Testing benchmark for streaming Quartus

fastmachinelearning · May 31, 2022 · 0fbf3c7 · 0fbf3c7
1 parent 739cb4a
commit 0fbf3c7
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Showing 2 changed files with 76 additions and 3 deletions.
diff --git a/hls4ml/templates/quartus/myproject_test.cpp b/hls4ml/templates/quartus/myproject_test.cpp
@@ -26,6 +26,8 @@
 #include "firmware/parameters.h"
 #include "firmware/myproject.h"
 
+#include "firmware/nnet_utils/nnet_helpers.h"
+
 #define CHECKPOINT 5000
 
 // This function is written to avoid stringstream, which is

diff --git a/hls4ml/writer/quartus_writer.py b/hls4ml/writer/quartus_writer.py
@@ -330,9 +330,80 @@ def write_test_bench(self, model):
                 else:
                     newline = line
                 fout.write(newline)
-        else:
-            # Temporary change, to allow compilation
-            pass
+        elif model.config.get_config_value('IOType') == 'io_stream':
+            for line in f.readlines():
+                indent = ' ' * (len(line) - len(line.lstrip(' ')))
+
+                # TODO - Works only with one input/output
+
+                # Insert numbers
+                if 'myproject' in line:
+                    newline = line.replace('myproject', model.config.get_project_name())
+                elif '//hls-fpga-machine-learning insert data' in line:
+                    newline = line
+                    newline += '      int in_begin = 0; \n'
+                    newline += '      int in_end; \n'
+                    newline += '      inputs.emplace_back(); \n'
+                    for inp in model.get_input_variables():
+                        newline += f'      in_end = in_begin + ({inp.size_cpp()}); \n'
+                        newline += f'      float vals[{inp.size_cpp()}]; \n'
+                        newline += f'      for (int j = in_begin ; j < in_end ; j++) {{'
+                        newline += f'          vals[j%{inp.size_cpp()}] = in[j]; \n'
+                        newline += f'      }}'
+                        newline += f'      nnet::convert_data<float, {inp.type.name}, {inp.size_cpp()}>(vals, inputs[0].{inp.member_name});\n'
+                        newline += f'      in_begin = in_end; \n'
+                    newline += f'      outputs.emplace_back(); \n'
+                elif '//hls-fpga-machine-learning insert zero' in line:
+                    newline = line
+                    newline += indent + 'for(int i = 0; i < num_iterations; i++) {\n'
+                    for inp in model.get_input_variables():
+                        newline += indent + f'  inputs.emplace_back(); \n'
+                        newline += indent + f'  outputs.emplace_back(); \n'
+                        newline += f'      float vals[{inp.size_cpp()}]; \n'
+                        newline += f'      for (int j = 0 ; j < {inp.size_cpp()} ; j++) {{ \n'
+                        newline += f'          vals[j%{inp.size_cpp()}] = 0.0; \n'
+                        newline += f'      }}'
+                        newline += f'      nnet::convert_data<float, {inp.type.name}, {inp.size_cpp()}>(vals, inputs[0].{inp.member_name}); \n' 
+                    newline += indent + '} \n'
+
+                elif '//hls-fpga-machine-learning insert top-level-function' in line:
+                    newline = line
+
+                    newline += indent + 'for(int i = 0; i < num_iterations; i++) { \n'
+                    newline += indent + f'  ihc_hls_enqueue(&outputs[i], {model.config.get_project_name()}, inputs[i]); \n'
+                    newline += indent + '} \n'
+                elif 'hls-fpga-machine-learning insert run' in line:
+                    newline = line
+                    newline += '    ' + 'ihc_hls_component_run_all({}); \n'.format(model.config.get_project_name())
+                elif '//hls-fpga-machine-learning insert predictions' in line:
+                    newline = line
+                    newline += indent + 'for(int i = 0; i < {}; i++) {{ \n'.format(outvar.size_cpp())
+                    newline += indent + '  std::cout << predictions[j][i] << " "; \n'
+                    newline += indent + '}\n'
+                    newline += indent + 'std::cout << std::endl; \n'
+                elif '//hls-fpga-machine-learning insert tb-output' in line:
+                    newline = line
+                    newline += indent + 'float res_tb[{}]; \n'.format(outvar.size_cpp())
+                    newline += indent + 'nnet::convert_data_back<{}, float, {}>(outputs[0].{}, res_tb); \n'.format(outvar.type.name,
+                                                                                                                outvar.size_cpp(),
+                                                                                                                outvar.member_name)
+                    newline += indent + 'for(int i = 0; i < {}; i++) {{\n'.format(outvar.size_cpp())
+                    newline += indent + '  fout << res_tb[i] << " "; \n'
+                    newline += indent + '} \n'
+                    newline += indent + 'fout << std::endl; \n'
+                elif '//hls-fpga-machine-learning insert output' in line or '//hls-fpga-machine-learning insert quantized' in line:
+                    newline = line
+                    newline += indent + 'float res[{}]; \n'.format(outvar.size_cpp())
+                    newline += indent + 'nnet::convert_data_back<{}, float, {}>(outputs[0].{}, res); \n'.format(outvar.type.name,
+                                                                                                            outvar.size_cpp(),
+                                                                                                            outvar.member_name)
+                    newline += indent + 'for(int i = 0; i < {}; i++) {{\n'.format(outvar.size_cpp())
+                    newline += indent + '  std::cout << res[i] << " "; \n'
+                    newline += indent + '} \n'
+                    newline += indent + 'std::cout << std::endl; \n'
+                else:
+                    newline = line
+                fout.write(newline)
 
         f.close()
         fout.close()