| /external/tensorflow/tensorflow/core/kernels/ |
| D | reshape_util.cc | 101 const int64 dense_size = input_shape.num_elements(); in ReshapeSparseTensor() local
134 const int64 missing = dense_size / product; in ReshapeSparseTensor()
136 context, product * missing == dense_size, in ReshapeSparseTensor()
138 "Input to reshape is a SparseTensor with ", dense_size, in ReshapeSparseTensor()
146 context, output_shape.num_elements() == dense_size, in ReshapeSparseTensor()
147 errors::InvalidArgument("Input to reshape is a tensor with ", dense_size, in ReshapeSparseTensor()
|
| /external/tensorflow/tensorflow/lite/kernels/parse_example/ |
| D | parse_example_test.cc | 162 const char* text_def, int dense_size = 2) { in ParseExampleOpModel() argument
174 if (dense_size > 0) { in ParseExampleOpModel()
176 TensorData(dense_types[0], {dense_size}), dense_defaults); in ParseExampleOpModel()
190 dense_outputs_.push_back(AddOutput({dense_types[i], {dense_size}})); in ParseExampleOpModel()
|
| D | parse_example.cc | 655 int dense_size = 0; member
713 data->dense_size = nodedef.attr().at("Ndense").i(); in PrepareParseExample()
716 data->dense_size = nodedef.attr().at("Tdense").list().type_size(); in PrepareParseExample()
743 data->dense_size = num_dense; in PrepareParseExample()
747 data->dense_size = GetTensorShape(dense_key_tensor).FlatSize(); in PrepareParseExample()
751 data->config.dense.reserve(data->dense_size); in PrepareParseExample()
753 data->dense_shapes.reserve(data->dense_size); in PrepareParseExample()
758 for (int i = 0; i < data->dense_size; i++) { in PrepareParseExample()
837 for (int i = 0; i < data->dense_size; i++) { in EvalParseExample()
843 ? kSparseKeysTensor + data->sparse_size + data->dense_size + i in EvalParseExample()
[all …]
|
| /external/tensorflow/tensorflow/lite/tools/optimize/sparsity/ |
| D | format_converter.cc | 232 dim_metadata_[2 * i] = {sparsity.dim_metadata[i].dense_size}; in FormatConverter()
249 block_size_[block_dim] = sparsity.dim_metadata[orig_dim].dense_size; in FormatConverter()
250 blocked_shape_[i] = shape[i] / sparsity.dim_metadata[orig_dim].dense_size; in FormatConverter()
|
| /external/tensorflow/tensorflow/lite/ |
| D | model_test.cc | 442 ASSERT_EQ(t1->sparsity->dim_metadata[0].dense_size, 2); in TEST()
447 ASSERT_EQ(t1->sparsity->dim_metadata[1].dense_size, 0); in TEST()
465 ASSERT_EQ(t1->sparsity->dim_metadata[2].dense_size, 2); in TEST()
470 ASSERT_EQ(t1->sparsity->dim_metadata[3].dense_size, 2); in TEST()
|
| D | interpreter_builder.cc | 476 tgt_metadata->dense_size = src_metadata->dense_size(); in ParseSparsity()
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/ir/ |
| D | tfl_structs.td | 26 StructFieldAttr<"dense_size", I32Attr>,
|
| /external/tensorflow/tensorflow/lite/tools/ |
| D | verifier.cc | 244 if (dim_metadata->dense_size() != dim_sizes[original_dim]) { in VerifyAndCountElements()
249 num_elements *= dim_metadata->dense_size(); in VerifyAndCountElements()
363 sparsity->dim_metadata()->Get(i + original_rank)->dense_size(); in VerifyAndCountSparseElements()
|
| D | verifier_test.cc | 710 tensor->sparsity->dim_metadata[0]->dense_size = 2; in TEST()
719 tensor->sparsity->dim_metadata[2]->dense_size = 2; in TEST()
721 tensor->sparsity->dim_metadata[3]->dense_size = 2; in TEST()
|
| /external/tensorflow/tensorflow/lite/c/ |
| D | common_test.cc | 132 t.sparsity->dim_metadata[0].dense_size = 4; in TEST()
|
| D | common.h | 355 int dense_size; member
|
| /external/tensorflow/tensorflow/lite/kernels/internal/optimized/sparse_ops/ |
| D | fully_connected.h | 48 const int w0_size = sparsity.dim_metadata[0].dense_size; in FullyConnectedSparseWeight()
|
| /external/tensorflow/tensorflow/lite/schema/ |
| D | schema_v3a.fbs | 143 // - If format is DimensionType.DENSE then we use the dense_size field to
153 dense_size:int;
|
| D | schema.fbs | 147 // - If format is DimensionType.DENSE then we use the dense_size field to
157 dense_size:int;
|
| D | schema_generated.h | 3448 int32_t dense_size;
3453 dense_size(0) {
3470 int32_t dense_size() const {
3552 void add_dense_size(int32_t dense_size) {
3553 fbb_.AddElement<int32_t>(DimensionMetadata::VT_DENSE_SIZE, dense_size, 0);
3582 int32_t dense_size = 0,
3590 builder_.add_dense_size(dense_size);
11633 { auto _e = dense_size(); _o->dense_size = _e; }
11649 auto _dense_size = _o->dense_size;
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/ |
| D | test_schema.fbs | 140 // - If format is DimensionType.DENSE then we use the dense_size field to
150 dense_size:int;
|
| /external/tensorflow/tensorflow/lite/python/interpreter_wrapper/ |
| D | interpreter_wrapper.cc | 122 PyLong_FromSize_t(param.dim_metadata[i].dense_size)); in PyDictFromSparsityParam()
|
| /external/tensorflow/tensorflow/lite/delegates/xnnpack/ |
| D | xnnpack_delegate.cc | 3181 const size_t dense_size = context->tensors[t].bytes / sizeof(float); in PrepareOpsToDelegate() local
3186 static_cast<const float*>(input_tensor.data.data), dense_size, in PrepareOpsToDelegate()
3191 const size_t dense_size = in PrepareOpsToDelegate() local
3199 dense_size, unpacked_fp16_data, context); in PrepareOpsToDelegate()
|
| /external/tensorflow/tensorflow/lite/kernels/ |
| D | fully_connected.cc | 878 sparsity.dim_metadata[2].dense_size == 4) { in EvalFloat()
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/ |
| D | flatbuffer_export.cc | 1859 dim_metadata.dense_size().getInt()); in BuildSparsityParameters()
|