| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| pack_op.cc | 47 std::vector<TensorShape> shapes; variable
48 OP_REQUIRES_OK(ctx, ctx->InputList("values", &values, &shapes));
54 // Verify that all input shapes match
56 OP_REQUIRES(ctx, shapes[0].IsSameSize(shapes[i]),
58 "Shapes of all inputs must match: values[0].shape = ",
59 shapes[0].DebugString(), " != values[", i, "].shape = ",
60 shapes[i].DebugString()));
63 int expanded_num_dims = shapes[0].dims() + 1;
74 TensorShape child_shape(shapes[0])
[all...] |
| bcast_ops.cc | 30 // Given shapes of two tensors, computes the broadcast shape.
41 gtl::InlinedVector<BCast::Vec, 2> shapes; variable
49 shapes.push_back(BCast::Vec(shape.begin(), shape.end()));
51 BCast bcast(shapes[0], shapes[1]);
54 "Incompatible shapes: [", str_util::Join(shapes[0], ","),
55 "] vs. [", str_util::Join(shapes[1], ","), "]"));
73 // Given shapes of two tensors, computes the reduction indices for the
90 gtl::InlinedVector<BCast::Vec, 4> shapes; variable
[all...] |
| /external/tensorflow/tensorflow/contrib/tpu/ops/ |
| outfeed_ops.cc | 68 .Attr("shapes: list(shape)")
72 std::vector<PartialTensorShape> shapes;
74 TF_RETURN_IF_ERROR(c->GetAttr("shapes", &shapes));
76 if (shapes.size() != dtypes.size()) {
78 "Incorrect number of output shapes specified");
80 for (int i = 0; i < shapes.size(); ++i) {
82 TF_RETURN_IF_ERROR(c->MakeShapeFromPartialTensorShape(shapes[i], &out));
94 shapes: The shapes of each tensor in `outputs`
[all...] |
| infeed_ops.cc | 60 .Attr("shapes: list(shape)")
69 shapes: The shapes of each tensor in `inputs`.
78 .Attr("shapes: list(shape)")
81 std::vector<PartialTensorShape> shapes;
82 TF_RETURN_IF_ERROR(c->GetAttr("shapes", &shapes));
83 for (int i = 0; i < shapes.size(); ++i) {
85 TF_RETURN_IF_ERROR(c->MakeShapeFromPartialTensorShape(shapes[i], &out));
96 shapes: The shapes of each tensor in `outputs`
[all...] |
| /external/gemmlowp/meta/generators/ |
| quantized_mul_kernels_arm_32.py | 32 shapes = [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8),
37 shapes)
|
| quantized_mul_kernels_arm_64.py | 32 shapes = [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (1, 7), (1, 8),
37 shapes)
|
| /external/tensorflow/tensorflow/core/kernels/ |
| sparse_concat_op.cc | 64 OpInputList shapes; variable
65 OP_REQUIRES_OK(context, context->input_list("shapes", &shapes));
66 OP_REQUIRES(context, shapes.size() == N,
67 errors::InvalidArgument("Expected ", N, " input shapes, got ",
68 shapes.size()));
70 OP_REQUIRES(context, TensorShapeUtils::IsVector(shapes[i].shape()),
72 "Input shapes should be a vector but received shape ",
73 shapes[i].shape().DebugString(), " at position ", i));
76 const TensorShape input_shape(shapes[0].vec<int64>())
[all...] |
| bcast_ops.cc | 24 // Given shapes of two tensors, computes the broadcast shape.
34 gtl::InlinedVector<BCast::Vec, 4> shapes; variable
44 shapes.push_back(vec);
46 BCast bcast(shapes[0], shapes[1]);
49 "Incompatible shapes: [", str_util::Join(shapes[0], ","),
50 "] vs. [", str_util::Join(shapes[1], ","), "]"));
69 // Given shapes of two tensors, computes the reduction indices for the
83 gtl::InlinedVector<BCast::Vec, 4> shapes; variable
[all...] |
| /external/tensorflow/tensorflow/core/ops/ |
| parsing_ops_test.cc | 65 std::vector<PartialTensorShape> shapes(size);
67 // Make shapes be the sequence [?,1]; [?,1,2], [?,1,2,3]...
70 shapes[i].Clear();
72 shapes[i].AddDim(-1);
75 shapes[i] = shapes[i - 1];
77 shapes[i].AddDim(i + 1);
79 if (add_extra_shape) shapes.push_back(PartialTensorShape({}));
80 return shapes;
142 INFER_ERROR("shapes[0] has unknown rank or unknown inner dimensions", op
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| input.py | 181 shapes=[element_shape],
344 # everything in TensorList matches. Maybe just check the inferred shapes?
648 # We want the shapes without the leading batch dimension.
656 def _shapes(tensor_list_list, shapes, enqueue_many):
657 """Calculate and merge the shapes of incoming tensors.
661 shapes: List of shape tuples corresponding to tensors within the lists.
662 enqueue_many: Boolean describing whether shapes will be enqueued as
666 A list of shapes aggregating shape inference info from `tensor_list_list`,
667 or returning `shapes` if it is not `None`.
670 ValueError: If any of the inferred shapes in `tensor_list_list` lack
[all...] |
| /external/harfbuzz_ng/src/ |
| gen-arabic-table.py | 152 shapes = {}
185 if items[0] not in shapes:
186 shapes[items[0]] = {}
187 shapes[items[0]][shape] = c
193 keys = shapes.keys ()
196 s = [shapes[u][shape] if u in shapes and shape in shapes[u] else 0
212 liga = (shapes[pair[0]]['initial'], shapes[pair[1]]['final']
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| model_analyzer.py | 65 print('Operations: name -> (type shapes) [size]')
70 shapes = []
75 shapes.append(tensor_description(output))
78 print(op.name, '\t->', ', '.join(shapes), '[' + str(op_size) + ']')
84 """Prints the names and shapes of the variables.
|
| /external/tensorflow/tensorflow/python/data/util/ |
| sparse.py | 40 def as_dense_shapes(shapes, classes):
41 """Converts sparse tensor shapes to their physical shapes.
