| /external/tensorflow/tensorflow/python/layers/ |
| D | core_test.py | 46 dense = core_layers.Dense(2, activation=nn_ops.relu, name='my_dense')
47 self.assertEqual(dense.units, 2)
48 self.assertEqual(dense.activation, nn_ops.relu)
49 self.assertEqual(dense.kernel_regularizer, None)
50 self.assertEqual(dense.bias_regularizer, None)
51 self.assertEqual(dense.activity_regularizer, None)
52 self.assertEqual(dense.use_bias, True)
55 dense = core_layers.Dense(2, activation=nn_ops.relu)
56 dense.apply(random_ops.random_uniform((5, 2)))
57 self.assertEqual(dense.name, 'dense_1')
[all …]
|
| /external/tensorflow/tensorflow/core/util/ |
| D | strided_slice_op.cc | 73 const StridedSliceSparseSpec& sparse, StridedSliceDenseSpec* dense) { in BuildDenseSpec() argument
76 dense->begin.resize(dense->dims); in BuildDenseSpec()
77 dense->end.resize(dense->dims); in BuildDenseSpec()
78 dense->strides.resize(dense->dims); in BuildDenseSpec()
80 dense->begin_mask = 0; in BuildDenseSpec()
81 dense->end_mask = 0; in BuildDenseSpec()
82 dense->shrink_axis_mask = 0; in BuildDenseSpec()
87 dense->begin_valid = sparse.begin_tensor != nullptr; in BuildDenseSpec()
88 dense->end_valid = sparse.end_tensor != nullptr; in BuildDenseSpec()
101 int32 next_index = std::min(dense->dims - (sparse.dims - i) + 1 + in BuildDenseSpec()
[all …]
|
| D | example_proto_fast_parsing.cc | 545 std::vector<int64> dense_feature_last_example(config.dense.size(), -1); in FastParseSerializedExample()
577 ? config.dense[d].feature_name in FastParseSerializedExample()
606 if (example_dtype != config.dense[d].dtype) { in FastParseSerializedExample()
610 " but expected type: ", DataTypeString(config.dense[d].dtype))); in FastParseSerializedExample()
612 if (!config.dense[d].variable_length) { in FastParseSerializedExample()
615 const std::size_t num_elements = config.dense[d].elements_per_stride; in FastParseSerializedExample()
631 " but output shape: ", config.dense[d].shape.DebugString())); in FastParseSerializedExample()
634 switch (config.dense[d].dtype) { in FastParseSerializedExample()
668 const std::size_t num_elements = config.dense[d].elements_per_stride; in FastParseSerializedExample()
671 example_dtype != config.dense[d].dtype) { in FastParseSerializedExample()
[all …]
|
| /external/eigen/Eigen/src/SparseLU/ |
| D | SparseLU_kernel_bmod.h | 33 …static EIGEN_DONT_INLINE void run(const Index segsize, BlockScalarVector& dense, ScalarVector& tem…
39 …l_bmod<SegSizeAtCompileTime>::run(const Index segsize, BlockScalarVector& dense, ScalarVector& tem… in run() argument
52 tempv(i) = dense(irow); in run()
80 dense(irow) = tempv(i); in run()
87 dense(irow) -= l(i); in run()
94 …static EIGEN_DONT_INLINE void run(const Index /*segsize*/, BlockScalarVector& dense, ScalarVector&…
100 EIGEN_DONT_INLINE void LU_kernel_bmod<1>::run(const Index /*segsize*/, BlockScalarVector& dense, Sc…
105 Scalar f = dense(lsub(lptr + no_zeros));
116 Scalar d0 = dense.coeff(i0);
117 Scalar d1 = dense.coeff(i1);
[all …]
|
| D | SparseLUImpl.h | 42 Index snode_bmod (const Index jcol, const Index fsupc, ScalarVector& dense, GlobalLU_t& glu);
49 …ndex jcol, MatrixType& A, IndexVector& perm_r, Index& nseg, ScalarVector& dense, IndexVector& pane…
