Merged with dev

aidge_export_cpp/templates/configuration/softmax_config.jinja

@@ -8,5 +8,6 @@
 #define {{ name|upper }}_AXIS_SIZE {{ axis_size }}
 #define {{ name|upper }}_AXIS_SIZE_POST {{ axis_size_post }}
 #define {{ name|upper }}_AXIS_SIZE_PRE {{ axis_size_pre }}
+{% include "./_save_outputs.jinja" %}
 
 #endif /* {{ name|upper }}_LAYER_H */

aidge_export_cpp/templates/configuration/transpose_ND_config.jinja

@@ -13,5 +13,6 @@ constexpr int {{ name|upper }}_OUT_STRIDES[] = { {{ out_strides | join(', ') }}
 
 constexpr int {{ name|upper }}_PERMUTE[] = { {{ output_dims_order | join(', ') }} };
 constexpr int {{ name|upper }}_DIMS[] = { {{ in_dims[0] | join(', ') }} };
+{% include "./_save_outputs.jinja" %}
 
 #endif /* {{ name|upper }}_LAYER_H */
\ No newline at end of file

aidge_export_cpp/templates/data/aidge_tensor.jinja

 #include <stdint.h>
 
-static const {{ data_t }} {{ name }}
+#define {{name|upper}}_FMT  Format::{{ dformat | upper }}
+
+{%- set format_map = {
+    "int8_t": "%4d",
+    "int16_t": "%6d",
+    "int32_t": "%6d",
+    "int64_t": "%8d",
+    "uint8_t": "%4d",
+    "uint16_t": "%6d",
+    "uint32_t": "%6d",
+    "uint64_t": "%8d",
+    "float": "%.9f",
+    "half_float::half": "%.9f",
+    "double": "%.17f"
+} %}
+
+static const {{ dtype }} {{ name }}
 {%- for dim in dims -%}
     [{{ dim }}]
 {%- endfor %} = 
-{{ values }};
+
+{{ '{' -}}
+
+{# 1D #}
+{%- if dims | length == 1 -%}
+{{ '{' }}
+{%- for x in range(dims[0]) -%}
+{{ format_map[dtype] | format(values[x]) }},
+{%- endfor -%}
+{{ '}' }};
+{%- endif -%}
+
+{#- 2D #}
+{%- if dims | length == 2 -%}
+{%- for y in range(dims[0]) -%}
+{{ '{' }}
+    {%- for x in range(dims[1]) -%}
+        {{ format_map[dtype] | format(values[y][x]) }}, 
+    {%- endfor -%}
+{{ '}' }},
+{%- endfor -%}
+{%- endif -%}
+
+{#- 3D #}
+{%- if dims | length == 3 -%}
+{%- for z in range(dims[0]) %}
+{{ '{' }}
+    {%- for y in range(dims[1]) %}
+    {{ '{' }}
+        {%- for x in range(dims[2]) -%}
+            {{ format_map[dtype] | format(values[z][y][x]) }}, 
+        {%- endfor -%}
+    {{ '}' }},
+    {%- endfor %}
+{{ '}' }},
+{%- endfor -%}
+{%- endif -%}
+
+{#- 4D #}
+{%- if dims | length == 4 -%}
+{%- for n in range(dims[0]) %}
+{{ '{' }}
+    {%- for z in range(dims[1]) %}
+    {{ '{' }}
+        {%- for y in range(dims[2]) %}
+        {{ '{' }}
+            {%- for x in range(dims[3]) -%}
+                {{ format_map[dtype] | format(values[n][z][y][x]) }}, 
+            {%- endfor -%}
+        {{ '}' }},
+        {%- endfor %}
+    {{ '}' }},
+    {%- endfor %}
+{{ '}' }},
+{%- endfor %}
+{%- endif -%}
+{{ '};' }}

