| /external/tensorflow/tensorflow/contrib/lite/toco/graph_transformations/ |
| resolve_reorder_axes.cc | 34 Array* input_array, Array* output_array) {
36 CHECK(!output_array->buffer);
39 reordered_data.resize(RequiredBufferSizeForShape(output_array->shape()));
42 Shape output_shape = output_array->shape();
50 input_array->copy_shape(output_array->shape());
62 auto& output_array = model->GetArray(output_array_name); local
67 if (!output_array.has_shape()) {
74 &input_array, &output_array);
78 &input_array, &output_array);
83 input_array.copy_shape(output_array.shape())
[all...] |
| resolve_constant_shape_or_rank.cc | 31 auto& output_array = model->GetArray(op->outputs[0]); local
32 if (output_array.data_type == ArrayDataType::kNone) {
43 if (!output_array.has_shape()) {
49 CHECK(!output_array.buffer);
50 auto& output_buffer = output_array.GetMutableBuffer<ArrayDataType::kInt32>();
59 output_array.mutable_shape()->ReplaceDims(
|
| resolve_constant_strided_slice.cc | 62 Array* output_array) {
69 CHECK(output_array->data_type == Type);
82 output_array->GetMutableBuffer<Type>().data;
83 output_data.resize(RequiredBufferSizeForShape(output_array->shape()));
138 auto& output_array = model->GetArray(op->outputs[0]); local
139 if (output_array.data_type == ArrayDataType::kNone) {
144 if (!output_array.has_shape()) {
165 CHECK(!output_array.buffer);
166 switch (output_array.data_type) {
168 StridedSlice<ArrayDataType::kFloat>(*op, input_array, &output_array);
[all...] |
| resolve_constant_stack.cc | 28 auto& output_array = model->GetArray(op.outputs[0]); local
29 CHECK(output_array.data_type == Type);
33 output_array.GetMutableBuffer<Type>().data;
34 output_data.resize(RequiredBufferSizeForShape(output_array.shape()));
62 auto& output_array = model->GetArray(op->outputs[0]); local
63 if (output_array.data_type == ArrayDataType::kNone) {
68 if (!output_array.has_shape()) {
80 CHECK(!output_array.buffer);
81 switch (output_array.data_type) {
|
| remove_trivial_slice.cc | 37 const auto& output_array = model.GetArray(op.outputs[0]); local
38 if (input_array.has_shape() && output_array.has_shape()) {
39 if (input_array.shape() == output_array.shape()) {
|
| resolve_constant_fill.cc | 27 auto& output_array = model->GetArray(op->outputs[0]); local
30 CHECK(output_array.data_type == Type);
34 output_array.GetMutableBuffer<Type>().data;
35 data.resize(RequiredBufferSizeForShape(output_array.shape()));
55 auto& output_array = model->GetArray(op->outputs[0]); local
56 if (output_array.data_type == ArrayDataType::kNone) {
61 if (!output_array.has_shape()) {
77 switch (output_array.data_type) {
|
| resolve_multiply_by_zero.cc | 61 auto& output_array = model->GetArray(output_array_name); local
64 if (!output_array.has_shape()) {
92 CHECK(constant_input_array.data_type == output_array.data_type);
93 switch (output_array.data_type) {
101 FillArrayWithZeros<ArrayDataType::kFloat>(&output_array);
110 FillArrayWithZeros<ArrayDataType::kUint8>(&output_array);
119 FillArrayWithZeros<ArrayDataType::kInt32>(&output_array);
128 FillArrayWithZeros<ArrayDataType::kInt64>(&output_array);
|
| remove_trivial_quantized_activation_func.cc | 36 const auto& output_array = model->GetArray(op->outputs[0]); local
37 if (!output_array.quantization_params) {
40 if (output_array.data_type != ArrayDataType::kUint8) {
43 const auto& quantization_params = output_array.GetQuantizationParams();
|
| remove_trivial_reshape.cc | 38 const auto& output_array = model.GetArray(op.outputs[0]); local
39 if (input_array.has_shape() && output_array.has_shape()) {
