[Refactor] simplify fpgadataflow transformation names

src/finn/transformation/fpgadataflow/compilation_transformation.py → src/finn/transformation/fpgadataflow/compile.py

@@ -3,8 +3,8 @@ import finn.custom_op.registry as registry
 from finn.transformation import Transformation
 
 
-class Compilation(Transformation):
-    """Compilation for all nodes in model"""
+class Compile(Transformation):
+    """Compile for all nodes in model"""
 
     def __init__(self):
         super().__init__()

tests/fpgadataflow/test_fpgadataflow_fclayer.py

@@ -8,8 +8,8 @@ import finn.custom_op.xnorpopcount as xp
 from finn.core.datatype import DataType
 from finn.core.modelwrapper import ModelWrapper
 from finn.core.utils import gen_finn_dt_tensor
-from finn.transformation.fpgadataflow.code_gen_transformation import CodeGen
-from finn.transformation.fpgadataflow.compilation_transformation import Compilation
+from finn.transformation.fpgadataflow.codegen import CodeGen
+from finn.transformation.fpgadataflow.compile import Compile
 
 
 def make_single_fclayer_modelwrapper(W, pe, simd, wdt, idt, odt, T=None, tdt=None):
@@ -107,7 +107,7 @@ def test_fpgadataflow_fclayer_noact(idt, wdt, nf, sf, mw, mh):
     x = gen_finn_dt_tensor(idt, (1, mw))
     model = make_single_fclayer_modelwrapper(W, pe, simd, wdt, idt, odt)
     model = model.transform(CodeGen())
-    model = model.transform(Compilation())
+    model = model.transform(Compile())
     # prepare input data
     input_dict = prepare_inputs(model, x, idt)
     if wdt == DataType.BIPOLAR and idt == DataType.BIPOLAR:

tests/fpgadataflow/test_layer_streaming_maxpool_batch.py

@@ -4,8 +4,8 @@ from onnx import TensorProto, helper
 import finn.core.onnx_exec as oxe
 from finn.core.datatype import DataType
 from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.fpgadataflow.code_gen_transformation import CodeGen
-from finn.transformation.fpgadataflow.compilation_transformation import Compilation
+from finn.transformation.fpgadataflow.codegen import CodeGen
+from finn.transformation.fpgadataflow.compile import Compile
 
 
 def test_layer_streaming_maxpool_batch():
@@ -112,7 +112,7 @@ def test_layer_streaming_maxpool_batch():
     print(input_tensor)
 
     model = model.transform(CodeGen())
-    model = model.transform(Compilation())
+    model = model.transform(Compile())
 
     input_dict = {"in": input_tensor}
     output_dict = oxe.execute_onnx(model, input_dict)

tests/transformation/test_code_gen_trafo.py

 import os
 
-import numpy as np
 from onnx import TensorProto, helper
 
 import finn.core.utils as util
 from finn.core.datatype import DataType
 from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.fpgadataflow.code_gen_transformation import CodeGen
+from finn.transformation.fpgadataflow.codegen import CodeGen
 
 
 def test_code_gen_trafo():

tests/transformation/test_compilation_trafo.py

 import os
 
-import numpy as np
 from onnx import TensorProto, helper
 
 import finn.core.utils as util
 from finn.core.datatype import DataType
 from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.fpgadataflow.code_gen_transformation import CodeGen
-from finn.transformation.fpgadataflow.compilation_transformation import Compilation
+from finn.transformation.fpgadataflow.codegen import CodeGen
+from finn.transformation.fpgadataflow.compile import Compile
 
 
 def test_compilation_trafo():
@@ -19,7 +18,6 @@ def test_compilation_trafo():
     wmem = mw * mh // (pe * simd)
     nf = mh // pe
     sf = mw // simd
-    tmem = nf
 
     inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, sf, simd])
     outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, nf, pe])
@@ -57,7 +55,7 @@ def test_compilation_trafo():
     model.set_initializer("weights", W)
 
     model = model.transform(CodeGen())
-    model = model.transform(Compilation())
+    model = model.transform(Compile())
     for node in model.graph.node:
         compilation_attribute = util.get_by_name(node.attribute, "executable_path")
         executable = compilation_attribute.s.decode("UTF-8")