| /external/guice/extensions/grapher/src/com/google/inject/grapher/graphviz/ |
| NodeShape.java | 31 private final String shape; field in class:NodeShape
33 NodeShape(String shape) {
34 this.shape = shape;
39 return shape;
|
| /external/snakeyaml/src/test/java/org/yaml/snakeyaml/javabeans/ |
| TriangleBean.java | 20 private Shape shape; field in class:TriangleBean
30 public Shape getShape() {
31 return shape;
34 public void setShape(Shape shape) {
35 this.shape = shape;
|
| /external/tensorflow/tensorflow/java/src/main/java/org/tensorflow/ |
| Shape.java | 20 /** The possibly partially known shape of a tensor produced by an operation. */
21 public final class Shape {
23 /** Create a Shape representing an unknown number of dimensions. */
24 public static Shape unknown() {
25 return new Shape(null);
28 /** Create a Shape representing a scalar value. */
29 public static Shape scalar() {
30 return new Shape(new long[0]);
34 * Create a Shape representing an N-dimensional value.
36 * <p>Creates a Shape representing an N-dimensional value (N being at least 1), with the provide
55 long[] shape = new long[otherDimensionSizes.length + 1]; local
118 private long[] shape; field in class:Shape
[all...] |
| /external/libtextclassifier/ |
| tensor-view.cc | 22 int NumberOfElements(const std::vector<int>& shape) {
24 for (const int dim : shape) {
|
| /external/tensorflow/tensorflow/contrib/timeseries/examples/ |
| predict_test.py | 40 self.assertAllEqual([500], times.shape)
41 self.assertAllEqual([500], observed.shape)
42 self.assertAllEqual([700], all_times.shape)
43 self.assertAllEqual([700], mean.shape)
44 self.assertAllEqual([700], upper_limit.shape)
45 self.assertAllEqual([700], lower_limit.shape)
54 self.assertAllEqual(times.shape, observed.shape)
55 self.assertAllEqual(all_times.shape, mean.shape)
[all...] |
| known_anomaly_test.py | 35 self.assertAllEqual([200], times.shape)
36 self.assertAllEqual([200], observed.shape)
37 self.assertAllEqual([300], all_times.shape)
38 self.assertAllEqual([300], mean.shape)
39 self.assertAllEqual([300], upper_limit.shape)
40 self.assertAllEqual([300], lower_limit.shape)
|
| /external/tensorflow/tensorflow/compiler/xla/client/lib/ |
| testing.cc | 35 // specified shape. In case of a (nested) tuple shape this is the total byte
37 int64 DataSizeOfShape(const Shape& shape) {
38 if (ShapeUtil::IsArray(shape)) {
39 return ShapeUtil::ByteSizeOf(shape);
43 for (const Shape& s : shape.tuple_shapes()) {
50 // given shape.
