1 /* Copyright 2019 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 #include <string.h>
18
19 #include "tensorflow/lite/c/common.h"
20 #include "tensorflow/lite/core/subgraph.h"
21 #include "tensorflow/lite/experimental/resource/resource_variable.h"
22 #include "tensorflow/lite/kernels/internal/tensor.h"
23 #include "tensorflow/lite/kernels/kernel_util.h"
24
25 namespace tflite {
26 namespace ops {
27 namespace builtin {
28 namespace read_variable {
29
30 constexpr int kInputVariableId = 0;
31 constexpr int kOutputValue = 0;
32
Prepare(TfLiteContext * context,TfLiteNode * node)33 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
34 TF_LITE_ENSURE_EQ(context, node->inputs->size, 1);
35 TF_LITE_ENSURE_EQ(context, node->outputs->size, 1);
36
37 const TfLiteTensor* input_resource_id_tensor;
38 TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputVariableId,
39 &input_resource_id_tensor));
40 TF_LITE_ENSURE(context, (input_resource_id_tensor->type == kTfLiteResource ||
41 input_resource_id_tensor->type == kTfLiteInt32));
42 TF_LITE_ENSURE_EQ(context, NumElements(input_resource_id_tensor), 1);
43
44 TfLiteTensor* output;
45 TF_LITE_ENSURE_OK(context,
46 GetOutputSafe(context, node, kOutputValue, &output));
47
48 if (output->dims->size == 0) {
49 // Currently there is no good way to differentiate between scalar and
50 // unranked tensor, so we set the tensor's allocation type to dynamic in
51 // both cases.
52 SetTensorToDynamic(output);
53 }
54
55 return kTfLiteOk;
56 }
57
Eval(TfLiteContext * context,TfLiteNode * node)58 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
59 Subgraph* subgraph = reinterpret_cast<Subgraph*>(context->impl_);
60
61 const TfLiteTensor* input_resource_id_tensor;
62 TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputVariableId,
63 &input_resource_id_tensor));
64 int resource_id = input_resource_id_tensor->data.i32[0];
65 auto& resources = subgraph->resources();
66 auto* variable = resource::GetResourceVariable(&resources, resource_id);
67 TF_LITE_ENSURE(context, variable != nullptr);
68
69 TfLiteTensor* variable_tensor = variable->GetTensor();
70 TfLiteTensor* output;
71 TF_LITE_ENSURE_OK(context,
72 GetOutputSafe(context, node, kOutputValue, &output));
73
74 TF_LITE_ENSURE_TYPES_EQ(context, variable_tensor->type, output->type);
75 // Only resize the output if the op produces dynamic output.
76 if (IsDynamicTensor(output)) {
77 TF_LITE_ENSURE_OK(context, context->ResizeTensor(
78 context, output,
79 TfLiteIntArrayCopy(variable_tensor->dims)));
80 }
81 memcpy(output->data.raw, variable_tensor->data.raw, output->bytes);
82
83 return kTfLiteOk;
84 }
85
86 } // namespace read_variable
87
Register_READ_VARIABLE()88 TfLiteRegistration* Register_READ_VARIABLE() {
89 static TfLiteRegistration r = {nullptr, nullptr, read_variable::Prepare,
90 read_variable::Eval};
91 return &r;
92 }
93
94 } // namespace builtin
95 } // namespace ops
96 } // namespace tflite
97