Merge pull request #1010 from calad0i/im2col_default

Make im2col default option for quartus
fastmachinelearning · Jun 28, 2024 · 02688f1 · 02688f1
2 parents 9e9944f + d72900b
commit 02688f1
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Showing 4 changed files with 4 additions and 8 deletions.
diff --git a/hls4ml/backends/quartus/quartus_backend.py b/hls4ml/backends/quartus/quartus_backend.py
@@ -274,7 +274,7 @@ def init_conv1d(self, layer):
         # - combination - at compile-time, the decision between Winograd and im2col is made
         # - im2col - specifically use im2col
         # - Winograd - use Winograd, if possible
-        layer.set_attr('implementation', layer.model.config.get_layer_config_value(layer, 'Implementation', 'combination'))
+        layer.set_attr('implementation', layer.model.config.get_layer_config_value(layer, 'Implementation', 'im2col'))
 
         layer.set_attr(
             'n_partitions', 1
@@ -305,7 +305,7 @@ def init_conv2d(self, layer):
         # - combination - at compile-time, the decision between Winograd and im2col is made
         # - im2col - specifically use im2col
         # - Winograd - use Winograd, if possible
-        layer.set_attr('implementation', layer.model.config.get_layer_config_value(layer, 'Implementation', 'combination'))
+        layer.set_attr('implementation', layer.model.config.get_layer_config_value(layer, 'Implementation', 'im2col'))
 
         layer.set_attr(
             'n_partitions', 1

diff --git a/hls4ml/templates/quartus/firmware/nnet_utils/nnet_conv1d_resource.h b/hls4ml/templates/quartus/firmware/nnet_utils/nnet_conv1d_resource.h
@@ -3,6 +3,7 @@
 
 #include "nnet_common.h"
 #include "nnet_dense.h"
+#include <cstdint>
 
 namespace nnet {
 

diff --git a/hls4ml/templates/quartus/firmware/nnet_utils/nnet_conv2d_resource.h b/hls4ml/templates/quartus/firmware/nnet_utils/nnet_conv2d_resource.h
@@ -4,6 +4,7 @@
 #include "nnet_common.h"
 #include "nnet_dense.h"
 #include "nnet_helpers.h"
+#include <cstdint>
 
 namespace nnet {
 

diff --git a/test/pytest/test_auto_precision.py b/test/pytest/test_auto_precision.py
@@ -151,12 +151,6 @@ def test_auto_precision_conv(keras_model_conv1d, keras_model_conv2d, data_2d, da
         },
     }
 
-    # Winograd is not bit-accurate, so avoid it.
-    if backend == 'Quartus' and io_type == 'io_parallel':
-        config['LayerName']['first_layer']['Implementation'] = 'im2col'
-        config['LayerName']['middle_layer']['Implementation'] = 'im2col'
-        config['LayerName']['last_layer']['Implementation'] = 'im2col'
-
     odir = str(test_root_path / f'hls4mlprj_auto_{model_type}_{backend}_{io_type}')
     hls_model = hls4ml.converters.convert_from_keras_model(
         model, hls_config=config, io_type=io_type, output_dir=odir, backend=backend