From b58419f25d1958fd51e294a0bcad38a835d8750a Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Fri, 18 Sep 2020 12:46:22 +0200
Subject: [PATCH] [Test] save end2end key results to txtfiles
---
tests/end2end/test_end2end_bnn_pynq.py | 49 +++++++++++++++++++++-----
1 file changed, 40 insertions(+), 9 deletions(-)
diff --git a/tests/end2end/test_end2end_bnn_pynq.py b/tests/end2end/test_end2end_bnn_pynq.py
index 33ba552f4..23286444e 100644
--- a/tests/end2end/test_end2end_bnn_pynq.py
+++ b/tests/end2end/test_end2end_bnn_pynq.py
@@ -93,6 +93,7 @@ from finn.transformation.merge_onnx_models import MergeONNXModels
from finn.transformation.insert_topk import InsertTopK
from finn.core.datatype import DataType
from dataset_loading import mnist, cifar
+from datetime import datetime
build_dir = "/tmp/" + os.environ["FINN_INST_NAME"]
target_clk_ns = 10
@@ -104,6 +105,18 @@ def get_checkpoint_name(topology, wbits, abits, step):
return build_dir + "/end2end_%s_w%da%d_%s.onnx" % (topology, wbits, abits, step)
+def update_dashboard_data(topology, wbits, abits, key, val):
+ stats_file = build_dir + "/end2end_%s_w%da%d.txt" % (topology, wbits, abits)
+ stats_dict = dict()
+ if os.path.isfile(stats_file):
+ with open(stats_file, "r") as f:
+ stats_dict_txt = f.read()
+ stats_dict = eval(stats_dict_txt)
+ stats_dict[key] = val
+ with open(stats_file, "w") as f:
+ f.write(str(stats_dict))
+
+
def fold_tfc(model):
fc_layers = model.get_nodes_by_op_type("StreamingFCLayer_Batch")
# (PE, SIMD, in_fifo_depth, out_fifo_depth, ramstyle) for each layer
@@ -275,6 +288,8 @@ class TestEnd2End:
(model, ishape) = get_trained_network_and_ishape(topology, wbits, abits)
chkpt_name = get_checkpoint_name(topology, wbits, abits, "export")
bo.export_finn_onnx(model, ishape, chkpt_name)
+ dtstr = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+ update_dashboard_data(topology, wbits, abits, "datetime", dtstr)
assert os.path.isfile(chkpt_name)
def test_import_and_tidy(self, topology, wbits, abits):
@@ -450,7 +465,9 @@ class TestEnd2End:
y = execute_parent(parent_chkpt, rtlsim_chkpt, input_tensor_npy)
model = ModelWrapper(rtlsim_chkpt)
perf["cycles_rtlsim"] = model.get_metadata_prop("cycles_rtlsim")
- warnings.warn("Estimated & rtlsim performance: " + str(perf))
+ # warnings.warn("Estimated & rtlsim performance: " + str(perf))
+ for (k, v) in perf.items():
+ update_dashboard_data(topology, wbits, abits, k, v)
assert np.isclose(y, output_tensor_npy).all()
@pytest.mark.slow
@@ -502,14 +519,17 @@ class TestEnd2End:
cfg = get_build_env(kind, target_clk_ns)
model = model.transform(cfg["build_fxn"])
model = model.transform(AnnotateResources("synth"))
- warnings.warn(
- "Post-synthesis resources (excluding shell): "
- + model.get_metadata_prop("res_total_synth")
- )
- warnings.warn(
- "Post-synthesis resources (all inclusive): "
- + model.get_metadata_prop("res_total_top_synth")
- )
+ # warnings.warn(
+ # "Post-synthesis resources (excluding shell): "
+ # + model.get_metadata_prop("res_total_synth")
+ # )
+ # warnings.warn(
+ # "Post-synthesis resources (all inclusive): "
+ # + model.get_metadata_prop("res_total_top_synth")
+ # )
+ synth_dct = eval(model.get_metadata_prop("res_total_top_synth"))
+ for (k, v) in synth_dct.items():
+ update_dashboard_data(topology, wbits, abits, k, v)
model.save(get_checkpoint_name(topology, wbits, abits, "build_" + kind))
@pytest.mark.parametrize("kind", ["zynq", "alveo"])
@@ -599,3 +619,14 @@ class TestEnd2End:
)
ret_str += "\n" + "-----------------------------"
warnings.warn(ret_str)
+ largest_bsize = bsize_range[-1]
+ update_dashboard_data(
+ topology, wbits, abits, "fclk[mhz]", ret[largest_bsize]["fclk[mhz]"]
+ )
+ update_dashboard_data(
+ topology,
+ wbits,
+ abits,
+ "throughput[images/s]",
+ ret[largest_bsize]["throughput[images/s]"],
+ )
--
GitLab