moved sources

.gitignore

@@ -3,4 +3,4 @@
 .vscode/
 *.tar
 __pycache__
-/build/
+/c++/build/

.gitmodules

@@ -1,3 +1,3 @@
-[submodule "lib/json"]
-	path = lib/json
+[submodule "c++/lib/json"]
+	path = c++/lib/json
 	url = https://github.com/nlohmann/json

src/entrypoint.cpp

@@ -17,7 +17,7 @@ namespace tf_lib {
   REGISTER_OP("MyDummy")
     .Input("input: int32")
     .Output("output: int32")
-    .SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
+    .SetShapeFn([](InferenceContext* c) {
       c->set_output(0, c->input(0));
       return Status::OK();
     });
@@ -28,7 +28,7 @@ namespace tf_lib {
   REGISTER_OP("MyDummyBig")
     .Input("input: int32")
     .Output("output: int32")
-    .SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
+    .SetShapeFn([](InferenceContext* c) {
       c->set_output(0, c->input(0));
       return Status::OK();
     });

doku/referenzen.md

@@ -1,5 +0,0 @@
-https://www.tensorflow.org/guide/create_op
-
-https://www.elektronikpraxis.vogel.de/welche-hardware-eignet-sich-besser-zur-ki-beschleunigung-a-720869/
-https://www.extremetech.com/computing/247199-googles-dedicated-tensorflow-processor-tpu-makes-hash-intel-nvidia-inference-workloads
-https://towardsdatascience.com/types-of-optimization-algorithms-used-in-neural-networks-and-ways-to-optimize-gradient-95ae5d39529f

examples/screengrab.py

@@ -13,8 +13,8 @@ import tensorflow as tf
 from tensorflow.keras import layers, models
 
 import sys
-sys.path.append('..')
-from hostLib.layers.conv2D import Conv2D as Conv2DFPGA
+sys.path.append('../hostLib/')
+from hostLib.layers.conv2d import Conv2D as Conv2DFPGA
 
 bounding_box = {'top': 0, 'left': 0, 'width': 2560, 'height': 1440}
 width, height = 228, 228

examples/train.py

@@ -10,8 +10,8 @@ import numpy as np
 from IPython import embed
 
 import sys
-sys.path.append('..')
-from hostLib.layers.conv2D import Conv2D as Conv2DFPGA
+sys.path.append('../hostLib/')
+from hostLib.layers.conv2d import Conv2D as Conv2DFPGA
 
 batch_size = 128
 num_classes = 10

hostLib/layers/__init__.py

@@ -0,0 +1,2 @@
+
+__all__ = ["conv2d"]

load_op.py

@@ -2,4 +2,4 @@ import os
 import tensorflow as tf
 
 dir_path = os.path.dirname(os.path.realpath(__file__))
-op_lib = tf.load_op_library(dir_path + '/build/op_lib.so')
+op_lib = tf.load_op_library(dir_path + '/../c++/build/op_lib.so')

layers/__init__.py

@@ -1,2 +0,0 @@
-
-__all__ = ["conv2D", "dummy"]

tests/op_test.py

@@ -3,9 +3,8 @@ import numpy as np
 from IPython import embed
 
 import sys
-import os
-sys.path.append('..')
-from hostLib.layers.conv2D import Conv2D as Conv2DFPGA
+sys.path.append('../hostLib/')
+from hostLib.layers.conv2d import Conv2D as Conv2DFPGA
 from hostLib import load_op