From 5abfe83f75acead8a25da63e4d96023bc8d78710 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Tue, 30 Aug 2022 21:11:44 +0200
Subject: [PATCH] [FIFO] characterize Add/DuplicateStreams, optional bypass
fix, pad
---
.../fpgadataflow/derive_characteristic.py | 33 +++++++++++++------
1 file changed, 23 insertions(+), 10 deletions(-)
diff --git a/src/finn/transformation/fpgadataflow/derive_characteristic.py b/src/finn/transformation/fpgadataflow/derive_characteristic.py
index 651462066..53540e22d 100644
--- a/src/finn/transformation/fpgadataflow/derive_characteristic.py
+++ b/src/finn/transformation/fpgadataflow/derive_characteristic.py
@@ -53,9 +53,10 @@ class DeriveCharacteristic(NodeLocalTransformation):
NodeLocalTransformation for more details.
"""
- def __init__(self, period, num_workers=None):
+ def __init__(self, period, num_workers=None, manual_bypass=False):
super().__init__(num_workers=num_workers)
self.period = period
+ self.manual_bypass = manual_bypass
def applyNodeLocal(self, node):
op_type = node.op_type
@@ -77,8 +78,6 @@ class DeriveCharacteristic(NodeLocalTransformation):
return (node, False)
# restricted to single input and output nodes for now
multistream_optypes = [
- "AddStreams_Batch",
- "DuplicateStreams_Batch",
"StreamingConcat",
]
if node.op_type in multistream_optypes:
@@ -107,9 +106,13 @@ class DeriveCharacteristic(NodeLocalTransformation):
},
"outputs": {"out": []},
}
-
- txns_in = {"in0": []}
- txns_out = {"out": []}
+ # override for certain fork/join nodes
+ if node.op_type == "DuplicateStreams_Batch":
+ del io_dict["outputs"]["out"]
+ io_dict["outputs"]["out0"] = []
+ io_dict["outputs"]["out1"] = []
+ elif node.op_type == "AddStreams_Batch":
+ io_dict["inputs"]["in1"] = [0 for i in range(n_inps)]
try:
# fill out weight stream for decoupled-mode components
@@ -123,10 +126,13 @@ class DeriveCharacteristic(NodeLocalTransformation):
io_dict["inputs"]["weights"] = [
0 for i in range(num_w_reps * n_weight_inps)
]
- txns_in["weights"] = []
except AttributeError:
pass
+ # extra dicts to keep track of cycle-by-cycle transaction behavior
+ txns_in = {key: [] for (key, value) in io_dict["inputs"].items()}
+ txns_out = {key: [] for (key, value) in io_dict["outputs"].items()}
+
def monitor_txns(sim_obj):
for inp in io_dict["inputs"]:
in_ready = _read_signal(sim, inp + sname + "TREADY") == 1
@@ -156,11 +162,15 @@ class DeriveCharacteristic(NodeLocalTransformation):
assert total_cycle_count <= self.period
# restrict to single input-output stream only for now
txns_in = txns_in["in0"]
- txns_out = txns_out["out"]
+ txns_out = txns_out[
+ "out" if node.op_type != "DuplicateStreams_Batch" else "out0"
+ ]
if len(txns_in) < self.period:
- txns_in += [0 for x in range(self.period - len(txns_in))]
+ pad_in = self.period - len(txns_in)
+ txns_in += [0 for x in range(pad_in)]
if len(txns_out) < self.period:
- txns_out += [0 for x in range(self.period - len(txns_out))]
+ pad_out = self.period - len(txns_out)
+ txns_out += [0 for x in range(pad_out)]
def accumulate_char_fxn(chrc):
p = len(chrc)
@@ -177,6 +187,7 @@ class DeriveCharacteristic(NodeLocalTransformation):
io_characteristic = txns_in + txns_out
inst.set_nodeattr("io_characteristic", io_characteristic)
inst.set_nodeattr("io_characteristic_period", self.period)
+ inst.set_nodeattr("io_characteristic_pads", [pad_in, pad_out])
except KeyError:
# exception if op_type is not supported
raise Exception(
@@ -186,6 +197,8 @@ class DeriveCharacteristic(NodeLocalTransformation):
def apply(self, model: ModelWrapper):
(model, run_again) = super().apply(model)
+ if not self.manual_bypass:
+ return (model, run_again)
# apply manual fix for DuplicateStreams and AddStreams for
# simple residual reconvergent paths with bypass
addstrm_nodes = model.get_nodes_by_op_type("AddStreams_Batch")
--
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