41 ShapesAgreeUpToExtending(input_array.shape(), output_array.shape())) {
49 if (input_array.shape().dims() == output_array.shape().dims()) {
|
| resolve_constant_fake_quant.cc | 48 auto& output_array = model->GetArray(fakequant_op->outputs[0]); local
50 output_array.data_type = ArrayDataType::kFloat;
51 CHECK(!output_array.buffer);
53 output_array.GetOrCreateMinMax() = *fakequant_op->minmax;
54 auto& output_buffer = output_array.GetMutableBuffer<ArrayDataType::kFloat>();
|
| resolve_constant_transpose.cc | 30 const std::vector<int>& perm, Array* output_array) {
35 const Shape& output_shape = output_array->shape();
37 output_array->GetMutableBuffer<Type>().data;
114 auto& output_array = model->GetArray(op->outputs[0]); local
115 if (output_array.data_type == ArrayDataType::kNone) {
119 if (!output_array.has_shape()) {
132 output_array.GetOrCreateMinMax() = input_array.GetMinMax();
143 CHECK(!output_array.buffer);
144 switch (output_array.data_type) {
147 &output_array);
[all...] |
| drop_fake_quant.cc | 40 const auto& output_array = model->GetArray(fakequant_op->outputs[0]); local
41 if (!output_array.minmax) {
|
| hardcode_min_max.cc | 50 auto& output_array = model->GetArray(op->outputs[0]); local
51 if (output_array.minmax) {
59 CHECK(!output_array.minmax);
60 auto& output_minmax = output_array.GetOrCreateMinMax();
130 auto& output_array = model->GetArray(op->outputs[0]); local
131 if (output_array.minmax) {
139 CHECK(!output_array.minmax);
140 auto& output_minmax = output_array.GetOrCreateMinMax();
147 auto& output_array = model->GetArray(op->outputs[0]); local
148 if (output_array.minmax)
166 auto& output_array = model->GetArray(op->outputs[0]); local
[all...] |
| convert_trivial_transpose_to_reshape.cc | 32 const auto& output_array = model->GetArray(transpose_op->outputs[0]); local
33 if (!output_array.has_shape()) {
40 std::vector<int> const& dims = output_array.shape().dims();
|
| propagate_fixed_sizes.cc | 66 Array* output_array) {
74 std::vector<int>* dims_out = output_array->mutable_shape()->mutable_dims();
102 CHECK(output_array->has_shape());
164 auto& output_array = model->GetArray(op->outputs[0]); local
170 output_array.mutable_shape(),
172 CHECK_EQ(output_array.shape().dimensions_count(), 4);
176 const auto& output_shape = output_array.shape();
280 auto& output_array = model->GetArray(op->outputs[0]); local
281 if (output_array.has_shape()) {
301 *(output_array.mutable_shape()->mutable_dims()) = dims
331 auto& output_array = model->GetArray(op->outputs[0]); local
337 auto& output_array = model->GetArray(op->outputs[0]); local
406 auto& output_array = model->GetArray(output_name); local
423 auto& output_array = model->GetArray(output_name); local
446 auto& output_array = model->GetArray(op->outputs[0]); local
468 auto& output_array = model->GetArray(op->outputs[0]); local
524 auto& output_array = model->GetArray(op->outputs[0]); local
564 auto& output_array = model->GetArray(op->outputs[0]); local
638 auto& output_array = model->GetArray(op->outputs[0]); local
955 auto& output_array = model->GetArray(op->outputs[0]); local
1034 auto& output_array = model->GetArray(op->outputs[0]); local
1051 auto& output_array = model->GetArray(op->outputs[0]); local
1072 auto& output_array = model->GetArray(op->outputs[0]); local
1093 auto& output_array = model->GetArray(op->outputs[0]); local
1134 auto& output_array = model->GetArray(op->outputs[0]); local
[all...] |
| resolve_constant_range.cc | 55 auto& output_array = model->GetArray(op->outputs[0]); local
56 if (output_array.data_type == ArrayDataType::kNone) {
79 auto& buffer = output_array.GetMutableBuffer<ArrayDataType::kInt32>();
