[Fix] Fix for conv depthwise and softmax, mbnet-v1 now working

aidge_export_arm_cortexm/_Aidge_Arm/kernels/Convolution/ConvDW.hpp

@@ -95,8 +95,8 @@ __attribute__((always_inline)) inline void convcellDWPropagate(
 
             for (int output = 0; output < NB_OUTPUTS; ++output) {
                 const int channel = (output * NB_CHANNELS) / NB_OUTPUTS;
-
-                SUM_T weightedSum = biasses[output];
+                using Sum_T = typename std::conditional<std::is_floating_point<Input_T>::value, float, int32_t>::type;
+                Sum_T weightedSum = biasses[output];
 
                 for (int sy = 0; sy < KERNEL_HEIGHT; ++sy) {
                     if ((PADDING_Y != 0

aidge_export_arm_cortexm/_Aidge_Arm/kernels/Softmax/aidge_softmax_chw_float32.h

@@ -2,16 +2,16 @@
 
 void aidge_softmax_chw_float32 (float* inputs, 
                             float* outputs,
-                            int inputDims[],
+                            const int inputDims[],
                             int axis,
-                            unsigned int size_inputDim,
-                            unsigned int size)
+                            const unsigned int size_inputDim,
+                            const unsigned int size)
 {
 
 	axis += (axis >= 0 ) ? 0 : size_inputDim;
 
     int postAxisElems = 1;
-    for (int i = axis+1; i < size_inputDim; ++i) {
+    for (unsigned int i = axis+1; i < size_inputDim; ++i) {
         postAxisElems *= inputDims[i];
     }
     int preAxisElems = 1;

aidge_export_arm_cortexm/_Aidge_Arm/templates/configuration/conv_dw_cinfig.jinja

+#define {{ name|upper }}_LAYER_H
+
+#include "typedefs.h"
+#include "nn_scaling_functions.hpp"
+
+{% include "./_def_io.jinja" %}
+{% include "./_meminfo.jinja" %}
+
+// Attributes
+#define {{ name|upper }}_KERNEL_HEIGHT {{ kernel_dims[1] }}
+#define {{ name|upper }}_KERNEL_WIDTH {{ kernel_dims[0] }}
+#define {{ name|upper }}_PADDING_Y {{ padding[1] }}
+#define {{ name|upper }}_PADDING_X {{ padding[0] }}
+#define {{ name|upper }}_STRIDE_Y {{ stride_dims[1] }}
+#define {{ name|upper }}_STRIDE_X {{ stride_dims[0] }}
+#define {{ name|upper }}_DILATION_Y {{ dilation_dims[1] }}
+#define {{ name|upper }}_DILATION_X {{ dilation_dims[0] }}
+{# #define {{ name|upper }}_GROUP {{ group }} #}
+
+// Activation/Scaling
+#define {{ name|upper }}_ACTIVATION {{ activation }}
+
+{%- if scaling_type == "floating_point" %}
+static const N2D2_Export::FloatingPointScaling {{ name|upper }}_SCALING = { {{scaling_value}} };
+{%- elif scaling_type == "fixed_point" %}
+static const N2D2_Export::FixedPointScaling<{{scaling_value}}, {{fractional_bits}}> {{ name|upper }}_SCALING;
+{%- elif scaling_type == "single_shift" %}
+static const N2D2_Export::SingleShiftScaling<{{shift_value}}> {{ name|upper }}_SCALING;
+{%- else %}
+static const N2D2_Export::NoScaling {{ name|upper }}_SCALING;
+{%- endif %}
+
+// Sizes
+#define {{ name|upper }}_WEIGHTS_SIZE {{ out_chan[0] * in_chan[0] * kernel_dims[1] * kernel_dims[0] }}
+#define {{ name|upper }}_BIASES_SIZE {{ out_chan[0] }}
+#define {{ name|upper }}_OUTPUTS_SIZE {{ out_chan[0] * out_height[0] * out_width[0] }}
+#define {{ name|upper }}_CHANNELS_SIZE {{ in_chan[0] * in_height[0] * in_width[0] }}
+
+
+#endif /* {{ name|upper }}_LAYER_H */

aidge_export_arm_cortexm/_Aidge_Arm/templates/configuration/softmax.jinja

+
+{% include "./_def_io.jinja" %}
+{% include "./_meminfo.jinja" %}
+
 {#- For name header -#}
 #ifndef {{ name|upper }}_LAYER_H
 #define {{ name|upper }}_LAYER_H
@@ -5,9 +9,8 @@
 {# For layer configuration -#}
 #define {{ name|upper }}_INPUTS_SIZE {{ in_size[0] }}
 #define {{ name|upper }}_OUTPUTS_SIZE {{ out_size[0] }}
-#define {{ name|upper }}_DIMS {{ in_dims[0] }}
 #define {{ name|upper }}_AXIS {{ axis }}
 #define {{ name|upper }}_INPUT_DIMS_SIZE {{ in_dims[0]|length}}
-
+static const int {{ name|upper }}_DIMS[] = { {{ in_dims[0] | join(', ') }} };
 
