1 | /* Copyright 2017 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 | #include <stdint.h> |
16 | |
17 | #include "tensorflow/lite/c/common.h" |
18 | #include "tensorflow/lite/kernels/internal/tensor.h" |
19 | #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
20 | #include "tensorflow/lite/kernels/kernel_util.h" |
21 | |
22 | namespace tflite { |
23 | namespace ops { |
24 | namespace builtin { |
25 | namespace rank { |
26 | |
27 | constexpr int kInputTensor = 0; |
28 | constexpr int kOutputTensor = 0; |
29 | |
30 | TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
31 | TF_LITE_ENSURE_EQ(context, NumInputs(node), 1); |
32 | TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
33 | |
34 | const TfLiteTensor* input; |
35 | TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input)); |
36 | TfLiteTensor* output; |
37 | TF_LITE_ENSURE_OK(context, |
38 | GetOutputSafe(context, node, kOutputTensor, &output)); |
39 | output->type = kTfLiteInt32; |
40 | |
41 | // By design, the input shape is always known at the time of Prepare, even |
42 | // if the preceding op that generates |input| is dynamic. Thus, we can |
43 | // always compute the rank immediately, without waiting for Eval. |
44 | SetTensorToPersistentRo(output); |
45 | |
46 | // Rank produces a 0-D int32 Tensor representing the rank of input. |
47 | TfLiteIntArray* output_size = TfLiteIntArrayCreate(0); |
48 | TF_LITE_ENSURE_STATUS(context->ResizeTensor(context, output, output_size)); |
49 | |
50 | TF_LITE_ENSURE_EQ(context, NumDimensions(output), 0); |
51 | |
52 | // Immediately propagate the known rank to the output tensor. This allows |
53 | // downstream ops that rely on the value to use it during prepare. |
54 | if (output->type == kTfLiteInt32) { |
55 | int32_t* output_data = GetTensorData<int32_t>(output); |
56 | *output_data = NumDimensions(input); |
57 | } else { |
58 | return kTfLiteError; |
59 | } |
60 | |
61 | return kTfLiteOk; |
62 | } |
63 | |
64 | TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
65 | return kTfLiteOk; |
66 | } |
67 | |
68 | } // namespace rank |
69 | |
70 | TfLiteRegistration* Register_RANK() { |
71 | static TfLiteRegistration r = {nullptr, nullptr, rank::Prepare, rank::Eval}; |
72 | return &r; |
73 | } |
74 | |
75 | } // namespace builtin |
76 | } // namespace ops |
77 | } // namespace tflite |
78 | |