1 | /* Copyright 2020 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 "tensorflow/core/framework/common_shape_fns.h" |
17 | #include "tensorflow/core/framework/op.h" |
18 | #include "tensorflow/core/framework/shape_inference.h" |
19 | |
20 | namespace tensorflow { |
21 | |
22 | using shape_inference::InferenceContext; |
23 | using shape_inference::ShapeHandle; |
24 | |
25 | Status DenseCountSparseOutputShapeFn(InferenceContext *c) { |
26 | auto values = c->input(0); |
27 | auto weights = c->input(1); |
28 | ShapeHandle output; |
29 | auto num_weights = c->NumElements(weights); |
30 | if (c->ValueKnown(num_weights) && c->Value(num_weights) == 0) { |
31 | output = values; |
32 | } else { |
33 | TF_RETURN_IF_ERROR(c->Merge(weights, values, &output)); |
34 | } |
35 | auto rank = c->Rank(output); |
36 | auto nvals = c->UnknownDim(); |
37 | c->set_output(0, c->Matrix(nvals, rank)); // out.indices |
38 | c->set_output(1, c->Vector(nvals)); // out.values |
39 | c->set_output(2, c->Vector(rank)); // out.dense_shape |
40 | return OkStatus(); |
41 | } |
42 | |
43 | Status SparseCountSparseOutputShapeFn(InferenceContext *c) { |
44 | ShapeHandle unused; |
45 | TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 2, &unused)); |
46 | auto rank = c->Dim(c->input(0), 1); |
47 | auto nvals = c->UnknownDim(); |
48 | c->set_output(0, c->Matrix(nvals, rank)); // out.indices |
49 | c->set_output(1, c->Vector(nvals)); // out.values |
50 | c->set_output(2, c->Vector(rank)); // out.dense_shape |
51 | return OkStatus(); |
52 | } |
53 | |
54 | Status RaggedCountSparseOutputShapeFn(InferenceContext *c) { |
55 | int32_t rank = c->Rank(c->input(1)); |
56 | if (rank != c->kUnknownRank) { |
57 | ++rank; // Add the ragged dimension |
58 | } |
59 | auto nvals = c->UnknownDim(); |
60 | c->set_output(0, c->Matrix(nvals, rank)); // out.indices |
61 | c->set_output(1, c->Vector(nvals)); // out.values |
62 | c->set_output(2, c->Vector(rank)); // out.dense_shape |
63 | return OkStatus(); |
64 | } |
65 | |
66 | REGISTER_OP("DenseCountSparseOutput" ) |
67 | .Input("values: T" ) |
68 | .Input("weights: output_type" ) |
69 | .Attr("T: {int32, int64}" ) |
70 | .Attr("minlength: int >= -1 = -1" ) |
71 | .Attr("maxlength: int >= -1 = -1" ) |
72 | .Attr("binary_output: bool" ) |
73 | .Attr("output_type: {int32, int64, float, double}" ) |
74 | .SetShapeFn(DenseCountSparseOutputShapeFn) |
75 | .Output("output_indices: int64" ) |
76 | .Output("output_values: output_type" ) |
77 | .Output("output_dense_shape: int64" ); |
78 | |
79 | REGISTER_OP("SparseCountSparseOutput" ) |
80 | .Input("indices: int64" ) |
81 | .Input("values: T" ) |
82 | .Input("dense_shape: int64" ) |
83 | .Input("weights: output_type" ) |
84 | .Attr("T: {int32, int64}" ) |
85 | .Attr("minlength: int >= -1 = -1" ) |
86 | .Attr("maxlength: int >= -1 = -1" ) |
87 | .Attr("binary_output: bool" ) |
88 | .Attr("output_type: {int32, int64, float, double}" ) |
89 | .SetShapeFn(SparseCountSparseOutputShapeFn) |
90 | .Output("output_indices: int64" ) |
91 | .Output("output_values: output_type" ) |
92 | .Output("output_dense_shape: int64" ); |
93 | |
94 | REGISTER_OP("RaggedCountSparseOutput" ) |
95 | .Input("splits: int64" ) |
96 | .Input("values: T" ) |
97 | .Input("weights: output_type" ) |
98 | .Attr("T: {int32, int64}" ) |
99 | .Attr("minlength: int >= -1 = -1" ) |
100 | .Attr("maxlength: int >= -1 = -1" ) |
101 | .Attr("binary_output: bool" ) |
102 | .Attr("output_type: {int32, int64, float, double}" ) |
103 | .SetShapeFn(RaggedCountSparseOutputShapeFn) |
104 | .Output("output_indices: int64" ) |
105 | .Output("output_values: output_type" ) |
106 | .Output("output_dense_shape: int64" ); |
107 | |
108 | } // namespace tensorflow |
109 | |