51 …Index m, const Index w, const Index jcol, const Index nseg, ScalarVector& dense, ScalarVector& tem…
53 …Index column_bmod(const Index jcol, const Index nseg, BlockScalarVector dense, ScalarVector& tempv…
54 …& segrep, BlockIndexVector repfnz ,IndexVector& perm_r, BlockScalarVector dense, GlobalLU_t& glu);
|
| D | SparseLU_column_bmod.h | 53 …Index>::column_bmod(const Index jcol, const Index nseg, BlockScalarVector dense, ScalarVector& tem… in column_bmod() argument
106 …LU_kernel_bmod<1>::run(segsize, dense, tempv, glu.lusup, luptr, lda, nrow, glu.lsub, lptr, no_zero… in column_bmod()
108 …LU_kernel_bmod<Dynamic>::run(segsize, dense, tempv, glu.lusup, luptr, lda, nrow, glu.lsub, lptr, n… in column_bmod()
131 glu.lusup(nextlu) = dense(irow); in column_bmod()
132 dense(irow) = Scalar(0.0); in column_bmod()
|
| D | SparseLU_copy_to_ucol.h | 51 … BlockIndexVector repfnz ,IndexVector& perm_r, BlockScalarVector dense, GlobalLU_t& glu) in copy_to_ucol() argument
89 glu.ucol(nextu) = dense(irow); in copy_to_ucol()
90 dense(irow) = Scalar(0.0); in copy_to_ucol()
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | sparse_to_dense_op_py_test.py | 114 dense = _SparseToDense([1, 3], [5], [[5], [3]], -1)
118 self.evaluate(dense)
123 dense = _SparseToDense([1, 3], [5], [1, 2, 3], -1)
126 self.evaluate(dense)
131 dense = _SparseToDense([1, 3], [5], [1, 2], [0])
133 self.evaluate(dense)
138 dense = _SparseToDense(
145 self.evaluate(dense)
159 dense = _SparseToDense(
165 self.evaluate(dense)
[all …]
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | topology_test.py | 198 dense = keras.layers.Dense(16, name='dense_1')
199 a_2 = dense(a)
200 b_2 = dense(b)
202 self.assertEqual(dense.get_input_at(0), a)
203 self.assertEqual(dense.get_input_at(1), b)
204 self.assertEqual(dense.get_output_at(0), a_2)
205 self.assertEqual(dense.get_output_at(1), b_2)
206 self.assertEqual(dense.get_input_shape_at(0), (None, 32))
207 self.assertEqual(dense.get_input_shape_at(1), (None, 32))
208 self.assertEqual(dense.get_output_shape_at(0), (None, 16))
[all …]
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseToDense.pbtxt | 13 1-D. Shape of the dense output tensor.
31 name: "dense"
43 summary: "Converts a sparse representation into a dense tensor."
45 Builds an array `dense` with shape `output_shape` such that
49 dense[i] = (i == sparse_indices ? sparse_values : default_value)
52 dense[sparse_indices[i]] = sparse_values[i]
55 dense[sparse_indices[i][0], ..., sparse_indices[i][d-1]] = sparse_values[i]
58 All other values in `dense` are set to `default_value`. If `sparse_values` is a
|
| D | api_def_SparseReshape.pbtxt | 13 1-D. `R_in` vector with the input SparseTensor's dense shape.
19 1-D. `R_out` vector with the requested new dense shape.
32 1-D. `R_out` vector with the full dense shape of the output
37 summary: "Reshapes a SparseTensor to represent values in a new dense shape."
39 This operation has the same semantics as reshape on the represented dense
43 dimension is computed so that the total dense size remains constant. At
44 most one component of `new_shape` can be -1. The number of dense elements
45 implied by `new_shape` must be the same as the number of dense elements
|
| D | api_def_SparseDenseCwiseMul.pbtxt | 23 name: "dense"
25 `R`-D. The dense Tensor operand.
