| /external/deqp/doc/testspecs/VK/ |
| D | sparse_resources.txt | 27 The test creates two queues - one supporting sparse binding operations, the second one supporting c…
29 First queue is used to perform binding of device memory to sparse buffer. The binding operation sig…
32 The second queue is used to perform transfer operations. The test creates two non-sparse buffer obj…
33 one used as input and the second as output. The input buffer is used to transfer data to sparse buf…
34 transfered further from sparse buffer to output buffer. The transer queue waits on a semaphore, bef…
46 The test creates two queues - one supporting sparse binding operations, the second one supporting c…
48 First queue is used to perform binding of device memory to sparse image. The binding operation sign…
51 The second queue is used to perform transfer operations. The test creates two non-sparse buffer obj…
52 one used as input and the second as output. The input buffer is used to transfer data to sparse ima…
53 transfered further from sparse image to output buffer. The transfer queue waits on a semaphore, bef…
[all …]
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| /external/tensorflow/tensorflow/python/data/ops/ |
| D | dataset_ops.py | 29 from tensorflow.python.data.util import sparse
103 sparse.as_dense_types(self.output_types, self.output_classes)),
105 sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
152 sparse.as_dense_types(self.output_types, self.output_classes)),
154 sparse.as_dense_shapes(self.output_shapes,
932 self._tensors = sparse.serialize_sparse_tensors(tensors)
933 self._output_classes = sparse.get_classes(tensors)
943 sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
976 self._tensors = sparse.serialize_many_sparse_tensors(tensors)
977 self._output_classes = sparse.get_classes(tensors)
[all …]
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| D | iterator_ops.py | 23 from tensorflow.python.data.util import sparse
172 sparse.as_dense_types(output_types, output_classes)),
174 sparse.as_dense_shapes(output_shapes, output_classes)))
241 sparse.as_dense_types(output_types, output_classes)),
243 sparse.as_dense_shapes(output_shapes, output_classes)))
354 return sparse.deserialize_sparse_tensors(
359 sparse.as_dense_types(
363 sparse.as_dense_shapes(
|
| /external/tensorflow/tensorflow/core/util/ |
| D | strided_slice_op.cc | 73 const StridedSliceSparseSpec& sparse, StridedSliceDenseSpec* dense) { in BuildDenseSpec() argument
86 const auto& strides_flat = sparse.strides_tensor.flat<T>(); in BuildDenseSpec()
87 dense->begin_valid = sparse.begin_tensor != nullptr; in BuildDenseSpec()
88 dense->end_valid = sparse.end_tensor != nullptr; in BuildDenseSpec()
90 for (int i = 0; i < sparse.dims; i++) { in BuildDenseSpec()
91 if ((1 << i) & sparse.ellipsis_mask) { in BuildDenseSpec()
94 int32 next_index = std::min(dense->dims - (sparse.dims - i) + 1 + in BuildDenseSpec()
95 sparse.num_add_axis_after_ellipsis, in BuildDenseSpec()
105 } else if ((1 << i) & sparse.new_axis_mask) { in BuildDenseSpec()
115 if (sparse.begin_tensor != nullptr) { in BuildDenseSpec()
[all …]
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| D | example_proto_fast_parsing.cc | 506 std::vector<int64> sparse_feature_last_example(config.sparse.size(), -1); in FastParseSerializedExample()
532 : config.sparse[d].feature_name; in FastParseSerializedExample()
685 example_dtype != config.sparse[d].dtype) { in FastParseSerializedExample()
688 "Expected type: ", DataTypeString(config.sparse[d].dtype), in FastParseSerializedExample()
692 switch (config.sparse[d].dtype) { in FastParseSerializedExample()
773 for (size_t d = 0; d < config.sparse.size(); ++d) { in FastParseSerializedExample()
873 for (auto& c : config.sparse) { in FastParseExample()
880 size_t config_size = config.dense.size() + config.sparse.size(); in FastParseExample()
890 for (size_t d = 0; d < config.sparse.size(); ++d) { in FastParseExample()
891 ok &= config_index.InsertUnique(hasher(config.sparse[d].feature_name), in FastParseExample()
[all …]
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| /external/tensorflow/tensorflow/core/ops/ |
| D | training_ops.cc | 37 static Status HandleGradAndIndicesInputs(InferenceContext* c, bool sparse, in HandleGradAndIndicesInputs() argument
40 if (!sparse) { in HandleGradAndIndicesInputs()
88 bool sparse) { in ApplyProximalGradientDescentShapeFn() argument
95 HandleGradAndIndicesInputs(c, sparse, 4 /* grad_idx */, &s)); in ApplyProximalGradientDescentShapeFn()
156 static Status ApplyAdadeltaShapeFn(InferenceContext* c, bool sparse) { in ApplyAdadeltaShapeFn() argument
