1 // Copyright 2020 Google LLC
2 //
3 // This source code is licensed under the BSD-style license found in the
4 // LICENSE file in the root directory of this source tree.
5
6 #include <stddef.h>
7 #include <stdint.h>
8
9 #include <xnnpack.h>
10 #include <xnnpack/log.h>
11 #include <xnnpack/params.h>
12 #include <xnnpack/subgraph.h>
13
14
create_depth_to_space_operator(const struct xnn_node * node,const struct xnn_value * values,size_t num_values,struct xnn_operator_data * opdata)15 static enum xnn_status create_depth_to_space_operator(
16 const struct xnn_node* node,
17 const struct xnn_value* values,
18 size_t num_values,
19 struct xnn_operator_data* opdata)
20 {
21 assert(node->compute_type == xnn_compute_type_fp32);
22
23 assert(node->num_inputs == 1);
24 const uint32_t input_id = node->inputs[0];
25 assert(input_id != XNN_INVALID_VALUE_ID);
26 assert(input_id < num_values);
27
28 assert(node->num_outputs == 1);
29 const uint32_t output_id = node->outputs[0];
30 assert(output_id != XNN_INVALID_VALUE_ID);
31 assert(output_id < num_values);
32
33 const size_t input_channel_dim = values[input_id].shape.dim[3];
34 const size_t output_channel_dim = values[output_id].shape.dim[3];
35
36 enum xnn_status status;
37 if (values[input_id].layout == xnn_layout_type_nchw) {
38 assert(values[output_id].layout == xnn_layout_type_nhwc);
39 status = xnn_create_depth_to_space_nchw2nhwc_x32(
40 output_channel_dim /* output channels */,
41 input_channel_dim /* input stride */,
42 output_channel_dim /* output stride */,
43 node->params.depth_to_space.block_size,
44 node->flags,
45 &opdata->operator_object);
46 } else {
47 assert(values[input_id].layout == xnn_layout_type_nhwc);
48 assert(values[output_id].layout == xnn_layout_type_nhwc);
49 status = xnn_create_depth_to_space_nhwc_x32(
50 output_channel_dim /* output channels */,
51 input_channel_dim /* input stride */,
52 output_channel_dim /* output stride */,
53 node->params.depth_to_space.block_size,
54 node->flags,
55 &opdata->operator_object);
56 }
57 if (status == xnn_status_success) {
58 opdata->batch_size = values[input_id].shape.dim[0];
59 opdata->input_height = values[input_id].shape.dim[1];
60 opdata->input_width = values[input_id].shape.dim[2];
61 opdata->output_height = values[output_id].shape.dim[1];
62 opdata->output_width = values[output_id].shape.dim[2];
63 opdata->inputs[0] = input_id;
64 opdata->outputs[0] = output_id;
65 }
66 return status;
67 }
68
setup_depth_to_space_operator(const struct xnn_operator_data * opdata,const struct xnn_blob * blobs,size_t num_blobs,pthreadpool_t threadpool)69 static enum xnn_status setup_depth_to_space_operator(
70 const struct xnn_operator_data* opdata,
71 const struct xnn_blob* blobs,
72 size_t num_blobs,
73 pthreadpool_t threadpool)
74 {
75 const uint32_t input_id = opdata->inputs[0];
76 assert(input_id != XNN_INVALID_VALUE_ID);
77 assert(input_id < num_blobs);
78
79 const uint32_t output_id = opdata->outputs[0];
80 assert(output_id != XNN_INVALID_VALUE_ID);
81 assert(output_id < num_blobs);
82
83 const struct xnn_blob* input_blob = blobs + input_id;
84 const void* input_data = input_blob->data;
85 assert(input_data != NULL);
86
87 const struct xnn_blob* output_blob = blobs + output_id;
88 void* output_data = output_blob->data;
89 assert(output_data != NULL);
90
91 switch (opdata->operator_object->type) {
92 case xnn_operator_type_depth_to_space_nchw2nhwc_x32:
93 return xnn_setup_depth_to_space_nchw2nhwc_x32(
94 opdata->operator_object,
95 opdata->batch_size,
96 opdata->input_height,
97 opdata->input_width,
98 input_data,
99 output_data,
100 threadpool);
