Update pragmas (fix a bug), load weights for simulation in the wrapper, and add _LOOP labels

Author: GiuseppeDiGuglielmo

hls4ml/templates/vivado_accelerator/myproject_axi.cpp

@@ -9,6 +9,14 @@ void myproject(
 
     //hls-fpga-machine-learning insert local vars
 
+#ifndef __SYNTHESIS__
+    static bool loaded_weights = false;
+    if (!loaded_weights) {
+        //hls-fpga-machine-learning insert load weights
+        loaded_weights = true;
+    }
+#endif
+
     //hls-fpga-machine-learning insert enqueue
 
     //hls-fpga-machine-learning insert call

hls4ml/writer/vivado_accelerator_writer.py

@@ -91,6 +91,8 @@ def write_axi_wrapper(self, model):
                 newline = '#include "{}_axi.h"\n'.format(model.config.get_project_name())
                 for b in model_brams:
                     newline += '#include "weights/{}.h"\n'.format(b.name)
+                newline += '\n'
+                newline += '#include "parameters.h"\n'
             elif '//hls-fpga-machine-learning insert local vars' in line:
                 newline = ''
                 if self.vivado_accelerator_config.get_interface() == 'axi_stream':
@@ -128,6 +130,16 @@ def write_axi_wrapper(self, model):
                     newline += indent + '#pragma HLS INTERFACE ap_ctrl_none port=return\n'
                     if model.config.get_config_value("IOType") == 'io_stream':
                         newline += indent + '#pragma HLS DATAFLOW\n'
+            elif '//hls-fpga-machine-learning insert load weights' in line:
+                newline = ''
+                for layer in model.get_layers():
+                    for w in layer.get_weights():
+                        if w.weight_class == 'CompressedWeightVariable':
+                            newline += indent + '    nnet::load_compressed_weights_from_txt<{}, {}>({}, "{}.txt");\n'.format(w.type.name, w.nonzeros, w.name, w.name)
+                        elif w.weight_class == 'ExponentWeightVariable':
+                            newline += indent + '    nnet::load_exponent_weights_from_txt<{}, {}>({}, "{}.txt");\n'.format(w.type.name, w.data_length, w.name, w.name)
+                        else:
+                            newline += indent + '    nnet::load_weights_from_txt<{}, {}>({}, "{}.txt");\n'.format(w.type.name, w.data_length, w.name, w.name)
             elif '//hls-fpga-machine-learning insert enqueue' in line:
                 io_type = model.config.get_config_value("IOType")
                 if io_type == 'io_parallel':
@@ -143,10 +155,12 @@ def write_axi_wrapper(self, model):
                     newline += indent + '}\n'
                 elif io_type == 'io_stream':
                     newline = ''
+                    newline += 'LOAD_INPUT_OUTER_LOOP:\n'
                     newline += indent + 'for(unsigned i = 0; i < N_IN / {input_t}::size; ++i) {{\n'
                     # newline += indent + indent + '#pragma HLS PIPELINE\n'
                     newline += indent + indent + '{input_t} ctype;\n'
                     newline += indent + indent + '#pragma HLS DATA_PACK variable=ctype\n'
+                    newline += 'LOAD_INPUT_INNER_LOOP:\n'
                     newline += indent + indent + 'for(unsigned j = 0; j < {input_t}::size; j++) {{\n'
                     # newline += indent + indent + indent + '#pragma HLS UNROLL\n'
                     if self.vivado_accelerator_config.get_interface() == 'axi_stream':
@@ -173,9 +187,11 @@ def write_axi_wrapper(self, model):
                     newline += indent + '}\n'
                 elif io_type == 'io_stream':
                     newline = ''
+                    newline += 'STORE_OUTPUT_OUTER_LOOP:\n'
                     newline += indent + 'for(unsigned i = 0; i < N_OUT / {result_t}::size; ++i) {{\n'
                     # newline += indent + indent + '#pragma HLS PIPELINE\n'
                     newline += indent + indent + '{result_t} ctype = out_local.read();\n'
+                    newline += 'STORE_OUTPUT_INNER_LOOP:\n'
                     newline += indent + indent + 'for(unsigned j = 0; j < {result_t}::size; j++) {{\n'
                     # newline += indent + indent + indent + '#pragma HLS UNROLL\n'
                     if self.vivado_accelerator_config.get_interface() == 'axi_stream':
@@ -192,6 +208,35 @@ def write_axi_wrapper(self, model):
         f.close()
         fout.close()
 
+    def modify_project_cpp(self, model):
+        '''
+        Modify the build_prj.tcl and build_lib.sh scripts to add the extra wrapper files and set the top function
+        '''
+        filedir = os.path.dirname(os.path.abspath(__file__))
+        oldfile = '{}/firmware/{}.cpp'.format(model.config.get_output_dir(), model.config.get_project_name())
+        newfile = '{}/build_prj_axi.tcl'.format(model.config.get_output_dir())
+        f = open(oldfile, 'r')
+        fout = open(newfile, 'w')
+
+        for line in f.readlines():
+            if '#pragma HLS INTERFACE axis port=' in line:
+                newline = ''
+            elif '#pragma HLS INTERFACE bram port=' in line:
+                newline = ''
+            elif 'nnet::load_weights_from_txt' in line:
+                newline = ''
+            elif 'nnet::load_exponent_weights_from_txt' in line:
+                newline = ''
+            elif 'nnet::load_compressed_weights_from_txt' in line:
+                newline = ''
+            else:
+                newline = line
+            fout.write(newline)
+
+        f.close()
+        fout.close()
+        os.rename(newfile, oldfile)
+
     def modify_build_script(self, model):
         '''
         Modify the build_prj.tcl and build_lib.sh scripts to add the extra wrapper files and set the top function
@@ -373,6 +418,7 @@ def write_hls(self, model):
         self.write_driver(model)
         self.write_wrapper_test(model)
         self.write_axi_wrapper(model)
+        self.modify_project_cpp(model)
         self.modify_build_script(model)
         self.write_new_tar(model)