1/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations 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
20namespace tensorflow {
21
22REGISTER_OP("BatchFunction")
23 .Input("in_tensors: Tin")
24 .Input("captured_tensors: Tcaptured")
25 .Output("out_tensors: Tout")
26 .Attr("f: func")
27 .Attr("num_batch_threads: int")
28 // 'max_batch_size' denotes the maximum batch size acceptable, i.e., inputs
29 // with larger batch size are simply invalidated.
30 // By default, 'max_batch_size' must be equal to max value of
31 // 'allowed_batch_sizes'.
32 // By setting 'enable_large_batch_splitting' (attribute below) to true,
33 // 'max_batch_size' can be greater than or equal to max value of
34 // 'allowed_batch_sizes', in other words,
35 // 1) input with size > 'max_batch_size' is still invalidated.
36 // 2) input with
37 // a) size <= 'max_batch_size'
38 // b) size > max value of 'allowed_batch_sizes'
39 // will automatically be split into multiple batches (with batch size in
40 // 'allowed_batch_sizes'), executed, and re-composed (as final output).
41 .Attr("max_batch_size: int")
42 .Attr("batch_timeout_micros: int")
43 .Attr("max_enqueued_batches: int = 10")
44 .Attr("allowed_batch_sizes: list(int) = []")
45 .Attr("container: string = ''")
46 .Attr("shared_name: string = ''")
47 .Attr("batching_queue: string = ''")
48 .Attr("Tin: list(type)")
49 .Attr("Tcaptured: list(type) >= 0")
50 .Attr("Tout: list(type)")
51 // If 'enable_large_batch_splitting' is true, for input batches exceeding
52 // the largest value in "allowed_batch_sizes", allow the batch to be split
53 // into multiple batches with batch size within "allowed_batch_sizes".
54 // NOTE: Support for `enable_large_batch_splitting == true` is still
55 // developed in progress.
56 .Attr("enable_large_batch_splitting: bool = false")
57 // TODO(apassos): Fix this shape inference function. It requires shape
58 // inference of function calls.
59 .SetShapeFn(shape_inference::UnknownShape)
60 .SetIsDistributedCommunication();
61
62REGISTER_OP("Batch")
63 .Input("in_tensors: T")
64 .Output("batched_tensors: T")
65 .Output("batch_index: int64")
66 .Output("id: int64")
67 .Attr("num_batch_threads: int")
68 .Attr("max_batch_size: int")
69 .Attr("max_enqueued_batches: int = 10")
70 .Attr("batch_timeout_micros: int")
71 .Attr("allowed_batch_sizes: list(int) = []")
72 .Attr("grad_timeout_micros: int")
73 .Attr("container: string = ''")
74 .Attr("shared_name: string = ''")
75 .Attr("batching_queue: string = ''")
76 .Attr("T: list(type)")
77 .SetShapeFn([](shape_inference::InferenceContext* c) {
78 std::vector<shape_inference::ShapeHandle> in_shapes;
79 TF_RETURN_IF_ERROR(c->input("in_tensors", &in_shapes));
80 std::vector<shape_inference::ShapeHandle> out_shapes(in_shapes.size());
81 for (int i = 0; i < in_shapes.size(); ++i) {
82 TF_RETURN_IF_ERROR(
83 c->ReplaceDim(in_shapes[i], 0, c->UnknownDim(), &out_shapes[i]));
84 }
85 TF_RETURN_IF_ERROR(c->set_output("batched_tensors", out_shapes));
86 TF_RETURN_IF_ERROR(c->set_output("id", {c->Scalar()}));
87 TF_RETURN_IF_ERROR(c->set_output(
88 "batch_index",
89 {c->MakeShape({shape_inference::DimensionOrConstant(c->UnknownDim()),
90 shape_inference::DimensionOrConstant(3)})}));
91 return OkStatus();
92 })
93 .SetIsDistributedCommunication();
94
95REGISTER_OP("Unbatch")
96 .Input("batched_tensor: T")
97 .Input("batch_index: int64")
98 .Input("id: int64")
99 .Output("unbatched_tensor: T")
100 .Attr("timeout_micros: int")
101 .Attr("container: string = ''")
102 .Attr("shared_name: string = ''")
103 .Attr("T: type")
104 .SetShapeFn([](shape_inference::InferenceContext* c) {
105 shape_inference::ShapeHandle out_shape;
106 TF_RETURN_IF_ERROR(
107 c->ReplaceDim(c->input(0), 0, c->UnknownDim(), &out_shape));
108 c->set_output(0, out_shape);
109 return OkStatus();
110 });
111
112REGISTER_OP("UnbatchGrad")
113 .Input("original_input: T")
114 .Input("batch_index: int64")
115 .Input("grad: T")
116 .Input("id: int64")
117 .Output("batched_grad: T")
118 .Attr("container: string = ''")
119 .Attr("shared_name: string = ''")
120 .Attr("T: type")
121 .SetShapeFn([](shape_inference::InferenceContext* c) {
122 c->set_output(0, c->UnknownShapeOfRank(c->Rank(c->input(2))));
123 return OkStatus();
124 });
125
126} // namespace tensorflow
127