51 ComputationDataHandle BuildFakeDataOpOnDevice(const Shape& shape
[all...] |
| /libcore/ojluni/src/test/java/util/stream/bootlib/java/util/stream/ |
| FlagDeclaringOp.java | 31 private final StreamShape shape; field in class:FlagDeclaringOp
37 public FlagDeclaringOp(int flags, StreamShape shape) {
39 this.shape = shape;
44 return shape;
49 return shape;
|
| /libcore/ojluni/src/test/java/util/stream/testlib/org/openjdk/testlib/java/util/stream/ |
| FlagDeclaringOp.java | 34 private final StreamShape shape; field in class:FlagDeclaringOp
40 public FlagDeclaringOp(int flags, StreamShape shape) {
42 this.shape = shape;
47 return shape;
52 return shape;
|
| /external/tensorflow/tensorflow/compiler/tf2xla/ |
| shape_util.h | 27 // Convert an XLA Shape into the equivalent TensorFlow shape. May fail since
29 Status XLAShapeToTensorShape(const xla::Shape& shape,
32 // Convert a TensorShape into the equivalent XLA Shape proto. Unlike Tensorflow,
36 xla::Shape* shape);
|
| literal_util.cc | 26 xla::Shape literal_shape;
28 host_tensor.dtype(), host_tensor.shape(), &literal_shape));
45 TF_RET_CHECK(xla::ShapeUtil::IsArray(literal.shape()) &&
46 xla::ShapeUtil::ElementsIn(literal.shape()) ==
51 if (literal.shape().element_type() != primitive_type) {
54 xla::PrimitiveType_Name(literal.shape().element_type()),
68 TensorShape shape; local
69 TF_RETURN_IF_ERROR(XLAShapeToTensorShape(literal.shape(), &shape));
70 *host_tensor = Tensor(target_type, shape);
[all...] |
| /toolchain/binutils/binutils-2.27/gas/testsuite/gas/arm/ |
| neon-vmov-bad.l | 2 [^:]*:3: Error: invalid instruction shape -- `vmov Q0,d0'
|
| /external/tensorflow/tensorflow/contrib/solvers/python/ops/ |
| util.py | 33 "LinearOperator", ["shape", "dtype", "apply", "apply_adjoint"])
36 shape = matrix.get_shape()
37 if shape.is_fully_defined():
38 shape = shape.as_list()
40 shape = array_ops.shape(matrix)
42 shape=shape,
52 "LinearOperator", ["shape", "dtype", "apply", "apply_adjoint"]
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/ |
| layout_util.cc | 89 /* static */ Layout LayoutUtil::GetDefaultLayoutForShape(const Shape& shape) {
91 DCHECK(!ShapeUtil::IsTuple(shape));
92 return CreateDefaultLayoutForRank(shape.dimensions_size());
111 /* static */ void LayoutUtil::SetToDefaultLayout(Shape* shape) {
112 if (ShapeUtil::IsTuple(*shape)) {
113 // Tuple shape.
114 for (auto& element_shape : *shape->mutable_tuple_shapes()) {
117 shape->clear_layout()
[all...] |
| shape_util.cc | 72 bool CompareShapes(const Shape& lhs, const Shape& rhs, bool compare_layouts) {
76 [=](const Shape& l, const Shape& r) {
117 // Constructs and returns the new shape with the given minor_to_major order in
119 StatusOr<Shape> MakeShapeWithLayoutInternal(
130 Shape shape = ShapeUtil::MakeShape(element_type, dimensions); local
131 auto min2maj = shape.mutable_layout()->mutable_minor_to_major();
136 if (!shape.has_layout())
210 Shape shape = ShapeUtil::MakeShape(element_type, dimensions); local
821 << "Invalid index " << index << " for shape " << shape; local
[all...] |
| index_util.cc | 30 const Shape& shape, tensorflow::gtl::ArraySlice<int64> multi_index) {
31 DCHECK_EQ(shape.dimensions_size(), multi_index.size());
33 DCHECK_EQ(0, shape.layout().padded_dimensions_size());
37 DCHECK_LT(multi_index[i], shape.dimensions(i))
40 << "\n\tshape: " << ShapeUtil::HumanString(shape);
81 for (auto dimension : LayoutUtil::MinorToMajor(shape)) {
85 scale = shape.dimensions(dimension);
89 scale *= shape.dimensions(dimension);
96 const Shape& shape, int64 linear_index)
[all...] |
| shape_layout.h | 28 // A ShapeLayout object encapsulates the layout of a particular shape (including
30 // single array. ShapeLayout contains a Layout proto for each array in the shape
33 // shape with mutable layouts.
36 // Constructs a ShapeLayout of the given shape. Layouts are copied from the
37 // shape parameter.
38 explicit ShapeLayout(const Shape& shape) : shape_(shape) {}
41 // shape. 'to_shape' and the shape of the ShapeLayout object must b
62 const Shape& shape() const { return shape_; } function in class:xla::ShapeLayout
[all...] |
| shape_util.h | 37 // An index for specifying a particular nested subshape within a shape. Used in
41 // shape. For a non-nested tuple, an index has a single element. For example,
143 // Namespaced collection of (static) shape utilities.
