From fcc457e5a020694329ca8da67e43043c77d43253 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Fri, 22 Nov 2019 19:09:52 +0000
Subject: [PATCH] [Transform] reiterated fixes for AbsorbAdd/Mul
---
src/finn/transformation/streamline/absorb.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/src/finn/transformation/streamline/absorb.py b/src/finn/transformation/streamline/absorb.py
index 0a0c8e301..6806137e0 100644
--- a/src/finn/transformation/streamline/absorb.py
+++ b/src/finn/transformation/streamline/absorb.py
@@ -26,8 +26,8 @@ class AbsorbAddIntoMultiThreshold(Transformation):
assert T is not None
start_name = n.input[0]
# we can only absorb 0d or 1d adds
- is_scalar = all(x == 1 for x in A.shape)
- is_1d = np.prod(A.shape) == A.shape[-1]
+ is_scalar = A.ndim == 0 or all(x == 1 for x in A.shape)
+ is_1d = A.ndim > 0 and np.prod(A.shape) == A.shape[-1]
if is_scalar or is_1d:
Tnew = T - A.reshape(-1, 1)
# Tnew = T - A.reshape(-1, T.shape[1])
@@ -56,8 +56,8 @@ class AbsorbMulIntoMultiThreshold(Transformation):
A = model.get_initializer(mul_weight_name)
assert A is not None
is_signed = (A < 0).any()
- is_scalar = np.prod(A.shape) == 1
- is_1d = len(A.shape) == 2 and A.shape[0] == 1
+ is_scalar = A.ndim == 0 or all(x == 1 for x in A.shape)
+ is_1d = A.ndim > 0 and np.prod(A.shape) == A.shape[-1]
consumer = model.find_consumer(n.output[0])
if consumer is not None and consumer.op_type == "MultiThreshold":
if not is_signed and (is_1d or is_scalar):
@@ -66,7 +66,7 @@ class AbsorbMulIntoMultiThreshold(Transformation):
assert T is not None
start_name = n.input[0]
# compute new thresholds and set initializer
- Tnew = T / A.reshape(-1, T.shape[1])
+ Tnew = T / A.reshape(-1, 1)
# TODO: need to handle negative A values correctly; produce
# mul sign mask and merge into preceding matmul?
model.set_initializer(threshold_name, Tnew)
--
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