44 shapes: a structure of shapes to convert.
48 a structure matching the nested structure of `shapes`, containing
50 `tf.SparseTensor` and matching contents of `shapes` otherwise
52 ret = nest.pack_sequence_as(shapes, [
54 for shape, c in zip(nest.flatten(shapes), nest.flatten(classes))
78 def deserialize_sparse_tensors(tensors, types, shapes, classes)
[all...] |
| /development/samples/ApiDemos/src/com/example/android/apis/graphics/kube/ |
| Kube.java | 151 GLShape[] shapes; local
156 shapes = layer.mShapes;
158 shapes[i] = mCubes[mPermutation[i]];
162 shapes = layer.mShapes;
164 shapes[k++] = mCubes[mPermutation[i]];
168 shapes = layer.mShapes;
171 shapes[k++] = mCubes[mPermutation[i + j]];
175 shapes = layer.mShapes;
178 shapes[k++] = mCubes[mPermutation[i + j]];
182 shapes = layer.mShapes
[all...] |
| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| bucket_ops.py | 70 shapes=None,
98 (i) the `shapes` argument is passed, or (ii) all of the tensors in
99 `tensors` must have fully-defined shapes. `ValueError` will be
113 In addition, all output tensors' static shapes, as accessed via the
133 shapes: (Optional) The shapes for each example. Defaults to the
134 inferred shapes for `tensors`.
135 dynamic_pad: Boolean. Allow variable dimensions in input shapes.
137 batch have the same shapes.
155 ValueError: If the `shapes` are not specified, and cannot b
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| data_flow_ops.py | 57 def _as_shape_list(shapes,
61 """Convert shapes to a list of tuples of int (or None)."""
64 if (not isinstance(shapes, collections.Sequence) or not shapes or
65 any(shape is None or isinstance(shape, int) for shape in shapes)):
67 "When providing partial shapes, a list of shapes must be provided.")
68 if shapes is None:
70 if isinstance(shapes, tensor_shape.TensorShape):
71 shapes = [shapes
244 def shapes(self): member in class:QueueBase
1528 def shapes(self): member in class:BaseStagingArea
[all...] |
| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| prefetch_queue.py | 59 dynamic_pad: Boolean. Whether to allow variable dimensions in input shapes.
79 shapes = [t.get_shape() for t in tensor_list]
83 shapes=shapes,
|
| /frameworks/base/graphics/java/android/graphics/drawable/shapes/ |
| ArcShape.java | 17 package android.graphics.drawable.shapes;
|
| /external/ImageMagick/Magick++/demo/ |
| demos.tap | 20 for demo in button demo flip gravity piddle shapes
|
| /external/ImageMagick/PerlMagick/demo/ |
| Makefile | 4 perl shapes.pl
|
| /external/tensorflow/tensorflow/contrib/tpu/python/ops/ |
| tpu_ops.py | 77 def infeed_dequeue_tuple(dtypes, shapes, name=None):
83 shapes: A list of shapes (each a `tf.TensorShape` or list of `ints`).
84 The shapes of each tensor in `outputs`.
99 return gen_tpu_ops.infeed_dequeue_tuple(dtypes, shapes, name=name)
|
| /external/tensorflow/tensorflow/python/keras/_impl/keras/utils/ |
| np_utils_test.py | 31 shapes = [(1,), (3,), (4, 3), (5, 4, 3), (3, 1), (3, 2, 1)]
37 labels = [np.random.randint(0, num_classes, shape) for shape in shapes]
|
| /external/gemmlowp/test/ |
| benchmark_all_sizes.cc | 278 std::vector<Shape> shapes; local
286 shapes.push_back(shape);
288 // Benchmark an assortment of cubic shapes
294 shapes.push_back(shape);
297 // Benchmark all sorts of shapes
305 shapes.push_back(shape);
310 #error What shapes should we benchmark? (Suggestion: #define BENCHMARK_QUICK)
312 std::shuffle(std::begin(shapes), std::end(shapes), RandomEngine());
313 return shapes;
317 std::vector<Shape> shapes; local
[all...] |
| /external/tensorflow/tensorflow/contrib/hvx/hvx_ops_support_checker/ |
| hvx_ops_support_checker_main.cc | 65 std::vector<TensorShape> shapes; local
67 node_def, &data_types, &shapes);
68 if (data_types.empty() || shapes.empty()) {
71 CHECK_EQ(data_types.size(), shapes.size());
74 << ", " << shapes.at(i).DebugString();
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| cholesky_op_test.py | 197 shapes = self.getShapes([1, 2, 10])
199 shapes, dtypes=(dtypes_lib.float32, dtypes_lib.float64))
203 shapes = self.getShapes([1, 2, 10])
205 shapes, dtypes=(dtypes_lib.complex64, dtypes_lib.complex128))
209 shapes = self.getShapes([self._backprop_block_size + 1])
211 shapes,
217 shapes = self.getShapes([2 * self._backprop_block_size + 1])
219 shapes, dtypes=(dtypes_lib.float32,), scalarTest=True)
223 shapes = self.getShapes([2 * self._backprop_block_size + 1])
225 shapes, dtypes=(dtypes_lib.float64,), scalarTest=True
303 shapes = [ variable in class:CholeskyBenchmark
[all...] |