166 HandleGradAndIndicesInputs(c, sparse, 6 /* grad_idx */, &s)); in ApplyAdadeltaShapeFn()
235 static Status ApplyAdagradShapeFn(InferenceContext* c, bool sparse) { in ApplyAdagradShapeFn() argument
241 HandleGradAndIndicesInputs(c, sparse, 3 /* grad_idx */, &s)); in ApplyAdagradShapeFn()
271 static Status ApplyProximalAdagradShapeFn(InferenceContext* c, bool sparse) { in ApplyProximalAdagradShapeFn() argument
279 HandleGradAndIndicesInputs(c, sparse, 5 /* grad_idx */, &s)); in ApplyProximalAdagradShapeFn()
[all …]
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| /external/tensorflow/tensorflow/python/data/util/ |
| D | sparse_test.py | 22 from tensorflow.python.data.util import sparse
71 sparse.any_sparse(test_case["classes"]), test_case["expected"])
153 sparse.as_dense_shapes(test_case["types"], test_case["classes"]),
227 sparse.as_dense_types(test_case["types"], test_case["classes"]),
286 sparse.get_classes(test_case["classes"]), test_case["expected"])
317 classes = sparse.get_classes(expected)
321 actual = sparse.deserialize_sparse_tensors(
322 sparse.serialize_sparse_tensors(expected), types, shapes,
323 sparse.get_classes(expected))
346 classes = sparse.get_classes(expected)
[all …]
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| /external/tensorflow/tensorflow/python/training/ |
| D | input_test.py | 741 sparse = sparse_tensor.SparseTensor(
743 self.assertAllEqual((1,), sparse.dense_shape.get_shape().as_list())
744 batched = inp.batch([sparse], batch_size=2)
748 sparse = sparse_tensor.SparseTensor(
750 self.assertAllEqual((1,), sparse.dense_shape.get_shape().as_list())
751 batched = inp.batch([sparse], batch_size=2, enqueue_many=True)
755 sparse = sparse_tensor.SparseTensor(
759 self.assertIs(None, sparse.dense_shape.get_shape().num_elements())
760 batched = inp.batch([sparse], batch_size=2)
764 sparse = sparse_tensor.SparseTensor(
[all …]
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| /external/eigen/doc/ |
| D | TutorialSparse.dox | 7 Manipulating and solving sparse problems involves various modules which are summarized below:
11 …eMatrix and SparseVector classes, matrix assembly, basic sparse linear algebra (including sparse t…
12 … <Eigen/SparseCholesky>\endcode</td><td>Direct sparse LLT and LDLT Cholesky factorization to solve…
14 <td>%Sparse LU factorization to solve general square sparse systems</td></tr>
15 …de<Eigen/SparseQR>\endcode </td><td>%Sparse QR factorization for solving sparse linear least-squar…
22 …ized representation storing only the nonzero coefficients. Such a matrix is called a sparse matrix.
26 The class SparseMatrix is the main sparse matrix representation of Eigen's sparse module; it offers…
45 and one of its possible sparse, \b column \b major representation:
68 The results of %Eigen's operations always produces \b compressed sparse matrices.
97 In this example, we start by defining a column-major sparse matrix type of double \c SparseMatrix<d…
[all …]
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseSlice.pbtxt | 6 2-D tensor represents the indices of the sparse tensor.
12 1-D tensor represents the values of the sparse tensor.
18 1-D. tensor represents the shape of the sparse tensor.
32 sparse tensors.
38 A list of 1-D tensors represents the values of the output sparse
45 A list of 1-D tensors represents the shape of the output sparse
|
| D | api_def_SparseSplit.pbtxt | 13 2-D tensor represents the indices of the sparse tensor.
19 1-D tensor represents the values of the sparse tensor.
25 1-D. tensor represents the shape of the sparse tensor.
27 sparse tensors.
33 A list of 1-D tensors represents the values of the output sparse
40 A list of 1-D tensors represents the shape of the output sparse
|
| D | api_def_SparseFillEmptyRows.pbtxt | 6 2-D. the indices of the sparse tensor.
12 1-D. the values of the sparse tensor.
18 1-D. the shape of the sparse tensor.
25 for rows missing from the input sparse tensor.
26 output indices: 2-D. the indices of the filled sparse tensor.
32 1-D. the values of the filled sparse tensor.
39 input sparse tensor.
|
| D | api_def_SparseAccumulatorApplyGradient.pbtxt | 12 The local_step value at which the sparse gradient was computed.
18 Indices of the sparse gradient to be accumulated. Must be a
33 Shape of the sparse gradient to be accumulated.
50 summary: "Applies a sparse gradient to a given accumulator."
|
| D | api_def_SparseAccumulatorTakeGradient.pbtxt | 18 Indices of the average of the accumulated sparse gradients.
24 Values of the average of the accumulated sparse gradients.
30 Shape of the average of the accumulated sparse gradients.
40 summary: "Extracts the average sparse gradient in a SparseConditionalAccumulator."
