started split layer (#26)

* started split layer

* working with main branch now (for current tests)

* added test for optimiser

* working on improving resource modelling

* updated resource models

* changes to split layer

* fixed merge conflict

* updated visualiser and fn model for splitlayer

Co-authored-by: AlexMontgomerie <[email protected]>
Co-authored-by: AlexMontgomerie <[email protected]>

README.md

@@ -26,6 +26,14 @@ A suite of tests have been created for the optimiser repo. To run all of them, u
 python -m unittest discover tests/
 ```
 
+## Testing
+
+A suite of tests have been created for the optimiser repo. To run all of them, use the following:
+
+```
+python -m unittest discover tests/
+```
+
 ## Optimiser Framework
 
 The main tool is the optimisation script which generates an optimised hardware topology for a given model and platform. There are several components needed for this: a model of the hardware, transforms that map the model to the hardware and an optimisation scheme that chooses the best mapping. These will be outlined later.

fpgaconvnet_optimiser/cli.py

@@ -15,6 +15,8 @@
 
 import fpgaconvnet_optimiser.tools.graphs as graphs
 
+import fpgaconvnet_optimiser.tools.graphs as graphs
+
 def main():
     parser = argparse.ArgumentParser(description="Optimiser Script")
     parser.add_argument('-n','--name',metavar='PATH',required=True,

fpgaconvnet_optimiser/models/layers/ConvolutionLayer.py

@@ -142,14 +142,14 @@ def rates_graph(self):
             rates_graph[0,0] = 1
             rates_graph[0,1] = 1
         else:
-            rates_graph[0,0] = self.modules['sliding_window'].rate_in(0)
-            rates_graph[0,1] = self.modules['sliding_window'].rate_out(0)
+            rates_graph[0,0] = self.modules['sliding_window'].rate_in()
+            rates_graph[0,1] = self.modules['sliding_window'].rate_out()
         # fork
-        rates_graph[1,1] = self.modules['fork'].rate_in(0)
-        rates_graph[1,2] = self.modules['fork'].rate_out(0)
+        rates_graph[1,1] = self.modules['fork'].rate_in()
+        rates_graph[1,2] = self.modules['fork'].rate_out()
         # conv
-        rates_graph[2,2] = self.modules['conv'].rate_in(0)
-        rates_graph[2,3] = self.modules['conv'].rate_out(0)
+        rates_graph[2,2] = self.modules['conv'].rate_in()
+        rates_graph[2,3] = self.modules['conv'].rate_out()
         # accum
         rates_graph[3,3] = self.modules['accum'].rate_in(0)
         rates_graph[3,4] = self.modules['accum'].rate_out(0)

fpgaconvnet_optimiser/models/layers/InnerProductLayer.py

@@ -110,14 +110,14 @@ def rates_graph(self):
         rates_graph[0,0] = self.modules['fork'].rate_in(0)
         rates_graph[0,1] = self.modules['fork'].rate_out(0)
         # conv
-        rates_graph[1,1] = self.modules['conv'].rate_in(0)
-        rates_graph[1,2] = self.modules['conv'].rate_out(0)
+        rates_graph[1,1] = self.modules['conv'].rate_in()
+        rates_graph[1,2] = self.modules['conv'].rate_out()
         # accum
-        rates_graph[2,2] = self.modules['accum'].rate_in(0)
-        rates_graph[2,3] = self.modules['accum'].rate_out(0)
+        rates_graph[2,2] = self.modules['accum'].rate_in()
+        rates_graph[2,3] = self.modules['accum'].rate_out()
         # glue
-        rates_graph[3,3] = self.modules['glue'].rate_in(0)
-        rates_graph[3,4] = self.modules['glue'].rate_out(0)
+        rates_graph[3,3] = self.modules['glue'].rate_in()
+        rates_graph[3,4] = self.modules['glue'].rate_out()
 
         return rates_graph
 

fpgaconvnet_optimiser/models/layers/Layer.py

@@ -335,7 +335,6 @@ def load_coef(self):
         #             "../../coefficients/{}_rsc_coef.npy".format(module))
         #     )
 
-
     def update(self):
         pass
 

fpgaconvnet_optimiser/models/layers/PoolingLayer.py