34 summary: "Component-wise multiplies a SparseTensor by a dense Tensor."
38 contents of the dense tensor (even if it's +/-INF and that INF*0 == NaN).
40 *Limitation*: this Op only broadcasts the dense side to the sparse side, but not
|
| D | api_def_SparseDenseCwiseAdd.pbtxt | 23 name: "dense"
25 `R`-D. The dense Tensor operand.
34 summary: "Adds up a SparseTensor and a dense Tensor, using these special rules:"
36 (1) Broadcasts the dense side to have the same shape as the sparse side, if
38 (2) Then, only the dense values pointed to by the indices of the SparseTensor
|
| D | api_def_SparseDenseCwiseDiv.pbtxt | 23 name: "dense"
25 `R`-D. The dense Tensor operand.
34 summary: "Component-wise divides a SparseTensor by a dense Tensor."
36 *Limitation*: this Op only broadcasts the dense side to the sparse side, but not
|
| /external/tensorflow/tensorflow/core/kernels/ |
| D | sparse_dense_binary_op_shared_test.cc | 106 Tensor dense(DT_FLOAT, TensorShape(shape)); in TEST_F() local
107 auto dense_flat = dense.flat<float>(); in TEST_F()
134 Tensor dense(DT_FLOAT, TensorShape({3, 1})); in TEST_F() local
135 auto dense_flat = dense.flat<float>(); in TEST_F()
161 Tensor dense(DT_FLOAT, TensorShape({2})); in TEST_F() local
162 auto dense_flat = dense.flat<float>(); in TEST_F()
193 Tensor dense(DT_FLOAT, TensorShape({2})); in TEST_F() local
194 auto dense_flat = dense.flat<float>(); in TEST_F()
213 Node* sp_shape, Node* dense) { in SparseMatCMulDenseMat() argument
220 .Input(dense) in SparseMatCMulDenseMat()
[all …]
|
| /external/eigen/doc/ |
| D | ClassHierarchy.dox | 31 …- Matrix means plain dense matrix. If \c m is a \c %Matrix, then, for instance, \c m+m is no longe…
33 …- MatrixBase means dense matrix expression. This means that a \c %MatrixBase is something that can…
36 …- Array means plain dense array. If \c x is an \c %Array, then, for instance, \c x+x is no longer …
38 …- ArrayBase means dense array expression. This means that an \c %ArrayBase is something that can be
41 …- DenseBase means dense (matrix or array) expression. Both \c %ArrayBase and \c %MatrixBase inherit
42 …\c %DenseBase. \c %DenseBase is where all the methods go that apply to dense expressions regardles…
51 …- PlainObjectBase means dense (matrix or array) plain object, i.e. something that stores its own d…
58 - DenseCoeffsBase means something that has dense coefficient accessors. It is a base class for
60 …accessors is very different depending on whether a dense expression has direct memory access or no…
65 …- EigenBase means anything that can be evaluated into a plain dense matrix or array (even if that …
[all …]
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | rev_block_lib_test.py | 48 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
51 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
71 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
74 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
102 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
107 return core_layers.dense(x, self.CHANNELS // 2, use_bias=True)
169 return core_layers.dense(
177 return core_layers.dense(x, self.CHANNELS // 2)
180 return core_layers.dense(x, self.CHANNELS // 2, activation=nn_ops.relu)
201 return core_layers.dense(x, self.CHANNELS // 2)
[all …]
|
| /external/tensorflow/tensorflow/python/keras/saving/ |
| D | saving_utils_test.py | 102 dense = keras.layers.Dense(num_classes, name='dense')
