5).astype(np.float32) # pylint: disable=too-many-functi…
71 …x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float64) # pylint: disable=too-many-functi…
72 …y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float64) # pylint: disable=too-many-functi…
79 x = np.linspace(-5, 20, 15).reshape(3, 5).astype(np.float64)
80 …y = np.linspace(20, -5, 30).reshape(2, 3, 5).astype(np.float64) # pylint: disable=too-many-functi…
134 x = (1 + np.linspace(0, 5, np.prod([1, 3, 2]))).astype(np.float32).reshape(
136 y = (1 + np.linspace(0, 5, np.prod([1, 3, 2]))).astype(np.float32).reshape(
[all …]
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| D | cwise_ops_binary_test.py | 198 …x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-many-functi…
199 …y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-many-functi…
219 …a_pos_small = np.linspace(0.1, 2, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-m…
220 …x_pos_small = np.linspace(0.1, 10, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-…
265 …x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float64) # pylint: disable=too-many-functi…
266 …y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float64) # pylint: disable=too-many-functi…
286 …a_pos_small = np.linspace(0.1, 2, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-m…
287 …x_pos_small = np.linspace(0.1, 10, 15).reshape(1, 3, 5).astype(np.float32) # pylint: disable=too-…
386 …x = (1 + 1j) * np.linspace(-10, 10, 6).reshape(1, 3, 2).astype( # pylint: disable=too-many-functi…
388 …y = (1 + 1j) * np.linspace(20, -20, 6).reshape(1, 3, 2).astype( # pylint: disable=too-many-functi…
[all …]
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| D | topk_op_test.py | 104 np.linspace(0, 100, dim, dtype=np.float64))
117 np.linspace(0, 100, b * n, dtype=dtype)).reshape(b, n)
131 np.linspace(0, 100, b * n, dtype=dtype)).reshape(b, n)
145 np.linspace(0, 100, b * n, dtype=dtype)).reshape(b, n)
160 np.linspace(0, 3, b * n, dtype=np.int32)).reshape(b, n)
|
| /external/webrtc/modules/audio_processing/agc2/ |
| D | interpolated_gain_curve_unittest.cc | 40 const auto levels = test::LinSpace( in TEST()
50 const auto levels = test::LinSpace( in TEST()
63 const auto levels = test::LinSpace( in TEST()
77 const auto levels = test::LinSpace( in TEST()
110 test::LinSpace(kLevelEpsilon, limiter.knee_start_linear(), kNumSteps); in TEST()
128 test::LinSpace(limiter.knee_start_linear() + kLevelEpsilon, in TEST()
148 const auto levels = test::LinSpace( in TEST()
170 const auto levels = test::LinSpace( in TEST()
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| D | agc2_testing_common_unittest.cc | 17 TEST(GainController2TestingCommon, LinSpace) { in TEST() argument
18 std::vector<double> points1 = test::LinSpace(-1.0, 2.0, 4); in TEST()
22 std::vector<double> points2 = test::LinSpace(0.0, 1.0, 4); in TEST()
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_LinSpace.pbtxt | 2 graph_op_name: "LinSpace"
37 tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0 11.0 12.0]
|
| /external/pytorch/test/typing/pass/ |
| D | creation_ops.py | 71 # torch.linspace
72 torch.linspace(3, 10, steps=5)
73 torch.linspace(-10, 10, steps=5)
74 torch.linspace(start=-10, end=10, steps=5)
75 torch.linspace(start=-10, end=10, steps=1)
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
| D | LinSpace.pbtxt | 2 name: "LinSpace"
44 name: "LinSpace"
87 name: "LinSpace"
|
| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | LinSpace.pbtxt | 2 name: "LinSpace"
44 name: "LinSpace"
87 name: "LinSpace"
|
| /external/pytorch/test/typing/reveal/ |