85 CHECK_EQ(buffer.data.size(), output_array.shape().dims()[0]);
|
| remove_unused_op.cc | 58 for (const string& output_array : model->flags.output_arrays()) {
59 if (output == output_array) {
|
| resolve_constant_binary.cc | 73 auto& output_array = model->GetArray(output_name); local
76 CHECK(output_array.data_type == OutputDataType);
83 CHECK(!output_array.buffer);
90 const Shape& output_shape = output_array.shape();
91 auto& output_data = output_array.GetMutableBuffer<OutputDataType>().data;
218 auto& output_array = model->GetArray(binary_op->outputs[0]); local
220 if (!output_array.has_shape()) {
|
| dequantize.cc | 136 for (const string& output_array : model->flags.output_arrays()) {
137 if (array_name == output_array) {
202 auto& output_array = model->GetArray(op->outputs[0]); local
203 output_array.data_type = ArrayDataType::kFloat;
204 output_array.quantization_params = nullptr;
|
| /external/libjpeg-turbo/ |
| jutils.c | 95 JSAMPARRAY output_array, int dest_row,
99 * to output_array[dest_row++]; these areas may overlap for duplication.
108 output_array += dest_row;
112 outptr = *output_array++;
|
| /external/tensorflow/tensorflow/contrib/lite/toco/ |
| tooling_util.cc | 647 for (const string& output_array : model_flags.output_arrays()) {
648 QCHECK_NE(input_array.name(), output_array)
649 << "The array " << output_array
690 for (const string& output_array : model_flags.output_arrays()) {
691 QCHECK(IsAsciiPrintable(output_array))
693 << output_array << ". Pass --allow_nonascii_arrays to allow that. "
695 << DumpAscii(output_array);
707 for (const string& output_array : model.flags.output_arrays()) {
708 CHECK(model.HasArray(output_array))
709 << "Output array not found: " << output_array;
1331 auto& output_array = model->GetArray(output); local
1485 const auto& output_array = model.GetArray(op->outputs[0]); local
1506 const auto& output_array = model.GetArray(op->outputs[0]); local
1514 const auto& output_array = model.GetArray(op->outputs[0]); local
1527 const auto& output_array = model.GetArray(op->outputs[0]); local
1540 const auto& output_array = model.GetArray(op->outputs[0]); local
1551 const auto& output_array = model.GetArray(op->outputs[0]); local
1561 const auto& output_array = model.GetArray(op->outputs[0]); local
1573 const auto& output_array = model.GetArray(op->outputs[0]); local
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| requantize.cc | 68 auto output_array = output->flat<T2>();
73 output_array.data());
|
| quantize_down_and_shrink_range.cc | 75 auto output_array = output->flat<T2>();
79 output_array.data());
|
| /external/tensorflow/tensorflow/compiler/xla/service/llvm_ir/ |
| ops.cc | 41 ElementGenerator update_array_generator, const IrArray& output_array,
44 const Shape& output_shape = output_array.GetShape();
73 output_array.EmitWriteArrayElement(output_index, update_data, ir_builder);
88 const IrArray& output_array, tensorflow::StringPiece name,
96 Shape output_shape = output_array.GetShape();
108 output_array, /*launch_dimensions=*/nullptr, name, ir_builder);
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| reduce_join_op_test.py | 81 output_array = _input_array(num_dims).reshape([-1])
82 self.assertAllEqualUnicode(truth, output_array)
122 output_array = output.eval()
124 self.assertAllEqualUnicode(truth, output_array)
164 output_array = output.eval()
169 self.assertAllEqualUnicode(truth_squeezed_array, output_array)
264 output_array = reduced.eval(feed_dict={placeholder.name: input_array})
265 self.assertAllEqualUnicode(truth, output_array)
|
