| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_util_test.py | 49 axis=0,
54 axis=0,
59 axis=1,
66 axis=0,
71 axis=0,
76 axis=1,
81 dict(data=3, repeats=4, axis=0, expected=[3, 3, 3, 3]),
82 dict(data=[3], repeats=4, axis=0, expected=[3, 3, 3, 3]),
83 dict(data=3, repeats=[4], axis=0, expected=[3, 3, 3, 3]),
84 dict(data=[3], repeats=[4], axis=0, expected=[3, 3, 3, 3]),
[all …]
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| D | ragged_reduce_op_test.py | 61 axis=0,
68 axis=-2,
75 axis=1,
82 axis=-1,
89 axis=0,
96 axis=1,
103 axis=0,
110 axis=1,
117 axis=0,
124 axis=1,
[all …]
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| D | ragged_tensor_shape.py | 112 for axis, dimension_size in enumerate(partitioned_dim_sizes):
115 'rank of partitioned_dim_sizes[%d] is unknown' % axis)
191 def dimension_size(self, axis): argument
193 if not isinstance(axis, int):
196 if axis < partitioned_ndims:
197 return self._partitioned_dim_sizes[axis]
199 return self._inner_dim_sizes[axis - partitioned_ndims]
201 def is_ragged(self, axis): argument
203 if not isinstance(axis, int):
206 if axis < 0:
[all …]
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| D | ragged_stack_op_test.py | 35 axis=0,
41 axis=1,
50 axis=2,
58 axis=-3,
64 axis=-2,
73 axis=-1,
82 axis=0,
90 axis=1,
100 axis=2,
109 axis=-3,
[all …]
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| D | ragged_one_hot_op_test.py | 44 axis=-1,
49 axis=2,
76 axis=2,
87 axis=None, argument
98 axis=axis,
104 dict(indices=[[1]], depth=4, axis=0, # axis < ragged_rank
106 dict(indices=[[1]], depth=4, axis=1, # axis == ragged_rank
108 dict(indices=[[1]], depth=4, axis=-2,
121 axis=None, argument
134 axis=axis,
[all …]
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| D | ragged_row_lengths_op_test.py | 37 axis=2,
46 axis=0,
61 axis=0,
68 axis=0,
73 axis=1,
78 axis=2,
85 axis=0,
89 axis=-3,
93 axis=1,
97 axis=-2,
[all …]
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| D | ragged_gather_op_test.py | 148 axis=1,
154 axis=1,
161 axis=1,
167 axis=1,
175 axis=2,
182 axis=2,
191 axis=None, argument
199 params, indices, axis=axis, batch_dims=batch_dims)
352 dict(params_shape=[3, 4], indices_shape=[], axis=0),
353 dict(params_shape=[3, 4], indices_shape=[5], axis=0),
[all …]
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| D | ragged_concat_op_test.py | 47 axis=1,
54 axis=0,
62 axis=1,
72 axis=-2,
80 axis=-1,
92 axis=0,
101 axis=1,
113 axis=0,
129 axis=1,
141 axis=2,
[all …]
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| D | ragged_math_ops.py | 245 axis=0)
479 axis, argument
523 return reduce_op(rt_input, axis, keepdims=keepdims, name=name)
528 rt_input, axis, keepdims=keepdims, name=name, separator=separator)
530 if isinstance(axis, ops.Tensor):
531 axis = tensor_util.constant_value(axis)
532 if axis is None:
534 if isinstance(axis, np.ndarray):
535 axis = axis.tolist()
538 if axis is None:
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/control_flow/ |
| D | scan_ops_test.py | 29 def numpy_reverse(x, axis): argument
31 if axis < 0:
32 axis = length + axis
35 slice(None, None, -1) if i == axis else slice(None) for i in range(length)
40 def handle_options(func, x, axis, exclusive, reverse): argument
43 if axis < 0:
44 axis = length + axis
47 x = numpy_reverse(x, axis)
50 ix_head = [slice(0, 1) if i == axis else slice(None) for i in range(length)]
52 slice(0, -1) if i == axis else slice(None) for i in range(length)
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/array_ops/ |
| D | gather_op_test.py | 82 for axis in range(data.ndim):
83 with self.subTest(dtype=dtype, axis=axis):
87 gather_t = array_ops.gather(params, indices, axis=axis)
89 self.assertAllEqual(np.take(params_np, 2, axis=axis), gather_val)
90 expected_shape = data.shape[:axis] + data.shape[axis + 1:]
98 for axis in range(data.ndim):
99 with self.subTest(dtype=dtype, axis=axis):
104 gather_t = array_ops.gather(params, indices, axis=axis)
106 self.assertAllEqual(np.take(params_np, [0, 1, 0, 2], axis=axis),
108 expected_shape = data.shape[:axis] + (4,) + data.shape[axis + 1:]
[all …]