101 case xnn_operator_type_depth_to_space_nhwc_x32:
102 return xnn_setup_depth_to_space_nhwc_x32(
103 opdata->operator_object,
104 opdata->batch_size,
105 opdata->input_height,
106 opdata->input_width,
107 input_data,
108 output_data,
109 threadpool);
110 default:
111 XNN_UNREACHABLE;
112 }
113 }
114
xnn_define_depth_to_space(xnn_subgraph_t subgraph,uint32_t input_id,uint32_t output_id,uint32_t block_size,uint32_t flags)115 enum xnn_status xnn_define_depth_to_space(
116 xnn_subgraph_t subgraph,
117 uint32_t input_id,
118 uint32_t output_id,
119 uint32_t block_size,
120 uint32_t flags)
121 {
122 if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) {
123 xnn_log_error("failed to define %s operator: XNNPACK is not initialized",
124 xnn_node_type_to_string(xnn_node_type_depth_to_space));
125 return xnn_status_uninitialized;
126 }
127
128 if (input_id >= subgraph->num_values) {
129 xnn_log_error(
130 "failed to define %s operator with input ID #%" PRIu32 ": invalid Value ID",
131 xnn_node_type_to_string(xnn_node_type_depth_to_space), input_id);
132 return xnn_status_invalid_parameter;
133 }
134
135 const struct xnn_value* input_value = &subgraph->values[input_id];
136 if (input_value->type != xnn_value_type_dense_tensor) {
137 xnn_log_error(
138 "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
139 xnn_node_type_to_string(xnn_node_type_depth_to_space), input_id, input_value->type);
140 return xnn_status_invalid_parameter;
141 }
142
143 switch (input_value->datatype) {
144 case xnn_datatype_fp32:
145 break;
146 default:
147 xnn_log_error(
148 "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
149 xnn_node_type_to_string(xnn_node_type_depth_to_space), input_id,
150 xnn_datatype_to_string(input_value->datatype), input_value->datatype);
151 return xnn_status_invalid_parameter;
152 }
153
154 if (output_id >= subgraph->num_values) {
155 xnn_log_error(
156 "failed to define %s operator with output ID #%" PRIu32 ": invalid Value ID",
157 xnn_node_type_to_string(xnn_node_type_depth_to_space), output_id);
158 return xnn_status_invalid_parameter;
159 }
160
161 const struct xnn_value* output_value = &subgraph->values[output_id];
162 if (output_value->type != xnn_value_type_dense_tensor) {
163 xnn_log_error(
164 "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
165 xnn_node_type_to_string(xnn_node_type_depth_to_space), output_id, output_value->type);
166 return xnn_status_invalid_parameter;
167 }
168
169 switch (output_value->datatype) {
170 case xnn_datatype_fp32:
171 break;
172 default:
173 xnn_log_error(
174 "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
175 xnn_node_type_to_string(xnn_node_type_depth_to_space), output_id,
176 xnn_datatype_to_string(output_value->datatype), output_value->datatype);
177 return xnn_status_invalid_parameter;
178 }
179
180 if (block_size < 2) {
181 xnn_log_error(
182 "failed to define %s operator with block size #%" PRIu32 ": invalid block_size",
183 xnn_node_type_to_string(xnn_node_type_depth_to_space), block_size);
184 return xnn_status_invalid_parameter;
185 }
186
187 struct xnn_node* node = xnn_subgraph_new_node(subgraph);
188 if (node == NULL) {
189 return xnn_status_out_of_memory;
190 }
191
192 node->type = xnn_node_type_depth_to_space;
193 node->compute_type = xnn_compute_type_fp32;
194 node->num_inputs = 1;
195 node->inputs[0] = input_id;
196 node->num_outputs = 1;
197 node->outputs[0] = output_id;
198 node->params.depth_to_space.block_size = block_size;
199 node->flags = flags;
200
201 node->create = create_depth_to_space_operator;
202 node->setup = setup_depth_to_space_operator;
203
204 return xnn_status_success;
205 }
206