1 | /* Copyright 2018 The TensorFlow Authors. All Rights Reserved. |
2 | |
3 | Licensed under the Apache License, Version 2.0 (the "License"); |
4 | you may not use this file except in compliance with the License. |
5 | You may obtain a copy of the License at |
6 | |
7 | http://www.apache.org/licenses/LICENSE-2.0 |
8 | |
9 | Unless required by applicable law or agreed to in writing, software |
10 | distributed under the License is distributed on an "AS IS" BASIS, |
11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
12 | See the License for the specific language governing permissions and |
13 | limitations under the License. |
14 | ==============================================================================*/ |
15 | |
16 | #include <stdint.h> |
17 | |
18 | #include "tensorflow/lite/c/builtin_op_data.h" |
19 | #include "tensorflow/lite/c/common.h" |
20 | #include "tensorflow/lite/kernels/internal/reference/reference_ops.h" |
21 | #include "tensorflow/lite/kernels/internal/tensor.h" |
22 | #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
23 | #include "tensorflow/lite/kernels/internal/types.h" |
24 | #include "tensorflow/lite/kernels/kernel_util.h" |
25 | |
26 | namespace tflite { |
27 | namespace ops { |
28 | namespace builtin { |
29 | namespace pack { |
30 | namespace { |
31 | |
32 | constexpr int kOutputTensor = 0; |
33 | |
34 | TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
35 | TfLitePackParams* data = |
36 | reinterpret_cast<TfLitePackParams*>(node->builtin_data); |
37 | |
38 | TF_LITE_ENSURE_EQ(context, NumInputs(node), data->values_count); |
39 | TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
40 | |
41 | const TfLiteTensor* input0; |
42 | TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, 0, &input0)); |
43 | const int dimension_size = NumDimensions(input0) + 1; |
44 | if (data->axis < 0) { |
45 | data->axis += dimension_size; |
46 | } |
47 | TF_LITE_ENSURE(context, NumDimensions(input0) >= data->axis); |
48 | TF_LITE_ENSURE(context, data->axis >= 0); |
49 | |
50 | if (input0->type != kTfLiteInt32 && input0->type != kTfLiteFloat32 && |
51 | input0->type != kTfLiteUInt8 && input0->type != kTfLiteInt8 && |
52 | input0->type != kTfLiteInt16 && input0->type != kTfLiteInt64) { |
53 | TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by pack." , |
54 | TfLiteTypeGetName(input0->type)); |
55 | return kTfLiteError; |
56 | } |
57 | // Make sure all inputs have the same shape and type. |
58 | for (int i = 1; i < data->values_count; ++i) { |
59 | const TfLiteTensor* input; |
60 | TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, i, &input)); |
61 | TF_LITE_ENSURE(context, HaveSameShapes(input0, input)); |
62 | TF_LITE_ENSURE_TYPES_EQ(context, input0->type, input->type); |
63 | } |
64 | |
65 | // Resize output. rank R will become rank R + 1 |
66 | const TfLiteIntArray* input_shape = input0->dims; |
67 | TfLiteIntArray* output_shape = TfLiteIntArrayCreate(dimension_size); |
68 | int i = 0; |
69 | for (int index = 0; index < dimension_size; ++index) { |
70 | if (index == data->axis) { |
71 | output_shape->data[index] = data->values_count; |
72 | } else { |
73 | output_shape->data[index] = input_shape->data[i++]; |
74 | } |
75 | } |
76 | |
77 | TfLiteTensor* output; |
78 | TF_LITE_ENSURE_OK(context, |
79 | GetOutputSafe(context, node, kOutputTensor, &output)); |
80 | TF_LITE_ENSURE_TYPES_EQ(context, output->type, input0->type); |
81 | |
82 | // Guarantee input/output quantization params match as we do not support |
83 | // packing quantized tensors. |
84 | for (int i = 0; i < data->values_count; i++) { |
85 | const TfLiteTensor* input; |
86 | TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, i, &input)); |
87 | TF_LITE_ENSURE_EQ(context, input->params.zero_point, |
88 | output->params.zero_point); |
89 | TF_LITE_ENSURE_EQ(context, input->params.scale, output->params.scale); |
90 | } |
91 | |
92 | return context->ResizeTensor(context, output, output_shape); |
93 | } |
94 | |
95 | template <typename T> |
96 | TfLiteStatus PackImpl(TfLiteContext* context, TfLiteNode* node, |
97 | TfLiteTensor* output, int values_count, int axis) { |
98 | TF_LITE_ENSURE(context, axis >= 0); |
99 | |
100 | VectorOfTensors<T> all_inputs(*context, *node->inputs); |
101 | tflite::PackParams op_params; |
102 | op_params.axis = axis; |
103 | op_params.inputs_count = values_count; |
104 | |
105 | reference_ops::Pack<T>(op_params, all_inputs.shapes(), all_inputs.data(), |
106 | GetTensorShape(output), GetTensorData<T>(output)); |
107 | return kTfLiteOk; |
108 | } |
109 | |
110 | TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
111 | const TfLitePackParams* data = |
112 | reinterpret_cast<TfLitePackParams*>(node->builtin_data); |
113 | |
114 | TfLiteTensor* output; |
115 | TF_LITE_ENSURE_OK(context, |
116 | GetOutputSafe(context, node, kOutputTensor, &output)); |
117 | switch (output->type) { |
118 | case kTfLiteFloat32: { |
119 | return PackImpl<float>(context, node, output, data->values_count, |
120 | data->axis); |
121 | } |
122 | case kTfLiteUInt8: { |
123 | return PackImpl<uint8_t>(context, node, output, data->values_count, |
124 | data->axis); |
125 | } |
126 | case kTfLiteInt8: { |
127 | return PackImpl<int8_t>(context, node, output, data->values_count, |
128 | data->axis); |
129 | } |
130 | case kTfLiteInt16: { |
131 | return PackImpl<int16_t>(context, node, output, data->values_count, |
132 | data->axis); |
133 | } |
134 | case kTfLiteInt32: { |
135 | return PackImpl<int32_t>(context, node, output, data->values_count, |
136 | data->axis); |
137 | } |
138 | case kTfLiteInt64: { |
139 | return PackImpl<int64_t>(context, node, output, data->values_count, |
140 | data->axis); |
141 | } |
142 | default: { |
143 | TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by pack." , |
144 | TfLiteTypeGetName(output->type)); |
145 | return kTfLiteError; |
146 | } |
147 | } |
148 | } |
149 | |
150 | } // namespace |
151 | } // namespace pack |
152 | |
153 | TfLiteRegistration* Register_PACK() { |
154 | static TfLiteRegistration r = {nullptr, nullptr, pack::Prepare, pack::Eval}; |
155 | return &r; |
156 | } |
157 | |
158 | } // namespace builtin |
159 | } // namespace ops |
160 | } // namespace tflite |
161 | |