diff --git a/AUTHORS.rst b/AUTHORS.rst
index 4b2194d1322981c471d6f77d994371e68ba519d0..a87cf170b065879f0c5e01e4726bc57608e5c4f2 100644
--- a/AUTHORS.rst
+++ b/AUTHORS.rst
@@ -2,4 +2,6 @@
Contributors
============
-* Yaman Umuroglu <yamanu@xilinx.com>
+* Yaman Umuroglu
+* Jakoba Petri-Koenig
+* Andrea Rigoni
diff --git a/run-docker.sh b/run-docker.sh
index 5b4f718ce3f1b8d3db0fb9c517ce3a414817ebf6..930766d6e5e14d089af66ca0de6ad8ca377433ca 100755
--- a/run-docker.sh
+++ b/run-docker.sh
@@ -17,6 +17,9 @@ DOCKER_TAG="finn_${DOCKER_UNAME}"
# uncomment to run multiple instances with different names
# DOCKER_INST_NAME="finn_${DOCKER_UNAME}_${DOCKER_RND}"
DOCKER_INST_NAME="finn_${DOCKER_UNAME}"
+# ensure Docker tag and inst. name are all lowercase
+DOCKER_TAG=$(echo "$DOCKER_TAG" | tr '[:upper:]' '[:lower:]')
+DOCKER_INST_NAME=$(echo "$DOCKER_INST_NAME" | tr '[:upper:]' '[:lower:]')
# the settings below will be taken from environment variables if available,
# otherwise the defaults below will be used
: ${JUPYTER_PORT=8888}
diff --git a/tests/fpgadataflow/test_code_gen_trafo.py b/tests/fpgadataflow/test_code_gen_trafo.py
index 0f153dfa59158f9cf3990e849690831d8de73858..414d7b42cc89400bbf6271f4c8aaa39fc83179c7 100644
--- a/tests/fpgadataflow/test_code_gen_trafo.py
+++ b/tests/fpgadataflow/test_code_gen_trafo.py
@@ -5,7 +5,6 @@ from onnx import TensorProto, helper
import finn.util.basic as util
from finn.core.datatype import DataType
from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.fpgadataflow.cleanup import CleanUp
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
@@ -66,4 +65,3 @@ def test_code_gen_trafo():
op type {} is empty!""".format(
node.op_type
)
- model = model.transform(CleanUp())
diff --git a/tests/fpgadataflow/test_compilation_trafo.py b/tests/fpgadataflow/test_compilation_trafo.py
index 3579485f37fb84a4bed6b5ca575e27c689a6521d..91f4b549911dc1a6cf8078d87208d4d603cc59a9 100644
--- a/tests/fpgadataflow/test_compilation_trafo.py
+++ b/tests/fpgadataflow/test_compilation_trafo.py
@@ -5,7 +5,6 @@ from onnx import TensorProto, helper
import finn.util.basic as util
from finn.core.datatype import DataType
from finn.core.modelwrapper import ModelWrapper
-from finn.transformation.fpgadataflow.cleanup import CleanUp
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
from finn.transformation.fpgadataflow.compile import Compile
@@ -63,4 +62,3 @@ def test_compilation_trafo():
op type {} does not exist!""".format(
node.op_type
)
- model = model.transform(CleanUp())
diff --git a/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py b/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
index 495c71dd14aa7ce0761e7b3765f6c8c3f4183079..389db8004d4a4fb1b07160720fd45ec53e60ba93 100644
--- a/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
+++ b/tests/fpgadataflow/test_fpgadataflow_convinputgenerator.py
@@ -6,7 +6,6 @@ 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.cleanup import CleanUp
from finn.transformation.fpgadataflow.codegen_ipgen import CodeGen_ipgen
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
from finn.transformation.fpgadataflow.compile import Compile
@@ -167,4 +166,3 @@ def test_fpgadataflow_slidingwindow(idt, k, ifm_dim, ifm_ch, stride):
model = model.transform(HLSSynth_IPGen())
y_produced = oxe.execute_onnx(model, input_dict)["outp"]
assert (y_produced == y_expected).all(), "rtlsim failed"
- model = model.transform(CleanUp())
diff --git a/tests/fpgadataflow/test_fpgadataflow_fclayer.py b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
index fcdd873f7d9195e0215bbc3f6ffb79843bffa843..5c1e3908c94a38fb008ca400f7058d8928807eb7 100644
--- a/tests/fpgadataflow/test_fpgadataflow_fclayer.py
+++ b/tests/fpgadataflow/test_fpgadataflow_fclayer.py
