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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 <math.h>
7 #include <stddef.h>
8 #include <stdint.h>
9 
10 #include <xnnpack.h>
11 #include <xnnpack/log.h>
12 #include <xnnpack/params.h>
13 #include <xnnpack/subgraph.h>
14 
15 
create_elu_operator(const struct xnn_node * node,const struct xnn_value * values,size_t num_values,struct xnn_operator_data * opdata)16 static enum xnn_status create_elu_operator(
17   const struct xnn_node* node,
18   const struct xnn_value* values,
19   size_t num_values,
20   struct xnn_operator_data* opdata)
21 {
22   assert(node->num_inputs == 1);
23   const uint32_t input_id = node->inputs[0];
24   assert(input_id != XNN_INVALID_VALUE_ID);
25   assert(input_id < num_values);
26 
27   assert(node->num_outputs == 1);
28   const uint32_t output_id = node->outputs[0];
29   assert(output_id != XNN_INVALID_VALUE_ID);
30   assert(output_id < num_values);
31 
32   const size_t num_input_dims = values[input_id].shape.num_dims;
33   const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1];
34 
35   enum xnn_status status;
36   switch (node->compute_type) {
37     case xnn_compute_type_fp32:
38       status = xnn_create_elu_nc_f32(
39         channel_dim /* channels */, channel_dim /* input stride */, channel_dim /* output stride */,
40         node->params.elu.alpha,
41         node->flags,
42         &opdata->operator_object);
43       break;
44 #ifndef XNN_NO_QS8_OPERATORS
45     case xnn_compute_type_qs8:
46       status = xnn_create_elu_nc_qs8(
47         channel_dim /* channels */, channel_dim /* input stride */, channel_dim /* output stride */,
48         node->params.elu.alpha,
49         (int8_t) values[input_id].quantization.zero_point,
50         values[input_id].quantization.scale,
51         (int8_t) values[output_id].quantization.zero_point,
52         values[output_id].quantization.scale,
53         INT8_MIN, INT8_MAX,
54         node->flags,
55         &opdata->operator_object);
56       break;
57 #endif  // XNN_NO_QS8_OPERATORS
58     default:
59       XNN_UNREACHABLE;
60   }
61   if (status == xnn_status_success) {
62     opdata->batch_size = xnn_shape_multiply_non_channel_dims(&values[input_id].shape);
63     opdata->inputs[0] = input_id;
64     opdata->outputs[0] = output_id;
65   }
66   return status;
67 }
68 
setup_elu_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_elu_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_elu_nc_f32:
93       return xnn_setup_elu_nc_f32(
94         opdata->operator_object,
95         opdata->batch_size,
96         input_data,
97         output_data,
98         threadpool);
99 #ifndef XNN_NO_QS8_OPERATORS
100     case xnn_operator_type_elu_nc_qs8:
101       return xnn_setup_elu_nc_qs8(
102         opdata->operator_object,
103         opdata->batch_size,
104         input_data,
105         output_data,
106         threadpool);
107 #endif  // XNN_NO_QS8_OPERATORS
108     default:
109       XNN_UNREACHABLE;
110   }
111 }
112 
xnn_define_elu(xnn_subgraph_t subgraph,float alpha,uint32_t input_id,uint32_t output_id,uint32_t flags)113 enum xnn_status xnn_define_elu(
114   xnn_subgraph_t subgraph,
115   float alpha,
116   uint32_t input_id,
117   uint32_t output_id,
118   uint32_t flags)
119 {
120   if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) {
121     xnn_log_error("failed to define %s operator: XNNPACK is not initialized",
122       xnn_node_type_to_string(xnn_node_type_elu));
123     return xnn_status_uninitialized;
124   }
125 
126   if (alpha <= 0.0f || !isnormal(alpha)) {
127     xnn_log_error(
128       "failed to define %s operator with %.7g alpha parameter: alpha must be finite, normalized, and positive",
129       xnn_node_type_to_string(xnn_node_type_elu), alpha);
130     return xnn_status_invalid_parameter;
131   }
132 
133   if (input_id >= subgraph->num_values) {
134     xnn_log_error(
135       "failed to define %s operator with input ID #%" PRIu32 ": invalid Value ID",
136       xnn_node_type_to_string(xnn_node_type_elu), input_id);
137     return xnn_status_invalid_parameter;
138   }
139 
140   const struct xnn_value* input_value = &subgraph->values[input_id];
141   if (input_value->type != xnn_value_type_dense_tensor) {
142     xnn_log_error(
143       "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
144       xnn_node_type_to_string(xnn_node_type_elu), input_id, input_value->type);
145     return xnn_status_invalid_parameter;
146   }
147 
148   switch (input_value->datatype) {
149     case xnn_datatype_fp32:
150 #ifndef XNN_NO_QS8_OPERATORS
151     case xnn_datatype_qint8:
152 #endif  // !defined(XNN_NO_QS8_OPERATORS)
153       break;
154     default:
155       xnn_log_error(
156         "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
157         xnn_node_type_to_string(xnn_node_type_elu), input_id,
158         xnn_datatype_to_string(input_value->datatype), input_value->datatype);
159       return xnn_status_invalid_parameter;
160   }
161 
162   if (output_id >= subgraph->num_values) {
163     xnn_log_error(
164       "failed to define %s operator with output ID #%" PRIu32 ": invalid Value ID",
165       xnn_node_type_to_string(xnn_node_type_elu), output_id);
166     return xnn_status_invalid_parameter;
167   }
168 
169   const struct xnn_value* output_value = &subgraph->values[output_id];
170   if (output_value->type != xnn_value_type_dense_tensor) {
171     xnn_log_error(
172       "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
173       xnn_node_type_to_string(xnn_node_type_elu), output_id, output_value->type);
174     return xnn_status_invalid_parameter;
175   }
176 
177   enum xnn_compute_type compute_type = xnn_compute_type_invalid;
178   switch (output_value->datatype) {
179     case xnn_datatype_fp32:
180       compute_type = xnn_compute_type_fp32;
181       break;
182 #ifndef XNN_NO_QS8_OPERATORS
183     case xnn_datatype_qint8:
184       compute_type = xnn_compute_type_qs8;
185       break;
186 #endif  // !defined(XNN_NO_QS8_OPERATORS)
187     default:
188       xnn_log_error(
189         "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
190         xnn_node_type_to_string(xnn_node_type_elu), output_id,
191         xnn_datatype_to_string(output_value->datatype), output_value->datatype);
192       return xnn_status_invalid_parameter;
193   }
194 
195   if (input_value->datatype != output_value->datatype) {
196     xnn_log_error(
197       "failed to define %s operator with input ID #%" PRIu32 " and output ID #%" PRIu32
198       ": mismatching datatypes across the input (%s) and output (%s)",
199       xnn_node_type_to_string(xnn_node_type_elu), input_id, output_id,
200       xnn_datatype_to_string(input_value->datatype),
201       xnn_datatype_to_string(output_value->datatype));
202     return xnn_status_invalid_parameter;
203   }
204 
205   struct xnn_node* node = xnn_subgraph_new_node(subgraph);
206   if (node == NULL) {
207     return xnn_status_out_of_memory;
208   }
209 
210   node->type = xnn_node_type_elu;
211   node->compute_type = compute_type;
212   node->params.elu.alpha = alpha;
213   node->num_inputs = 1;
214   node->inputs[0] = input_id;
215   node->num_outputs = 1;
216   node->outputs[0] = output_id;
217   node->flags = flags;
218 
219   node->create = create_elu_operator;
220   node->setup = setup_elu_operator;
221 
222   return xnn_status_success;
223 }
224