Merge pull request #230 from thesps/bestof_220

Best of PR #220

hls4ml/converters/__init__.py

@@ -86,5 +86,8 @@ def convert_from_keras_model(model, output_dir='my-hls-test', project_name='mypr
 
     if 'Optimizers' in hls_config:
         config['HLSConfig']['Optimizers'] = hls_config['Optimizers']
+
+    if 'SkipOptimizers' in hls_config:
+        config['HLSConfig']['SkipOptimizers'] = hls_config['SkipOptimizers']
 
     return keras_to_hls(config)

hls4ml/model/hls_layers.py

@@ -1144,6 +1144,7 @@ def _get_transforms_config(self, params):
         params['sublayer_configs'] = '\n'.join(sublayer_configs)
 
 layer_map = {
+    'Input'              : Input,
     'InputLayer'         : Input,
     'Activation'         : Activation,
     'QActivation'        : Activation,

hls4ml/model/hls_model.py

@@ -12,7 +12,7 @@
 from hls4ml.model.hls_layers import *
 from hls4ml.templates import get_backend
 from hls4ml.writer import get_writer
-from hls4ml.model.optimizer import optimize_model
+from hls4ml.model.optimizer import optimize_model, get_available_passes
 
 class HLSConfig(object):
     def __init__(self, config):
@@ -143,7 +143,20 @@ def get_compression(self, layer):
 
     def _parse_hls_config(self):
         hls_config = self.config['HLSConfig']
+
         self.optimizers = hls_config.get('Optimizers')
+        if 'SkipOptimizers' in hls_config:
+            if self.optimizers is not None:
+                raise Exception('Invalid optimizer configuration, please use either "Optimizers" or "SkipOptimizers".')
+            skip_optimizers = hls_config.get('SkipOptimizers')
+            selected_optimizers = get_available_passes()
+            for opt in skip_optimizers:
+                try:
+                    selected_optimizers.remove(opt)
+                except ValueError:
+                    pass                
+            self.optimizers = selected_optimizers
+
         model_cfg = hls_config.get('Model')
         if model_cfg is not None:
             precision_cfg = model_cfg.get('Precision')
@@ -355,6 +368,14 @@ def get_layer_output_variable(self, output_name):
         return self.output_vars[output_name]
 
     def write(self):
+        def make_stamp():
+            from string import hexdigits
+            from random import choice
+            length = 8
+            return ''.join(choice(hexdigits) for m in range(length))
+
+        self.config.config['Stamp'] = make_stamp()
+
         self.config.writer.write_hls(self)
 
     def compile(self):
@@ -367,7 +388,7 @@ def compile(self):
             ret_val = os.system('bash build_lib.sh')
             if ret_val != 0:
                 raise Exception('Failed to compile project "{}"'.format(self.config.get_project_name()))
-            lib_name = 'firmware/{}.so'.format(self.config.get_project_name())
+            lib_name = 'firmware/{}-{}.so'.format(self.config.get_project_name(), self.config.get_config_value('Stamp'))
             if self._top_function_lib is not None:
 
                 if platform.system() == "Linux":

hls4ml/model/optimizer/__init__.py

@@ -1,6 +1,6 @@
 from __future__ import absolute_import
 
-from hls4ml.model.optimizer.optimizer import OptimizerPass, register_pass, get_optimizer, optimize_model
+from hls4ml.model.optimizer.optimizer import OptimizerPass, register_pass, get_optimizer, optimize_model, get_available_passes
 
 
 from hls4ml.model.optimizer.passes.nop import EliminateLinearActivation

hls4ml/model/optimizer/optimizer.py

@@ -24,6 +24,9 @@ def register_pass(name, opt_cls):
 def get_optimizer(name):
     return optimizer_map[name]()
 
+def get_available_passes():
+    return list(optimizer_map.keys())
+
 def optimize_model(model, passes=None):
     if passes is None:
         passes = optimizer_map.keys()

hls4ml/templates/vivado/build_lib.sh

@@ -9,8 +9,9 @@ fi
 LDFLAGS=
 INCFLAGS="-Ifirmware/ap_types/"
 PROJECT=myproject
+LIB_STAMP=mystamp
 