@@ -9,7 +9,6 @@ from finn.analysis.fpgadataflow.hls_synth_res_estimation import hls_synth_res_es
from finn.core.datatype import DataType
from finn.core.modelwrapper import ModelWrapper
from finn.custom_op.multithreshold import multithreshold
-from finn.transformation.fpgadataflow.cleanup import CleanUp
from finn.transformation.fpgadataflow.codegen_ipgen import CodeGen_ipgen
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
from finn.transformation.fpgadataflow.compile import Compile
@@ -175,7 +174,6 @@ def test_fpgadataflow_fclayer_npysim(idt, wdt, act, nf, sf, mw, mh):
# execute model
y_produced = oxe.execute_onnx(model, input_dict)["outp"]
assert (y_produced.reshape(y_expected.shape) == y_expected).all(), "npysim failed"
- model = model.transform(CleanUp())
# activation: None or DataType
@@ -257,5 +255,3 @@ def test_fpgadataflow_fclayer_rtlsim(idt, wdt, act, nf, sf, mw, mh):
hls_synt_res_est = model.analysis(hls_synth_res_estimation)
assert "StreamingFCLayer_Batch_0" in hls_synt_res_est
-
- model = model.transform(CleanUp())
diff --git a/tests/fpgadataflow/test_layer_streaming_maxpool_batch.py b/tests/fpgadataflow/test_layer_streaming_maxpool_batch.py
index 32aca4a59c924d2b4fbb967885a640723821727c..4c6396da55ac144f35fd21b841787d987e2069ff 100644
--- a/tests/fpgadataflow/test_layer_streaming_maxpool_batch.py
+++ b/tests/fpgadataflow/test_layer_streaming_maxpool_batch.py
@@ -4,7 +4,6 @@ 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.cleanup import CleanUp
from finn.transformation.fpgadataflow.codegen_npysim import CodeGen_npysim
from finn.transformation.fpgadataflow.compile import Compile
from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
@@ -111,7 +110,6 @@ def test_layer_streaming_maxpool_batch():
],
dtype=np.float32,
).reshape(2, 2, 4, 4)
- print(input_tensor)
model = model.transform(SetExecMode("npysim"))
model = model.transform(CodeGen_npysim())
@@ -119,5 +117,3 @@ def test_layer_streaming_maxpool_batch():
input_dict = {"in": input_tensor}
output_dict = oxe.execute_onnx(model, input_dict)
- print(output_dict)
- model = model.transform(CleanUp())
diff --git a/tests/transformation/test_batchnorm_to_affine.py b/tests/transformation/test_batchnorm_to_affine.py
index d23934ce2b24531e13f106abe2d3108406ac8cb4..b55b88d6f4e031237bc384ef3f28d9c6b0703693 100644
--- a/tests/transformation/test_batchnorm_to_affine.py
+++ b/tests/transformation/test_batchnorm_to_affine.py
@@ -30,16 +30,18 @@ def test_batchnorm_to_affine_lfc_w1a1():
os.remove(export_onnx_path)
-def test_batchnorm_to_affine_cnv_w1a1():
- lfc = get_test_model_trained("CNV", 1, 1)
- bo.export_finn_onnx(lfc, (1, 3, 32, 32), export_onnx_path)
- model = ModelWrapper(export_onnx_path)
- model = model.transform(InferShapes())
- model = model.transform(FoldConstants())
- # TODO shape inference failing on transformed model below -- needs debug
- new_model = model.transform(BatchNormToAffine())
- # check that there are no BN nodes left
- # TODO replace this with execution test
- op_types = list(map(lambda x: x.op_type, new_model.graph.node))
- assert "BatchNormalization" not in op_types
- os.remove(export_onnx_path)
+# cnv batchnorm to affine not yet supported
+
+# def test_batchnorm_to_affine_cnv_w1a1():
+# lfc = get_test_model_trained("CNV", 1, 1)
+# bo.export_finn_onnx(lfc, (1, 3, 32, 32), export_onnx_path)
+# model = ModelWrapper(export_onnx_path)
+# model = model.transform(InferShapes())
+# model = model.transform(FoldConstants())
+# # TODO shape inference failing on transformed model below -- needs debug
+# new_model = model.transform(BatchNormToAffine())
+# # check that there are no BN nodes left
+# # TODO replace this with execution test
+# op_types = list(map(lambda x: x.op_type, new_model.graph.node))
+# assert "BatchNormalization" not in op_types
+# os.remove(export_onnx_path)