aidge_export_cpp/templates/data/parameters.jinja

 {#- For libraries -#}
 #include <stdint.h>
 
+{%- set format_map = {
+    "int8_t": "%4d",
+    "int16_t": "%6d",
+    "int32_t": "%6d",
+    "int64_t": "%8d",
+    "uint8_t": "%4d",
+    "uint16_t": "%6d",
+    "uint32_t": "%6d",
+    "uint64_t": "%8d",
+    "float": "%.9f",
+    "half_float::half": "%.9f",
+    "double": "%.17f"
+} %}
+
 {# Design header of the array -#}
-static const {{ data_t }} {{ name }}[{{ values|length }}] __attribute__((section(".nn_data"))) =
+static const {{ dtype }} {{ name }}[{{ dims | join("*") }}] __attribute__((section(".nn_data"))) =
 {
-    {# For loop to add new elements -#}
-    {%- for i in range(values|length) %}
+{# 1D #}
+{%- if dims | length == 1 -%}
+{%- for x in range(dims[0]) -%}
+{{ format_map[dtype] | format(values[x]) }}, 
+{%- endfor -%}
+{%- endif -%}
+
+{#- 2D #}
+{%- if dims | length == 2 -%}
+{%- for y in range(dims[0]) %}
+{{ ' ' }}
+    {%- for x in range(dims[1]) -%}
+        {{ format_map[dtype] | format(values[y][x]) }}, 
+    {%- endfor %}
+{%- endfor -%}
+{%- endif -%}
+
+{#- 3D #}
+{%- if dims | length == 3 -%}
+{%- for z in range(dims[0]) %}
+{{ ' ' }}
+    {%- for y in range(dims[1]) %}
+    {{ ' ' }}
+        {%- for x in range(dims[2]) -%}
+            {{ format_map[dtype] | format(values[z][y][x]) }}, 
+        {%- endfor -%}
+    {%- endfor %}
+{%- endfor -%}
+{%- endif -%}
 
-        {#- Last value -#}
-        {%- if (i+1) == values|length -%}
-        {{ values[i]|string }}
-        {%- else -%}
-            {%- if (i+1) % 5 == 0 -%}
-            {{ values[i]|string + ",\n\t" }}
-            {%- else -%}
-            {{ values[i]|string + ", " }}
-            {%- endif -%}
-        {%- endif -%}
+{#- 4D #}
+{%- if dims | length == 4 -%}
+{%- for n in range(dims[0]) %}
+{{ ' ' }}
+    {%- for z in range(dims[1]) %}
+    {{ ' ' }}
+        {%- for y in range(dims[2]) %}
+        {{ ' ' }}
+            {%- for x in range(dims[3]) -%}
+                {{ format_map[dtype] | format(values[n][z][y][x]) }}, 
+            {%- endfor -%}
+        {%- endfor %}
     {%- endfor %}
+{%- endfor %}
+{%- endif %}
 };

aidge_export_cpp/templates/kernel_forward/_aidge_cmp.jinja

@@ -2,7 +2,9 @@
 #if AIDGE_CMP
     aidge_cmp<{{ out_name[0] | upper }}_NB_OUTPUTS, 
               {{ out_name[0] | upper }}_OUT_HEIGHT, 
-              {{ out_name[0] | upper }}_OUT_WIDTH>
+              {{ out_name[0] | upper }}_OUT_WIDTH,
+              {{ out_name[0] | upper }}_AIDGE_FMT,
+              {{ out_name[0] | upper }}_DEV_FMT>
              ("{{ name }}", ({{out_cdtype[0]}}*) {{ out_name[0] }}_aidge, {{ out_name[0] }});
 #endif
 {%- endif %}
\ No newline at end of file

aidge_export_cpp/templates/kernel_forward/_save_outputs.jinja

 
 #if SAVE_OUTPUTS
-{% for outidx in range(nb_out) -%}
-    FILE* {{out_name[outidx]|upper}}_STREAM = fopen("data/export_outputs/{{out_name[outidx]}}.txt", "w");
-    saveOutputs<{{out_cdtype[outidx]}}>(
-        {{out_name[outidx]|upper}}_NB_OUTPUTS,
-        {{out_name[outidx]|upper}}_OUT_HEIGHT,
-        {{out_name[outidx]|upper}}_OUT_WIDTH,
-        {#- {{out_name[outidx]|upper}}_CONT_OFFSET,
-        {{out_name[outidx]|upper}}_CONT_SIZE,
-        {{out_name[outidx]|upper}}_WRAP_OFFSET,
-        {{out_name[outidx]|upper}}_WRAP_SIZE,
-        {{out_name[outidx]|upper}}_STRIDE, #}
-        {{out_name[outidx]}},
-        {{out_name[outidx]|upper}}_STREAM,
-        Format::NHWC);
-    fclose({{out_name[outidx]|upper}}_STREAM);
-{% endfor %}
+printf("[NOTICE] Saving outputs of node {{ name }}\n");
+FILE* {{ out_name[0] | upper }}_STREAM = fopen("data/export_outputs/{{out_name[0]}}.txt", "w");
+saveOutputs<{{ out_name[0] | upper }}_NB_OUTPUTS,
+            {{ out_name[0] | upper }}_OUT_HEIGHT,
+            {{ out_name[0] | upper }}_OUT_WIDTH,
+            {{ out_name[0] | upper }}_DEV_FMT>
+            ({#- {{ 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, -#}
+            {{ out_name[0] }},
+            {{ out_name[0] | upper }}_STREAM);
+fclose({{ out_name[0] | upper }}_STREAM);
 #endif

examples/export_LeNet/.gitignore

@@ -4,3 +4,4 @@ log_outputs/*
 assets/*
 data/*
 log.txt
+*.json

examples/export_LeNet/lenet.py

@@ -18,11 +18,7 @@ import aidge_backend_cpu
 import aidge_quantization
 import aidge_export_cpp
 
