| /external/tensorflow/tensorflow/core/kernels/ |
| sparse_to_dense_op.cc | 73 // sparse_values
74 const Tensor& sparse_values = c->input(2); variable
75 const int64 num_values = sparse_values.NumElements();
77 sparse_values.dims() == 0 ||
78 (sparse_values.dims() == 1 && num_values == num_elems),
79 errors::InvalidArgument("sparse_values has incorrect shape ",
80 sparse_values.shape().DebugString(),
110 if (TensorShapeUtils::IsScalar(sparse_values.shape())) {
114 sparse_values_b.vec<T>().setConstant(sparse_values.scalar<T>()());
116 sparse_values_b = sparse_values;
[all...] |
| sdca_ops_test.cc | 175 std::vector<NodeBuilder::NodeOut> sparse_values; local
186 sparse_values.reserve(num_sparse_feature_groups);
188 sparse_values.push_back(
216 .Input(sparse_values)
|
| example_parsing_ops.cc | 148 OpOutputList sparse_values; variable
152 OP_REQUIRES_OK(ctx, ctx->output_list("sparse_values", &sparse_values));
159 sparse_values.set(d, result.sparse_values[d]);
244 OpOutputList sparse_values; variable
248 OP_REQUIRES_OK(ctx, ctx->output_list("sparse_values", &sparse_values));
255 sparse_values.set(d, result.sparse_values[d])
[all...] |
| sparse_to_dense_op_test.cc | 59 // sparse_values
78 // sparse_values
97 // sparse_values
116 // sparse_values
138 // sparse_values
160 // sparse_values
182 // sparse_values
219 Tensor sparse_values(DT_FLOAT, TensorShape({N}));
233 {&sparse_indices, &output_shape, &sparse_values, &default_value}) {
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| sparse_to_dense_op_py_test.py | 31 sparse_values,
37 sparse_values,
105 r"sparse_values has incorrect shape \[2,1\], "
113 r"sparse_values has incorrect shape \[3\], should be \[\] or \[2\]"):
127 sparse_values=[-1.0, 1.0],
137 sparse_values=[-1.0, 1.0],
147 sparse_values=[-1.0, 1.0],
155 sparse_values=[-1.0, 1.0],
165 sparse_values=[-1.0, 1.0],
173 sparse_values=[-1.0, 1.0]
[all...] |
| /external/tensorflow/tensorflow/core/util/ |
| example_proto_fast_parsing.h | 68 std::vector<Tensor> sparse_values; member in struct:tensorflow::example::Result
|
| example_proto_fast_parsing.cc | [all...] |
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| input_data.cc | 106 const Tensor& sparse_values,
115 new SparseValuesStorageType(sparse_values.tensor<float, 1>()));
|
| input_data.h | 70 const Tensor& sparse_values,
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| embedding_ops.py | 367 sparse_values,
380 sparse_values: A 2-D `SparseTensor` containing the values to be embedded.
394 sparse_values.
397 TypeError: If sparse_values is not a SparseTensor.
408 if not isinstance(sparse_values, sparse_tensor.SparseTensor):
409 raise TypeError("sparse_values must be SparseTensor")
412 params + [sparse_values]) as scope:
416 if sparse_values.dtype == dtypes.string:
420 sparse_values, _ = sparse_ops.sparse_fill_empty_rows(
421 sparse_values, default_value
[all...] |
| feature_column.py | 587 sparse_values = string_ops.as_string(input_tensor.values)
589 sparse_values = input_tensor.values
595 sparse_values, self.bucket_size, key)
603 sparse_values, self.bucket_size, name="lookup")
[all...] |
| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/ |
| sdca_optimizer.py | 114 sparse_values = array_ops.gather_nd(dense_tensor, sparse_indices)
124 array_ops.reshape(math_ops.to_float(sparse_values), [-1]))
|
| /external/tensorflow/tensorflow/contrib/tensor_forest/python/ |
| tensor_forest.py | 602 sparse_values = []
606 sparse_values = sparse_features.values
616 sparse_values,
633 sparse_values,
662 sparse_values = []
666 sparse_values = sparse_features.values
675 sparse_values,
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/kernels/ |
| quantile_ops.cc | 52 const char* const kSparseValuesName = "sparse_values";
414 const auto sparse_values =
429 stream.PushEntry(sparse_values(j), example_weights(example_id));
[all...] |
| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/ |
| tree_utils.h | 162 const Tensor& sparse_values);
|
| tree_utils.cc | 556 const Tensor& sparse_values) {
559 const auto values = sparse_values.vec<float>();
|
| /external/tensorflow/tensorflow/python/ops/ |
| parsing_ops.py | 715 (sparse_indices, sparse_values, sparse_shapes, dense_values) = outputs
719 in zip(sparse_indices, sparse_values, sparse_shapes)]
[all...] |
| sparse_ops.py | 741 sparse_values,
751 dense[i] = (i == sparse_indices ? sparse_values : default_value)
754 dense[sparse_indices[i]] = sparse_values[i]
757 dense[sparse_indices[i][0], ..., sparse_indices[i][d-1]] = sparse_values[i]
760 All other values in `dense` are set to `default_value`. If `sparse_values`
769 `sparse_indices[i]` contains the complete index where `sparse_values[i]`
773 sparse_values: A 0-D or 1-D `Tensor`. Values corresponding to each row of
775 default_value: A 0-D `Tensor` of the same type as `sparse_values`. Value
783 `sparse_values`.
788 sparse_values,
[all...] |
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| factorization_ops_test.py | 121 sparse_values = [666., 777., 888.]
148 values=sparse_values,
[all...] |
| /external/tensorflow/tensorflow/python/feature_column/ |
| feature_column.py | [all...] |
| /external/tensorflow/tensorflow/go/op/ |
| wrappers.go | [all...] |
