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 | |
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 | |
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 | |
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 | |