From d77dd7fe0de8fe473cd04d76ddde1877967a8c14 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Tue, 10 Mar 2020 18:17:29 +0000
Subject: [PATCH] [Streamline] better 1d checking for absorbption
---
src/finn/transformation/streamline/absorb.py | 9 ++++++---
1 file changed, 6 insertions(+), 3 deletions(-)
diff --git a/src/finn/transformation/streamline/absorb.py b/src/finn/transformation/streamline/absorb.py
index 5a9355bcf..68e013a6d 100644
--- a/src/finn/transformation/streamline/absorb.py
+++ b/src/finn/transformation/streamline/absorb.py
@@ -55,7 +55,8 @@ class AbsorbAddIntoMultiThreshold(Transformation):
start_name = n.input[0]
# we can only absorb 0d or 1d adds
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]
+ actual_ndims = len(tuple(filter(lambda x: x > 1, A.shape)))
+ is_1d = actual_ndims == 1
if is_scalar or is_1d:
Tnew = T - A.reshape(-1, 1)
# Tnew = T - A.reshape(-1, T.shape[1])
@@ -85,7 +86,8 @@ class AbsorbMulIntoMultiThreshold(Transformation):
assert A is not None, "Initializer for mul weights is not set."
is_signed = (A < 0).any()
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]
+ actual_ndims = len(tuple(filter(lambda x: x > 1, A.shape)))
+ is_1d = actual_ndims == 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):
@@ -122,7 +124,8 @@ class FactorOutMulSignMagnitude(Transformation):
A = model.get_initializer(mul_weight_name)
assert A is not None, "Initializer for mul weights is not set."
is_scalar = np.prod(A.shape) == 1
- is_1d = len(A.shape) == 2 and A.shape[0] == 1
+ actual_ndims = len(tuple(filter(lambda x: x > 1, A.shape)))
+ is_1d = actual_ndims == 1
is_not_bipolar = (
model.get_tensor_datatype(mul_weight_name) != DataType.BIPOLAR
)
--
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