 #endif /* {{ name|upper }}_LAYER_H */

aidge_export_arm_cortexm/_Aidge_Arm/templates/forward_call/conv_dw_kernel.jinja

+{% filter indent(width=4, first=False) %}
+{% include "./_mem_offset.jinja" %}
+N2D2_Export::convcellDWPropagate<{{ in_name[0]|upper }}_NB_CHANNELS,
+                               {{ in_name[0]|upper }}_IN_HEIGHT,
+                               {{ in_name[0]|upper }}_IN_WIDTH,
+                               {{ out_name[0]|upper }}_NB_OUTPUTS,
+                               {{ out_name[0]|upper }}_OUT_HEIGHT,
+                               {{ out_name[0]|upper }}_OUT_WIDTH,
+                               {{ name|upper }}_PADDING_Y,
+                               {{ name|upper }}_PADDING_X,
+                               {{ name|upper }}_STRIDE_Y,
+                               {{ name|upper }}_STRIDE_X,
+                               {{ name|upper }}_KERNEL_HEIGHT,
+                               {{ name|upper }}_KERNEL_WIDTH,
+                               {{ name|upper }}_ACTIVATION,
+                               {{ in_name[0]|upper }}_CONT_OFFSET,
+                               {{ in_name[0]|upper }}_CONT_SIZE,
+                               {{ in_name[0]|upper }}_WRAP_OFFSET,
+                               {{ in_name[0]|upper }}_WRAP_SIZE,
+                               {{ in_name[0]|upper }}_STRIDE,
+                               {{ out_name[0]|upper }}_CONT_OFFSET,
+                               {{ out_name[0]|upper }}_CONT_SIZE,
+                               {{ out_name[0]|upper }}_WRAP_OFFSET,
+                               {{ out_name[0]|upper }}_WRAP_SIZE,
+                               {{ out_name[0]|upper }}_STRIDE>
+                               ({{in_name[0]}}, {{out_name[0]}}, {{in_name[2]}}, {{in_name[1]}}, {{ name|upper }}_SCALING);
+{% endfilter %}
+

aidge_export_arm_cortexm/operators.py

@@ -250,8 +250,8 @@ class ConvDW_ARMCortexM(ExportNodeCpp):
         # Use PaddedConv to add padding attribute
         self.attributes["padding"] = [0, 0]
 
-        self.config_template = str(ROOT / "_Aidge_Arm" / "templates" / "configuration" / "conv_config.jinja")
-        self.forward_template = str(ROOT / "_Aidge_Arm" / "templates" / "forward_call" / "conv_kernel.jinja")
+        self.config_template = str(ROOT / "_Aidge_Arm" / "templates" / "configuration" / "conv_dw_config.jinja")
+        self.forward_template = str(ROOT / "_Aidge_Arm" / "templates" / "forward_call" / "conv_dw_kernel.jinja")
         self.include_list = []
         self.kernels_to_copy = [
             str(ROOT / "_Aidge_Arm" / "kernels" / "Convolution" / "ConvDW.hpp")
@@ -275,8 +275,8 @@ class PaddedConvDW_ARMCortexM(ExportNodeCpp):
                 self.attributes["dilation_dims"] = n.get_operator(
                 ).attr.dilation_dims
 
-        self.config_template = str(ROOT / "_Aidge_Arm" / "templates" / "configuration" / "conv_config.jinja")
-        self.forward_template = str(ROOT / "_Aidge_Arm" / "templates" / "forward_call" / "conv_kernel.jinja")
+        self.config_template = str(ROOT / "_Aidge_Arm" / "templates" / "configuration" / "conv_dw_config.jinja")
+        self.forward_template = str(ROOT / "_Aidge_Arm" / "templates" / "forward_call" / "conv_dw_kernel.jinja")
         self.include_list = []
         self.kernels_to_copy = [
             str(ROOT / "_Aidge_Arm" / "kernels" / "Convolution" / "ConvDW.hpp")