105 branch_a = [input_a, dense]
106 branch_b = [input_b, dense, dense2, dropout]
154 self.dense = keras.layers.Dense(3, name='dense')
161 return self.dense(x) + y
217 dense = keras.layers.Dense(4, name='dense')
218 c = dense(a)
219 d = dense(b)
|
| /external/tensorflow/tensorflow/core/ops/ |
| D | parsing_ops.cc | 87 ShapeHandle dense; in __anonb04296470202() local
89 c->MakeShapeFromPartialTensorShape(attrs.dense_shapes[i], &dense)); in __anonb04296470202()
90 TF_RETURN_IF_ERROR(c->Concatenate(input, dense, &dense)); in __anonb04296470202()
91 c->set_output(output_idx++, dense); in __anonb04296470202()
130 ShapeHandle dense; in __anonb04296470302() local
132 c->MakeShapeFromPartialTensorShape(attrs.dense_shapes[i], &dense)); in __anonb04296470302()
133 c->set_output(output_idx++, dense); in __anonb04296470302()
|
| /external/llvm/test/tools/llvm-profdata/ |
| D | general.proftext | 3 # RUN: llvm-profdata merge -sparse=false %s -o %t.profdata.dense
15 # RUN: llvm-profdata show %t.profdata.dense --function "name with spaces" --counts | FileCheck %s -…
43 # RUN: llvm-profdata show %t.profdata.dense --function hex_hash | FileCheck %s -check-prefix=HEX-HA…
56 # RUN: llvm-profdata show %t.profdata.dense --function _ | FileCheck %s -check-prefix=SOMEFUNCS_DEN…
63 # RUN: llvm-profdata show %t.profdata.dense | FileCheck %s -check-prefix=SUMMARY
70 # RUN: llvm-profdata show --detailed-summary %t.profdata.dense | FileCheck %s -check-prefix=DETAILE…
|
| /external/swiftshader/third_party/llvm-7.0/llvm/test/tools/llvm-profdata/ |
| D | general.proftext | 3 # RUN: llvm-profdata merge -sparse=false %s -o %t.profdata.dense
15 # RUN: llvm-profdata show %t.profdata.dense --function "name with spaces" --counts | FileCheck %s -…
43 # RUN: llvm-profdata show %t.profdata.dense --function hex_hash | FileCheck %s -check-prefix=HEX-HA…
56 # RUN: llvm-profdata show %t.profdata.dense --function _ | FileCheck %s -check-prefix=SOMEFUNCS_DEN…
63 # RUN: llvm-profdata show %t.profdata.dense | FileCheck %s -check-prefix=SUMMARY
70 # RUN: llvm-profdata show --detailed-summary %t.profdata.dense | FileCheck %s -check-prefix=DETAILE…
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| D | input_data.cc | 104 void TensorDataSet::set_input_tensors(const Tensor& dense, in set_input_tensors() argument
108 if (dense.shape().dims() == 2) { in set_input_tensors()
109 dense_data_.reset(new DenseStorageType(dense.tensor<float, 2>())); in set_input_tensors()
118 original_dense_tensor_ = dense; in set_input_tensors()
|
| D | candidate_graph_runner.cc | 119 auto* dense = stats->mutable_classification()->mutable_dense_counts(); in GetLeftStats() local
121 dense->add_value()->set_float_value(counts(i)); in GetLeftStats()
129 auto* dense = stats->mutable_classification()->mutable_dense_counts(); in GetRightStats() local
131 dense->add_value()->set_float_value(counts(i)); in GetRightStats()
|
| /external/tensorflow/tensorflow/examples/tutorials/layers/ |
| D | cnn_mnist.py | 78 dense = tf.layers.dense(inputs=pool2_flat, units=1024, activation=tf.nn.relu)
82 inputs=dense, rate=0.4, training=mode == tf.estimator.ModeKeys.TRAIN)
87 logits = tf.layers.dense(inputs=dropout, units=10)
|
| /external/tensorflow/tensorflow/python/util/ |
| D | serialization_test.py | 37 dense = core.Dense(3)
38 dense(constant_op.constant([[4.]]))
40 dense, default=serialization.get_json_type))
|