@@ -19,7 +19,7 @@ def __init__(
             k_size      =2,
             stride      =2,
             pad         =0,
-            fine        =1,
+            fine        =1
         ):
 
         # initialise parent class
@@ -108,11 +108,11 @@ def update(self):
     def rates_graph(self):
         rates_graph = np.zeros( shape=(2,3) , dtype=float )
         # sliding_window
-        rates_graph[0,0] = self.modules['sliding_window'].rate_in(0)
-        rates_graph[0,1] = self.modules['sliding_window'].rate_out(0)
+        rates_graph[0,0] = self.modules['sliding_window'].rate_in()
+        rates_graph[0,1] = self.modules['sliding_window'].rate_out()
         # pool
-        rates_graph[1,1] = self.modules['pool'].rate_in(0)
-        rates_graph[1,2] = self.modules['pool'].rate_out(0)
+        rates_graph[1,1] = self.modules['pool'].rate_in()
+        rates_graph[1,2] = self.modules['pool'].rate_out()
 
         return rates_graph
 

tests/test_layers.py

@@ -43,7 +43,6 @@ class TestPoolingLayer(TestLayerTemplate,unittest.TestCase):
         "tests/configs/layers/pooling/config_12.json",
     )
     def test_layer_configurations(self, config_path):
-
         # open configuration
         with open(config_path, "r") as f:
             config = json.load(f)
@@ -59,7 +58,6 @@ def test_layer_configurations(self, config_path):
             stride=config["stride"],
             pad=config["pad"],
         )
-
         # run tests
         self.run_test_dimensions(layer)
         self.run_test_rates(layer)
@@ -88,12 +86,10 @@ class TestConvolutionLayer(TestLayerTemplate,unittest.TestCase):
         "tests/configs/layers/convolution/config_19.json",
     )
     def test_layer_configurations(self, config_path):
-
         # open configuration
         with open(config_path, "r") as f:
             config = json.load(f)
 
-        # initialise layer
         layer = ConvolutionLayer(
             config["filters"],
             config["rows"],
@@ -108,6 +104,36 @@ def test_layer_configurations(self, config_path):
             fine=config["fine"],
         )
 
+        # run tests
+        self.run_test_dimensions(layer)
+        self.run_test_rates(layer)
+
+@ddt.ddt
+class TestSplitLayer(TestLayerTemplate,unittest.TestCase):
+
+    @ddt.data(
+        "tests/configs/layers/split/config_0.json",
+    )
+    def test_layer_configurations(self, config_path):
+
+        # open configuration
+        with open(config_path, "r") as f:
+            config = json.load(f)
+
+        # initialise layer
+        layer = SplitLayer(
+            config["rows"],
+            config["cols"],
+            config["channels"],
+            config["coarse"],
+            ports_out=config["ports_out"]
+        )
+
+        # run tests
+        self.run_test_dimensions(layer)
+        self.run_test_rates(layer)
+
+
         # run tests
         self.run_test_dimensions(layer)
         self.run_test_rates(layer)

tests/test_modules.py

@@ -42,6 +42,15 @@ def run_test_resources(self, module):
         self.assertGreaterEqual(rsc["BRAM"], 0.0)
 
 
+    def run_test_resources(self, module):
+
+        rsc = module.rsc()
+        self.assertGreaterEqual(rsc["LUT"], 0.0)
+        self.assertGreaterEqual(rsc["FF"], 0.0)
+        self.assertGreaterEqual(rsc["DSP"], 0.0)
+        self.assertGreaterEqual(rsc["BRAM"], 0.0)
+
+
 @ddt.ddt
 class TestForkModule(TestModuleTemplate,unittest.TestCase):
 
@@ -77,12 +86,6 @@ def test_module_configurations(self, config_path):
         self.run_test_methods_exist(module)
         self.run_test_dimensions(module)
         self.run_test_rates(module)
-<<<<<<< HEAD
-
-=======
-        self.run_test_resources(module)
-
->>>>>>> 9c525fe... started split layer (#26)
         # additional checks
         self.assertGreater(module.filters,0)