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | sparse_add_op_test.py | 52 def _randomTensor(self, size, np_dtype, sparse=True): argument
55 return _sparsify(x) if sparse else x
166 sparse, unused_nnz = _sparsify(rand_vals_np, index_dtype=index_dtype)
167 s = sparse_ops.sparse_add(sparse,
174 sparse).eval()
185 sparse, nnz = _sparsify(rand_vals_np)
187 s = sparse_ops.sparse_add(sparse, dense)
189 err = gradient_checker.compute_gradient_error([sparse.values, dense],
203 sparse = sparse_tensor.SparseTensorValue(bad_idx, val, shape)
204 s = sparse_ops.sparse_add(sparse, dense)
|
| /external/tensorflow/tensorflow/contrib/data/python/ops/ |
| D | interleave_ops.py | 23 from tensorflow.python.data.util import sparse
41 sparse.as_dense_types(input_dataset.output_types,
46 dense_shapes = sparse.as_dense_shapes(input_dataset.output_shapes,
52 nested_args = sparse.deserialize_sparse_tensors(
98 sparse.as_dense_types(self.output_types, self.output_classes)),
100 sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
|
| D | grouping.py | 22 from tensorflow.python.data.util import sparse
148 sparse.as_dense_types(input_dataset.output_types,
153 dense_shapes = sparse.as_dense_shapes(input_dataset.output_shapes,
159 nested_args = sparse.deserialize_sparse_tensors(
221 sparse.as_dense_types(self.output_types, self.output_classes)),
223 sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
|
| D | scan_ops.py | 24 from tensorflow.python.data.util import sparse
72 sparse.as_dense_types(input_dataset.output_types,
78 dense_shapes = sparse.as_dense_shapes(input_dataset.output_shapes,
156 sparse.as_dense_types(self.output_types, self.output_classes)),
158 sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
|
| /external/deqp/external/openglcts/docs/specs/ |
| D | CTS_ARB_sparse_texture_clamp.txt | 50 * Iterate through all sparse supported targets.
51 Allocate sparse texture for current <target> with committed and
70 … that the texels will be filled with (1, 1, 1, 1) if the areas of the sparse texture accessed
75 Sparse and Non-sparse Texture Clamp Lookup Color Tests
77 * Iterate through all sparse and non-sparse supported targets.
|
| /external/smali/baksmali/src/test/resources/SwitchTest/ |
| D | UnorderedSparseSwitchInput.smali | 9 sparse-switch v0, :SparseSwitch
28 .sparse-switch
34 .end sparse-switch
|
| D | UnorderedSparseSwitchOutput.smali | 6 sparse-switch v0, :sswitch_data_c
21 .sparse-switch
27 .end sparse-switch
|
| /external/lz4/tests/ |
| D | Makefile | 143 test-lz4-sparse: lz4 datagen
146 $(LZ4) -B4D tmpSrc | $(LZ4) -dv --sparse > tmpB4
148 $(LZ4) -B5D tmpSrc | $(LZ4) -dv --sparse > tmpB5
150 $(LZ4) -B6D tmpSrc | $(LZ4) -dv --sparse > tmpB6
152 $(LZ4) -B7D tmpSrc | $(LZ4) -dv --sparse > tmpB7
154 $(LZ4) tmpSrc | $(LZ4) -dv --no-sparse > tmpNoSparse
157 …./datagen -s1 -g1200007 -P100 | $(LZ4) | $(LZ4) -dv --sparse > tmpOdd # Odd size file (to genera…
182 @./datagen -g3G -P100 | $(LZ4) -vv | $(LZ4) --decompress --force --sparse - tmp
184 … -g3G -P100 | $(LZ4) --quiet --content-size | $(LZ4) --verbose --decompress --force --sparse - tmp2
293 test-lz4: lz4 datagen test-lz4-opt-parser test-lz4-basic test-lz4-multiple test-lz4-sparse \
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/python/ops/ |
| D | data_ops.py | 57 self.sparse = DataColumnCollection()
64 self.sparse.SerializeToString())
133 elif data_spec.sparse.size() == 0:
134 col_spec = data_spec.sparse.add()
166 col_spec = data_spec.sparse.add()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | edit_distance_op.cc | 136 sparse::SparseTensor hypothesis(*hypothesis_indices, *hypothesis_values, in Compute()
138 sparse::SparseTensor truth(*truth_indices, *truth_values, truth_st_shape, in Compute()
173 sparse::Group truth_i = *truth_iter; in Compute()
174 sparse::Group hypothesis_j = *hypothesis_iter; in Compute()
205 sparse::Group hypothesis_j = *hypothesis_iter; in Compute()
217 sparse::Group truth_i = *truth_iter; in Compute()
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| /external/tensorflow/tensorflow/core/kernels/data/ |
| D | sparse_tensor_slice_dataset_op.cc | 34 const sparse::SparseTensor& sparse_tensor) in Dataset()
110 sparse::Group group = *iter_; in GetNextInternal()
195 sparse::GroupIterable group_iterable_ GUARDED_BY(mu_);
196 sparse::GroupIterable::IteratorStep iter_ GUARDED_BY(mu_);
204 const sparse::SparseTensor sparse_tensor_;
255 sparse::SparseTensor sparse_tensor( in MakeDataset()
|