 ${CC} ${CFLAGS} ${INCFLAGS} -c firmware/${PROJECT}.cpp -o ${PROJECT}.o
 ${CC} ${CFLAGS} ${INCFLAGS} -c ${PROJECT}_bridge.cpp -o ${PROJECT}_bridge.o
-${CC} ${CFLAGS} ${INCFLAGS} -shared ${PROJECT}.o ${PROJECT}_bridge.o -o firmware/${PROJECT}.so
+${CC} ${CFLAGS} ${INCFLAGS} -shared ${PROJECT}.o ${PROJECT}_bridge.o -o firmware/${PROJECT}-${LIB_STAMP}.so
 rm -f *.o

hls4ml/templates/vivado/build_prj.tcl

@@ -92,6 +92,8 @@ if {$opt(cosim)} {
   set time_start [clock clicks -milliseconds]
   cosim_design -trace_level all
   set time_end [clock clicks -milliseconds]
+  puts "INFO:"
+  puts [read [open myproject_prj/solution1/sim/report/myproject_cosim.rpt r]]
   report_time "C/RTL SIMULATION" $time_start $time_end
 }
 

hls4ml/templates/vivado/myproject_test.cpp

@@ -56,7 +56,6 @@ int main(int argc, char **argv)
   if (fin.is_open() && fpr.is_open()) {
     while ( std::getline(fin,iline) && std::getline (fpr,pline) ) {
       if (e % CHECKPOINT == 0) std::cout << "Processing input " << e << std::endl;
-      e++;
       char* cstr=const_cast<char*>(iline.c_str());
       char* current;
       std::vector<float> in;
@@ -85,6 +84,7 @@ int main(int argc, char **argv)
         std::cout << "Quantized predictions" << std::endl;
         //hls-fpga-machine-learning insert quantized
       }
+      e++;
     }
     fin.close();
     fpr.close();

hls4ml/utils/config.py

@@ -84,11 +84,12 @@ def config_from_keras_model(model, granularity='model', default_precision='ap_fi
         keras_layer_config = model_arch['config']
         if 'layers' in keras_layer_config: # Newer Keras versions have 'layers' in 'config' key
             keras_layer_config = keras_layer_config['layers']
-        # Sequential doesn't have InputLayer
-        input_layer = {}
-        input_layer['name'] = 'input1'
-        input_layer['class_name'] = 'InputLayer'
-        layer_list.append(input_layer)
+        # Sequential doesn't have InputLayer in TF < 2.3 (Keras 2.4.0)
+        if keras_layer_config[0]['class_name'] != 'InputLayer':
+            input_layer = {}
+            input_layer['name'] = 'input1'
+            input_layer['class_name'] = 'Input'
+            layer_list.append(input_layer)
     elif model_arch['class_name'] in ['Model', 'Functional']:
         print('Interpreting Model')
         keras_layer_config = model_arch['config']['layers']
@@ -108,6 +109,9 @@ def config_from_keras_model(model, granularity='model', default_precision='ap_fi
         layer['class_name'] = keras_layer['class_name']
         layer['config'] = keras_layer['config']
 
+        if layer['class_name'] == 'InputLayer':
+            layer['class_name'] = 'Input'
+
         if layer['class_name'] in qkeras_layers:
             layer['precision'] = {}
             for qname, qclass in layer['config'].items():
@@ -169,6 +173,11 @@ def make_layer_config(layer):
                 print('WARNING: Found no precision information in QKeras layer {} ({})'.format(layer['name'], layer['class_name']))
                 layer_config['Precision'] = default_precision
             layer_config['ReuseFactor'] = default_reuse_factor
+
+        elif layer['class_name'] == 'Input':
+            layer_config['Precision'] = {}
+            layer_config['Precision']['result'] = default_precision
+
         else:
             layer_config['Precision'] = default_precision
 
@@ -189,7 +198,7 @@ def make_layer_config(layer):
     elif granularity.lower() == 'type':
         type_config = {}
         for layer in layer_list:
-            if layer['class_name'] in type_config or layer['class_name'] == 'InputLayer':
+            if layer['class_name'] in type_config:
                 continue
             layer_config = make_layer_config(layer)
             type_config[layer['class_name']] = layer_config
@@ -199,8 +208,6 @@ def make_layer_config(layer):
     elif granularity.lower() == 'name':
         name_config = {}
         for layer in layer_list:
-            if layer['class_name'] == 'InputLayer': # Skip INputLayer
-                continue
             layer_config = make_layer_config(layer)
             name_config[layer['name']] = layer_config
 

hls4ml/writer/vivado_writer.py

@@ -531,6 +531,7 @@ def write_build_script(self, model):
 
         for line in f.readlines():
             line = line.replace('myproject', model.config.get_project_name())
+            line = line.replace('mystamp', model.config.get_config_value('Stamp'))
 
             fout.write(line)
         f.close()

setup.py

@@ -7,7 +7,7 @@
     long_description = f.read()
 
 setup(name='hls4ml',
-      version='0.3.0',
+      version='0.4.0',
       description='Machine learning in FPGAs using HLS',
       long_description=long_description,
       long_description_content_type='text/markdown',
@@ -36,8 +36,6 @@
           'Intended Audience :: Science/Research',
           'License :: OSI Approved :: Apache Software License',
           'Programming Language :: C++',
-          'Programming Language :: Python :: 2',
-          'Programming Language :: Python :: 2.7',
           'Programming Language :: Python :: 3',
           'Programming Language :: Python :: 3.6',
           'Topic :: Software Development :: Libraries',