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| D | unstack_op_test.py | 27 def np_split_squeeze(array, axis): argument
28 axis_len = array.shape[axis]
31 arr, axis=(axis,)) for arr in np.split(
32 array, axis_len, axis=axis)
45 def unstackReference(self, data, axis): argument
49 axis = axis + rank if axis < 0 else axis
50 for k in range(data.shape[axis]):
51 axis = rank + axis if axis < 0 else axis
56 slice(None) if i != axis else k for i in range(rank))
64 for axis in range(-rank, rank):
[all …]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | scan_ops_test.py | 30 def numpy_reverse(x, axis): argument
32 if axis < 0:
33 axis = length + axis
36 slice(None, None, -1) if i == axis else slice(None) for i in range(length)
41 def handle_options(func, x, axis, exclusive, reverse): argument
44 if axis < 0:
45 axis = length + axis
48 x = numpy_reverse(x, axis)
51 ix_head = tuple(slice(0, 1) if i == axis else slice(None)
54 slice(0, -1) if i == axis else slice(None) for i in range(length)
[all …]
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| D | gather_test.py | 58 for axis in 0, 1, -1:
62 gather_t = array_ops.gather(params, indices, axis=axis)
65 np.take(params_np, 2, axis=axis), dtype)
73 for axis in 0, 1, -1:
78 gather_t = array_ops.gather(params, indices, axis=axis)
81 np.take(params_np, [0, 1, 0, 2], axis=axis), dtype)
94 for axis in 0, 1, -1:
98 gather_t = array_ops.gather(params, indices, axis=axis)
105 np.take(params_np, [0, 1, 0, 2], axis=axis), dtype)
113 for axis in 0, 1, 2, 3, -1, -2:
[all …]
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| /external/s2-geometry-library-java/src/com/google/common/geometry/ |
| D | S2Cap.java | 42 private final S2Point axis; field in S2Cap
48 axis = new S2Point(); in S2Cap()
52 private S2Cap(S2Point axis, double height) { in S2Cap() argument
53 this.axis = axis; in S2Cap()
63 public static S2Cap fromAxisHeight(S2Point axis, double height) { in fromAxisHeight() argument
65 return new S2Cap(axis, height); in fromAxisHeight()
73 public static S2Cap fromAxisAngle(S2Point axis, S1Angle angle) { in fromAxisAngle() argument
80 return new S2Cap(axis, 2 * d * d); in fromAxisAngle()
88 public static S2Cap fromAxisArea(S2Point axis, double area) { in fromAxisArea() argument
90 return new S2Cap(axis, area / (2 * S2.M_PI)); in fromAxisArea()
[all …]
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| /external/tensorflow/tensorflow/python/ops/ |
| D | sort_ops.py | 31 def sort(values, axis=-1, direction='ASCENDING', name=None): argument
83 return _sort_or_argsort(values, axis, direction, return_argsort=False)
88 def argsort(values, axis=-1, direction='ASCENDING', stable=False, name=None): argument
150 return _sort_or_argsort(values, axis, direction, return_argsort=True)
153 def _sort_or_argsort(values, axis, direction, return_argsort): argument
174 axis = framework_ops.convert_to_tensor(axis, name='axis')
175 axis_static = tensor_util.constant_value(axis)
176 if axis.shape.ndims not in (None, 0) or axis_static is None:
186 def _descending_sort(values, axis, return_argsort=False): argument
199 k = array_ops.shape(values)[axis]
[all …]
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| D | array_ops.py | 305 def expand_dims(input, axis=None, name=None, dim=None): argument
369 axis = deprecation.deprecated_argument_lookup("axis", axis, "dim", dim)
370 if axis is None:
372 return expand_dims_v2(input, axis, name)
377 def expand_dims_v2(input, axis, name=None): argument
442 return gen_array_ops.expand_dims(input, axis, name)
1418 def stack(values, axis=0, name="stack"): argument
1463 if axis == 0:
1473 if axis < -expanded_num_dims or axis >= expanded_num_dims:
1477 return gen_array_ops.pack(values, axis=axis, name=name)
[all …]
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| /external/tensorflow/tensorflow/python/keras/layers/normalization/ |
| D | layer_normalization.py | 153 axis=-1, argument
165 if isinstance(axis, (list, tuple)):
166 self.axis = axis[:]
167 elif isinstance(axis, int):
168 self.axis = axis
171 'argument \'axis\', but received: %r' % axis)
195 axis = sorted(self.axis)
