From cb18a1b87c76d1c01901c6ccb6f8af93261cdc7b Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Wed, 14 Oct 2020 01:27:04 +0200
Subject: [PATCH] [Test] test runtime writes for weights, now passing
---
tests/fpgadataflow/test_runtime_weights.py | 33 ++++++++--------------
1 file changed, 11 insertions(+), 22 deletions(-)
diff --git a/tests/fpgadataflow/test_runtime_weights.py b/tests/fpgadataflow/test_runtime_weights.py
index 807483cd1..1c7d66231 100644
--- a/tests/fpgadataflow/test_runtime_weights.py
+++ b/tests/fpgadataflow/test_runtime_weights.py
@@ -36,14 +36,15 @@ from finn.transformation.fpgadataflow.prepare_rtlsim import PrepareRTLSim
from finn.custom_op.registry import getCustomOp
from finn.core.rtlsim_exec import rtlsim_exec
from finn.util.basic import gen_finn_dt_tensor
-from finn.util.pyverilator import axilite_read, axilite_write
+from finn.util.pyverilator import axilite_write
import numpy as np
-import os
+import pytest
test_fpga_part = "xc7z020clg400-1"
target_clk_ns = 5
+@pytest.mark.vivado
def test_runtime_weights_single_layer():
idt = DataType.UINT32
wdt = DataType.UINT8
@@ -67,32 +68,18 @@ def test_runtime_weights_single_layer():
op_inst = getCustomOp(fcl)
op_inst.set_nodeattr("mem_mode", "decoupled")
op_inst.set_nodeattr("runtime_writeable_weights", 1)
- model.set_initializer("W_0", np.eye(mh).astype(np.float32))
model = model.transform(GiveUniqueNodeNames())
model = model.transform(PrepareIP(test_fpga_part, target_clk_ns))
model = model.transform(HLSSynthIP())
model = model.transform(CreateStitchedIP(test_fpga_part, target_clk_ns))
model = model.transform(PrepareRTLSim())
model.set_metadata_prop("exec_mode", "rtlsim")
- os.environ["RTLSIM_TRACE_DEPTH"] = "5"
- model.set_metadata_prop("rtlsim_trace", "trace.vcd")
- in_tensor = np.asarray(range(mw), dtype=np.float32).reshape(1, mw)
+ in_tensor = np.asarray(range(mw), dtype=np.float32)
+ # add two copies of the input tensor as the first one is just used to
+ # "flush out" the pipeline (as mvau already starts receiving old weights while
+ # we write new ones)
+ in_tensor = np.tile(in_tensor, (2, 1))
exec_ctx = {"act_0": in_tensor}
- extracted_weights = np.zeros((mh, mw))
-
- def read_weights(sim):
- addr = 0
- for w in range(mw):
- for h in range(mh):
- extracted_weights[h, w] = axilite_read(
- sim, addr, basename="s_axilite_0_"
- )
- addr += 4
-
- rtlsim_exec(model, exec_ctx, pre_hook=read_weights)
- assert (extracted_weights == model.get_initializer("W_0")).all()
- y = exec_ctx["act_1"]
- assert (y == np.dot(in_tensor, extracted_weights.T)).all()
new_weights = gen_finn_dt_tensor(wdt, (mh, mw))
def write_weights(sim):
@@ -104,4 +91,6 @@ def test_runtime_weights_single_layer():
rtlsim_exec(model, exec_ctx, pre_hook=write_weights)
y = exec_ctx["act_1"]
- assert (y == np.dot(in_tensor, new_weights.T)).all()
+ # only use second batch element in output; first will be invalid due to
+ # old weights (see above)
+ assert (y[1] == np.dot(in_tensor[1], new_weights)).all()
--
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