149 // Returns the number of elements are contained within the provided shape;
152 // LayoutUtil::MaxSparseElements(shape) to obtain the maximum number of
153 // elements that can be stored in a sparse shape.
154 // Precondition: !IsTuple(shape)
155 static int64 ElementsIn(const Shape& shape);
157 // Returns true if 'shape' has zero elements
[all...] |
| /development/samples/ApiDemos/src/com/example/android/apis/animation/ |
| ShapeHolder.java | 22 import android.graphics.drawable.shapes.Shape;
26 * A data structure that holds a Shape and various properties that can be used to define
27 * how the shape is drawn.
31 private ShapeDrawable shape; field in class:ShapeHolder
57 shape = value;
60 return shape;
66 shape.getPaint().setColor(value);
78 shape.setAlpha((int)((alpha * 255f) + .5f));
82 return shape.getShape().getWidth();
85 Shape s = shape.getShape()
[all...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| reverse_ops_test.py | 34 shape = (7, 5, 9, 11)
35 for revdim in range(len(shape)):
36 self._AssertReverseEqual([revdim], shape)
39 shape = (7, 5, 9, 11)
41 itertools.combinations(range(len(shape)), k)
42 for k in range(2, len(shape)+1)):
43 self._AssertReverseEqual(revdims, shape)
45 def _AssertReverseEqual(self, revdims, shape):
47 pval = np.random.randint(0, 100, size=shape).astype(float)
50 p = array_ops.placeholder(dtypes.int32, shape=shape
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| partitioned_variables.py | 42 <shape>, <slicing>, <initializer>, name=<optional-name>)
111 def _partitioner(shape, dtype):
115 shape: A `TensorShape`.
119 A tuple representing how much to slice each axis in shape.
122 ValueError: If shape is not a fully defined `TensorShape` or dtype is not
125 if not isinstance(shape, tensor_shape.TensorShape):
126 raise ValueError("shape is not a TensorShape: %s" % shape)
127 if not shape.is_fully_defined():
128 raise ValueError("shape is not fully defined: %s" % shape
[all...] |
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| softmax_centered.py | 102 ndims = array_ops.shape(input_shape)
104 # It is not possible for a negative shape so we need only check <= 1.
124 ndims = array_ops.shape(output_shape)[0]
126 # It is not possible for a negative shape so we need only check <= 1.
140 # Set shape hints.
141 if x.shape.ndims is not None:
142 shape = x.shape.as_list()
144 shape += [2]
145 elif shape[-1] is not None
[all...] |
| /external/tensorflow/tensorflow/compiler/xla/service/cpu/ |
| cpu_hlo_support_checker.cc | 29 ShapeUtil::ValidateShapeWithOptionalLayout(instruction->shape()));
31 instruction->shape(),
32 [&instruction](const Shape& subshape, const ShapeIndex&) {
35 "CPU backend does not support HLO instruction %s with shape "
38 ShapeUtil::HumanStringWithLayout(instruction->shape())
|
| /external/tensorflow/tensorflow/compiler/xla/service/gpu/ |
| gpu_hlo_support_checker.cc | 29 ShapeUtil::ValidateShapeWithOptionalLayout(instruction->shape()));
31 instruction->shape(),
32 [&instruction](const Shape& subshape, const ShapeIndex&) {
35 "GPU backend does not support HLO instruction %s with shape "
38 ShapeUtil::HumanStringWithLayout(instruction->shape())
|
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| zero_sized_hlo_elimination.cc | 35 ShapeUtil::IsTuple(instruction->shape())) {
39 ShapeUtil::HasZeroElements(instruction->shape())) {
42 Literal::CreateFromShape(instruction->shape()))));
|