198 if axis[-1] == ndims - 1 and axis[-1] - axis[0] == len(axis) - 1:
216 if isinstance(self.axis, int):
217 self.axis = [self.axis]
[all …]
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| /external/oboe/samples/RhythmGame/third_party/glm/gtx/ |
| D | matrix_interpolation.inl | 10 tvec3<T, P> & axis, argument
22 axis.x = (T)1.0;
23 axis.y = (T)0.0;
24 axis.z = (T)0.0;
37 axis.x = (T)0.0;
38 axis.y = (T)0.7071;
39 axis.z = (T)0.7071;
41 axis.x = sqrt(xx);
42 axis.y = xy / axis.x;
43 axis.z = xz / axis.x;
[all …]
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| /external/tensorflow/tensorflow/python/distribute/ |
| D | strategy_gather_test.py | 70 def _gather_same_shape_and_verify(self, value_on_replica, axis, pure_eager, argument
76 return strategy.gather(distributed_values, axis=axis)
84 expected_result = array_ops.concat(all_results, axis=axis)
90 axis = 0
91 self._gather_same_shape_and_verify(single_value, axis, pure_eager, strategy)
96 axis = 0
97 self._gather_same_shape_and_verify(single_value, axis, pure_eager, strategy)
102 axis = 1
103 self._gather_same_shape_and_verify(single_value, axis, pure_eager, strategy)
108 axis = 0
[all …]
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| /external/fonttools/Tests/ttLib/tables/ |
| D | _f_v_a_r_test.py | 53 axis = Axis()
54 axis.axisTag = tag
55 axis.defaultValue = defaultValue
56 axis.minValue, axis.maxValue = minValue, maxValue
57 axis.axisNameID = AddName(font, name).nameID
58 fvarTable.axes.append(axis)
111 axis = Axis()
112 axis.axisTag, axis.axisNameID = ('opsz', 345)
113 axis.minValue, axis.defaultValue, axis.maxValue = (-0.5, 1.3, 1.5)
114 self.assertEqual(FVAR_AXIS_DATA, axis.compile())
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/strings_ops/ |
| D | reduce_join_op_test.py | 100 axis, argument
116 axis=axis,
124 def _testMultipleReduceJoin(self, input_array, axis, separator=" "): argument
138 inputs=input_array, axis=axis, keep_dims=False, separator=separator)
140 inputs=input_array, axis=axis, keep_dims=True, separator=separator)
143 for index in axis:
145 inputs=truth, axis=index, keep_dims=True, separator=separator)
146 if not axis:
148 truth_squeezed = array_ops.squeeze(truth, axis=axis)
162 self._testReduceJoin(input_array, truth, truth_shape, axis=0)
[all …]
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | expand_dims.cc | 34 int axis, TfLiteTensor* output) { in ExpandTensorDim() argument
36 if (axis < 0) { in ExpandTensorDim()
37 axis = input_dims.size + 1 + axis; in ExpandTensorDim()
39 TF_LITE_ENSURE(context, axis <= input_dims.size); in ExpandTensorDim()
40 TF_LITE_ENSURE(context, axis >= 0); in ExpandTensorDim()
44 if (i < axis) { in ExpandTensorDim()
46 } else if (i == axis) { in ExpandTensorDim()
57 const TfLiteTensor& axis, int* axis_value) { in GetAxisValueFromTensor() argument
58 TF_LITE_ENSURE_EQ(context, NumElements(&axis), 1); in GetAxisValueFromTensor()
59 switch (axis.type) { in GetAxisValueFromTensor()
[all …]
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| /external/tensorflow/tensorflow/python/ops/signal/ |
| D | shape_ops.py | 29 def _infer_frame_shape(signal, frame_length, frame_step, pad_end, axis): argument
33 axis = tensor_util.constant_value(axis)
36 if axis is None:
41 frame_axis = signal_shape[axis]
42 outer_dimensions = signal_shape[:axis]
43 inner_dimensions = signal_shape[axis:][1:]
57 def frame(signal, frame_length, frame_step, pad_end=False, pad_value=0, axis=-1, argument
119 axis = ops.convert_to_tensor(axis, name="axis")
124 axis.shape.assert_has_rank(0)
127 axis)
[all …]
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| /external/fonttools/Lib/fontTools/designspaceLib/ |
| D | types.py | 94 axis = doc.getAxis(name)
95 if axis is None:
100 designRegion[name] = axis.map_forward(value)
103 axis.map_forward(value.minimum),
104 axis.map_forward(value.maximum),
105 axis.map_forward(value.default),
116 axis = doc.getAxis(axisSubset.name)
117 if axis is None:
126 if not hasattr(axis, "minimum"):
131 axis = cast(AxisDescriptor, axis)
[all …]
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