-from aidge_export_cpp.export_utils import (
-    cpp_fuse_to_metaops,
-    set_nodes_names,
-    set_nodes_datatypes,
-    exclude_unwanted_producers)
+from aidge_export_cpp.export_utils import *
 
 from aidge_core.export_utils import remove_optional_inputs, get_node_from_metaop
 
@@ -310,8 +306,9 @@ if quantize_model:
         tensors[i] = aidge_core.Tensor(array)
         tensors[i].set_datatype(TARGET_TYPE)
         tensors[i].set_backend("cpu")
-    # Setting modele to CPU for export
-    model.set_backend("cpu")
+
+# Setting model to CPU for export
+model.set_backend("cpu")
 
 
 # --------------------------------------------------------------
@@ -442,9 +439,8 @@ Once the tensors have been casted, the log_outputs() function can be
 called to store their values into log files.
 """
 
-if os.path.isdir("log_outputs"):
-    shutil.rmtree("log_outputs")
-model.log_outputs("log_outputs")
+if AIDGE_CMP:
+    generate_aidge_ifmaps(model)
 
 # --------------------------------------------------------------
 # TEST MODE
@@ -461,29 +457,10 @@ changing the inputs of the layer, to isolate the source of the issue.
 for node in model.get_nodes():
     node.attributes().dev_mode = DEV_MODE
 
-# --------------------------------------------------------------
-# AIDGE CMP
-# --------------------------------------------------------------
-
-"""
-If the --aidge_cmp option is enabled, the feature maps generated by aidge with the
-backend cpu will be exported in the generated export. It will be used as reference
-to verify that the results with the optimized kernels are correct for the exported
-model.
-This option has to be passed to each node in order to be used within the Export Nodes.
-(JConv, JPad, ...) that you can find in the "operators" folder.
-"""
-
-if AIDGE_CMP:
-    for node in model.get_nodes():
-        node.attributes().aidge_cmp = True
-
 # --------------------------------------------------------------
 # EXPORT THE MODEL
 # --------------------------------------------------------------
 
-model.save("exported_model")
-
 aidge_export_cpp.export(EXPORT_FOLDER,
                         model,
                         scheduler,
@@ -503,4 +480,4 @@ try:
     for std_line in aidge_core.utils.run_command(["./bin/run_export"], cwd=EXPORT_FOLDER):
         print(std_line, end="")
 except subprocess.CalledProcessError as e:
-    raise RuntimeError(0, f"An error occurred, failed to run export.") from e
\ No newline at end of file
+    raise RuntimeError(0, f"An error occurred, failed to run export.") from e

examples/export_ResNet18/resnet18.py

@@ -23,12 +23,7 @@ import aidge_backend_cpu
 import aidge_quantization
 import aidge_export_cpp
 
-from aidge_export_cpp.export_utils import (
-    cpp_fuse_to_metaops,
-    exclude_unwanted_producers,
-    set_nodes_names,
-    set_nodes_datatypes,
-    normalize)
+from aidge_export_cpp.export_utils import *
 
 from aidge_core.export_utils import remove_optional_inputs, get_node_from_metaop
 
@@ -506,16 +501,6 @@ tensors' datatypes to Int8, except for biases which should remain in Int32.
 if quantize_model:
     set_nodes_datatypes(model)
 
-# Store tensors values into log files
-"""
-Once the tensors has been casted, the log_outputs() function can be
-called to store their values into log files.
-"""
-
-if os.path.isdir("log_outputs"):
-    shutil.rmtree("log_outputs")
-model.log_outputs("log_outputs")
-
 # --------------------------------------------------------------
 # TEST MODE
 # --------------------------------------------------------------
@@ -545,15 +530,12 @@ This option has to be passed to each node in order to be used within the Export
 """
 
 if AIDGE_CMP:
-    for node in model.get_nodes():
-        node.attributes().aidge_cmp = True
+    generate_aidge_ifmaps(model)
 
 # --------------------------------------------------------------
 # EXPORT THE MODEL
 # --------------------------------------------------------------
 
-model.save("exported_model")
-
 aidge_export_cpp.export(EXPORT_FOLDER,
                         model,
                         scheduler,