From 188b6ac5709ef14d13d64b6eb498c0f42d73c6b2 Mon Sep 17 00:00:00 2001
From: Tobi-Alonso <tobi.alonso@gmail.com>
Date: Tue, 19 May 2020 16:10:19 +0100
Subject: [PATCH] [TRANSFORM] Generalize from past scalar to past any linear op
(this was supported, but restricted). Fix node sorting problem, by iterating
over a copy list of the node instead of iteration over graph.node. Fix corner
case when both branches are empty and come from the same node
---
src/finn/transformation/streamline/reorder.py | 22 +++++++++----------
1 file changed, 10 insertions(+), 12 deletions(-)
diff --git a/src/finn/transformation/streamline/reorder.py b/src/finn/transformation/streamline/reorder.py
index 96046602e..1886c7857 100644
--- a/src/finn/transformation/streamline/reorder.py
+++ b/src/finn/transformation/streamline/reorder.py
@@ -34,8 +34,6 @@ from finn.transformation.infer_shapes import InferShapes
from finn.core.onnx_exec import execute_node
from finn.util.basic import get_by_name
-def is_scalar(x):
- return np.prod(x.shape) == 1
class MoveAddPastMul(Transformation):
"""Move add operations past multiply operations. The aim is to have them
@@ -273,12 +271,12 @@ class MoveScalarMulPastConv(Transformation):
return (model, graph_modified)
-class MoveScalarLinearPastEltwiseAdd(Transformation):
- """Move scalar linear operations (mul, add) past elementwise add operations where possible. Specifically,
- matches and transforms the following patterns:
+class MoveLinearPastEltwiseAdd(Transformation):
+ """Move linear operations (mul, add) past elementwise add operations where possible.
+ Specifically,matches and transforms the following patterns:
(x*C) + (y*C) -> (x + y) * C
(x+A) + (y+B) -> (x + y) + (A + B)
- where x and y are dynamic inputs, A, B, C are constants.
+ where x and y are dynamic inputs, A, B, C are constant tensors (in general).
"""
def move_node(self, graph, n, prod0, prod1, node_ind):
@@ -305,7 +303,8 @@ class MoveScalarLinearPastEltwiseAdd(Transformation):
graph = model.graph
node_ind = 0
graph_modified = False
- for n in graph.node:
+ nodes = [n for n in graph.node]
+ for n in nodes:
node_ind += 1
if n.op_type == "Add":
# check for tensors on both inputs (eltwise add)
@@ -321,17 +320,16 @@ class MoveScalarLinearPastEltwiseAdd(Transformation):
# check for mul with same initializer on both inputs
prod0 = model.find_producer(in0)
prod1 = model.find_producer(in1)
- if prod0 is None or prod1 is None:
+ # Also check case when both branches are empty and come
+ # from the same node: (prod0 == prod1)
+ # Other transform should handle that
+ if prod0 is None or prod1 is None or (prod0 == prod1):
continue
init0 = model.get_initializer(prod0.input[1])
init1 = model.get_initializer(prod1.input[1])
# if either initializer is None, skip
if init0 is None or init1 is None:
continue
- # if either initializer is non-scalar, skip
- # TODO relax this to 1D tensors?
- if (not is_scalar(init0)) or (not is_scalar(init1)):
- continue
if prod0.op_type == "Mul" and prod1.op_type == "Mul":
if np.array_equal(init0, init1):
self.move_node(graph, n, prod0, prod1, node_ind)
--
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