Publishing 2019 R1 content
[platform/upstream/dldt.git] / inference-engine / thirdparty / clDNN / src / embed.cpp
1 /*
2 // Copyright (c) 2018 Intel Corporation
3 //
4 // Licensed under the Apache License, Version 2.0 (the "License");
5 // you may not use this file except in compliance with the License.
6 // You may obtain a copy of the License at
7 //
8 //      http://www.apache.org/licenses/LICENSE-2.0
9 //
10 // Unless required by applicable law or agreed to in writing, software
11 // distributed under the License is distributed on an "AS IS" BASIS,
12 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 // See the License for the specific language governing permissions and
14 // limitations under the License.
15 */
16
17 ///////////////////////////////////////////////////////////////////////////////////////////////////
18 ///////////////////////////////////////////////////////////////////////////////////////////////////
19 #include "embed_inst.h"
20 #include "primitive_type_base.h"
21 #include "error_handler.h"
22 #include "json_object.h"
23
24 namespace cldnn
25 {
26         primitive_type_id embed_type_id()
27         {
28                 static primitive_type_base<embed> instance;
29                 return &instance;
30         }
31
32         layout embed_inst::calc_output_layout(embed_node const& node)
33         {
34         assert((bool)node.get_primitive()->output_data_type == false
35                && "Output data type forcing is not supported for embed_node!");
36         auto input_layout = node.input().get_output_layout();
37                 auto desc = node.get_primitive();
38                 auto weights_layout = node.weights().get_output_layout();
39
40                 auto result = layout(input_layout.data_type, format::bfyx, tensor(input_layout.size.batch[0], input_layout.size.spatial[0], weights_layout.size.batch[0], 1));
41                 return result;
42                 
43         }
44
45         std::string embed_inst::to_string(embed_node const& node)
46         {
47                 auto desc = node.get_primitive();
48                 auto node_info = node.desc_to_json();
49                 auto bias_id = desc->bias != "" ? desc->bias : "no bias";
50                 auto weights_id = desc->weights;
51
52                 std::stringstream primitive_description;
53
54                 json_composite embed_info;
55                 embed_info.add("weights id", weights_id);
56                 embed_info.add("bias id", bias_id);
57
58                 node_info->add("embed info", embed_info);
59                 node_info->dump(primitive_description);
60
61                 return primitive_description.str();
62         }
63
64         embed_inst::typed_primitive_inst(network_impl& network, embed_node const& node)
65                 :parent(network, node)
66         {
67         auto input_size = node.input().get_output_layout();
68                 auto output_size = output_memory().get_layout();
69                 CLDNN_ERROR_NOT_PROPER_FORMAT(node.id(), "input format", input_size.format.value, "expected format", format::yxfb, format::bfyx);
70                 CLDNN_ERROR_NOT_EQUAL(node.id(), "Input size", input_size.size.raw.size(), "output size", output_size.size.raw.size(), "");
71         CLDNN_ERROR_NOT_EQUAL(node.id(), "Input batch", input_size.size.batch[0], "output batch", output_size.size.batch[0], "");
72         CLDNN_ERROR_NOT_EQUAL(node.id(), "Input feature", input_size.size.feature[0], "size 1", 1, "");
73         CLDNN_ERROR_NOT_EQUAL(node.id(), "Input y size ", input_size.size.spatial[1], "size 1", 1, "");
74         }
75 }