| D | tensor_constructors.py | 75 # torch.linspace
76 reveal_type(torch.linspace(3, 10, steps=5)) # E: {Tensor}
77 reveal_type(torch.linspace(-10, 10, steps=5)) # E: {Tensor}
78 reveal_type(torch.linspace(start=-10, end=10, steps=5)) # E: {Tensor}
79 reveal_type(torch.linspace(start=-10, end=10, steps=1)) # E: {Tensor}
|
| /external/pytorch/test/torch_np/numpy_tests/lib/ |
| D | test_histograms.py | 55 (a, b) = histogram(np.linspace(0, 10, 100))
184 v = np.linspace(0, 10, 10)
249 vals = np.linspace(0.0, 1.0, num=100)
255 vals = np.linspace(0.0, 1.0, num=100)
262 vals = np.linspace(0.0, 1.0, num=100)
285 vals = np.linspace(0.0, 1.0, num=100)
458 Straightforward testing with a mixture of linspace data (for
500 x1 = np.linspace(-10, -1, testlen // 5 * 2)
501 x2 = np.linspace(1, 10, testlen // 5 * 3)
602 # assert_equal(edges_auto, np.linspace(0, 100, 12))
[all …]
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| /external/pytorch/test/jit/fixtures_srcs/ |
| D | fixtures_src.py | 16 c = torch.linspace(a, b, steps=5)
17 d = torch.linspace(a, b)
28 return torch.linspace(a, b, out=out)
|
| /external/tensorflow/tensorflow/core/api_def/java_api/ |
| D | api_def_LinSpace.pbtxt | 2 graph_op_name: "LinSpace"
4 name: "LinSpace"
|
| /external/tensorflow/tensorflow/core/api_def/python_api/ |
| D | api_def_LinSpace.pbtxt | 2 graph_op_name: "LinSpace"
8 name: "linspace"
|
| /external/yapf/yapftests/ |
| D | reformatter_style_config_test.py | 153 plt.plot(numpy.linspace(0, 1, 10), numpy.linspace(0, 1, 10), marker="x",
180 plt.plot(numpy.linspace(0, 1, 10),
181 numpy.linspace(0, 1, 10),
|
| /external/pytorch/test/ |
| D | test_decomp.py | 272 (torch.int8, torch.ops.aten.linspace.default): (0, 1),
273 (torch.uint8, torch.ops.aten.linspace.default): (0, 1),
274 (torch.int16, torch.ops.aten.linspace.default): (0, 1),
275 (torch.int32, torch.ops.aten.linspace.default): (0, 1),
276 (torch.int64, torch.ops.aten.linspace.default): (0, 1),
277 (torch.int8, torch.ops.aten.linspace.Tensor_Tensor): (0, 1),
278 (torch.uint8, torch.ops.aten.linspace.Tensor_Tensor): (0, 1),
279 (torch.int16, torch.ops.aten.linspace.Tensor_Tensor): (0, 1),
280 (torch.int32, torch.ops.aten.linspace.Tensor_Tensor): (0, 1),
281 (torch.int64, torch.ops.aten.linspace.Tensor_Tensor): (0, 1),
[all …]
|
| /external/pytorch/benchmarks/dynamo/microbenchmarks/ |
| D | utils.py | 7 ret = torch.linspace(low, high, steps)
17 ret = torch.pow(pow, torch.linspace(start, stop, steps))
|
| /external/tensorflow/tensorflow/python/ops/signal/ |
| D | mel_ops.py | 164 # Note: As num_spectrogram_bins is passed to `math_ops.linspace`
165 # and the validation is already done in linspace (both in shape function
183 linear_frequencies = math_ops.linspace(
193 math_ops.linspace(_hertz_to_mel(lower_edge_hertz),
|
| /external/sdv/vsomeip/third_party/boost/numeric/odeint/test_external/nt2/ |
| D | copy.cpp | 11 #include <nt2/include/functions/linspace.hpp>
34 nt2::table<T> x = nt2::linspace(T(1),T(0),7); in BOOST_AUTO_TEST_CASE_TEMPLATE()
|
| /external/tensorflow/tensorflow/python/debug/cli/ |
| D | tensor_format_test.py | 180 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
192 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
201 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
217 a = np.linspace(0.0, 1.0 - 1.0 / 40.0, 40).reshape([2, 20])
236 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])
248 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])
279 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])
432 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
452 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])
|