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 | #include "tensorflow/core/framework/common_shape_fns.h" |
16 | #include "tensorflow/core/framework/op.h" |
17 | #include "tensorflow/core/framework/shape_inference.h" |
18 | |
19 | namespace tensorflow { |
20 | |
21 | using shape_inference::DimensionHandle; |
22 | using shape_inference::InferenceContext; |
23 | using shape_inference::ShapeHandle; |
24 | |
25 | Status RaggedRangeShapeFn(InferenceContext* c); |
26 | |
27 | //============================================================================== |
28 | // Registered Ops |
29 | //============================================================================== |
30 | |
31 | REGISTER_OP("RaggedRange" ) |
32 | .Input("starts: T" ) |
33 | .Input("limits: T" ) |
34 | .Input("deltas: T" ) |
35 | .Output("rt_nested_splits: Tsplits" ) |
36 | .Output("rt_dense_values: T" ) |
37 | .Attr("T: {bfloat16, float, double, int32, int64} = DT_INT32" ) |
38 | .Attr("Tsplits: {int32, int64} = DT_INT64" ) |
39 | .SetShapeFn(RaggedRangeShapeFn); |
40 | |
41 | //============================================================================== |
42 | // Shape Functions |
43 | //============================================================================== |
44 | |
45 | Status RaggedRangeShapeFn(InferenceContext* c) { |
46 | // Check that all inputs (starts, limits, and deltas) have rank 0 or 1. |
47 | ShapeHandle starts = c->input(0); |
48 | ShapeHandle limits = c->input(1); |
49 | ShapeHandle deltas = c->input(2); |
50 | TF_RETURN_IF_ERROR(c->WithRankAtMost(starts, 1, &starts)); |
51 | TF_RETURN_IF_ERROR(c->WithRankAtMost(limits, 1, &limits)); |
52 | TF_RETURN_IF_ERROR(c->WithRankAtMost(deltas, 1, &deltas)); |
53 | |
54 | // For the inputs with rank 1, make sure shapes match. |
55 | DimensionHandle dim = c->UnknownDim(); |
56 | if (c->Rank(starts) == 1) { |
57 | TF_RETURN_IF_ERROR(c->Merge(c->Dim(starts, 0), dim, &dim)); |
58 | } |
59 | if (c->Rank(limits) == 1) { |
60 | TF_RETURN_IF_ERROR(c->Merge(c->Dim(limits, 0), dim, &dim)); |
61 | } |
62 | if (c->Rank(deltas) == 1) { |
63 | TF_RETURN_IF_ERROR(c->Merge(c->Dim(deltas, 0), dim, &dim)); |
64 | } |
65 | |
66 | // If any input shape is known, then calculate `rt_nested_splits` shape. |
67 | int64_t rt_nested_splits_dim = InferenceContext::kUnknownDim; |
68 | if (c->ValueKnown(dim)) { |
69 | rt_nested_splits_dim = c->Value(dim) + 1; |
70 | } else if (c->Rank(starts) == 0 && c->Rank(limits) == 0 && |
71 | c->Rank(deltas) == 0) { |
72 | rt_nested_splits_dim = 2; |
73 | } |
74 | c->set_output(0, c->Vector(rt_nested_splits_dim)); |
75 | |
76 | // `rt_dense_values` is rank 1, but size can't be calculated statically. |
77 | c->set_output(1, c->UnknownShapeOfRank(1)); |
78 | return OkStatus(); |
79 | } |
80 | |
81 | } // namespace tensorflow |
82 | |