From 21e19d0241568fe3c4c68a4c56046fbf4fdf2655 Mon Sep 17 00:00:00 2001
From: Hendrik Borras <hendrikborras@web.de>
Date: Fri, 29 Oct 2021 18:04:52 +0100
Subject: [PATCH] Updated finn-base commit and moved _get_signed_from_upstream
function from finn-base to finn.
---
docker/Dockerfile.finn | 2 +-
.../qonnx/infer_quant_avg_pool_2d.py | 77 ++++++++++++++++++-
2 files changed, 76 insertions(+), 3 deletions(-)
diff --git a/docker/Dockerfile.finn b/docker/Dockerfile.finn
index 8e2d2b62f..d44f16762 100644
--- a/docker/Dockerfile.finn
+++ b/docker/Dockerfile.finn
@@ -86,7 +86,7 @@ RUN pip install -e git+https://github.com/fbcotter/dataset_loading.git@0.0.4#egg
# git-based Python repo dependencies
# these are installed in editable mode for easier co-development
-ARG FINN_BASE_COMMIT="686639de94f96f02fef794a693a295591d3f25c6"
+ARG FINN_BASE_COMMIT="901d38414c7507b1eb5a7afa76e58a4368864455"
ARG QONNX_COMMIT="6d55dce220c7f744ef23585686460b9370b672a0"
ARG FINN_EXP_COMMIT="f82c0d9868bb88ea045dfadb28508d327d287221"
ARG BREVITAS_COMMIT="5b22551871d25bf5e26917fe5900fcaa49406faf"
diff --git a/src/finn/transformation/qonnx/infer_quant_avg_pool_2d.py b/src/finn/transformation/qonnx/infer_quant_avg_pool_2d.py
index f563e885d..faad31fa0 100644
--- a/src/finn/transformation/qonnx/infer_quant_avg_pool_2d.py
+++ b/src/finn/transformation/qonnx/infer_quant_avg_pool_2d.py
@@ -30,6 +30,7 @@
import math
from onnx import TensorProto, helper
+from finn.core.datatype import DataType
from finn.custom_op.registry import getCustomOp
from finn.transformation.base import Transformation
from finn.transformation.infer_datatypes import InferDataTypes
@@ -37,6 +38,79 @@ from finn.transformation.infer_shapes import InferShapes
from finn.util.basic import get_by_name
+def _get_signed_from_upstream(model, trunc_node):
+ """
+ Find out what the sign of the input to the trunc node is,
+ by looking at the upstream nodes.
+ """
+ node = trunc_node
+ # Check if the input of this node already has a FINN datatype
+ signed = None
+ inp_dt = model.get_tensor_datatype(node.input[0])
+ if inp_dt is not None and inp_dt is not DataType["FLOAT32"]:
+ signed = inp_dt.signed()
+ # Go further up the graph, since the datatype inference works top down
+ # these nodes should either be sign preserving ops or they already have a
+ # datatype defined for the output tensor.
+ curr_node = node
+ if signed is None:
+ while curr_node is not None:
+ if model.is_join_node(curr_node):
+ raise RuntimeError(
+ "Datatype Inference for the Trunc node only supports "
+ "linear nodes in the upstream path."
+ )
+ next_node = model.find_direct_predecessors(curr_node)
+ if next_node is None:
+ raise RuntimeError(
+ "Could not infere the Datatype for the Trunc node due to "
+ "missing upstream ndoes."
+ )
+ next_node = next_node[0]
+ out_dt = model.get_tensor_datatype(next_node.output[0])
+ if out_dt is not None and out_dt is not DataType["FLOAT32"]:
+ signed = out_dt.signed()
+ break
+ # Special cases where the node has an internal or intrinsic datatype.
+ if next_node.op_type == "MultiThreshold":
+ mt_inst = getCustomOp(next_node)
+ out_dt = DataType[mt_inst.get_nodeattr("out_dtype")]
+ if out_dt is not None and out_dt is not DataType["FLOAT32"]:
+ signed = out_dt.signed()
+ break
+ if next_node.op_type == "BipolarQuant":
+ signed = True
+ break
+ if next_node.op_type == "Quant":
+ q_inst = getCustomOp(next_node)
+ out_dt = q_inst.get_integer_datatype(model)
+ if out_dt is not None and out_dt is not DataType["FLOAT32"]:
+ signed = out_dt.signed()
+ break
+
+ # Check if we are allowed to move on to the next op
+ sign_preserving_ops = ["Add", "Mul", "AveragePool", "Pad"]
+ if next_node.op_type not in sign_preserving_ops:
+ raise RuntimeError(
+ f"Could not infere the Datatype for the Trunc node, "
+ f"because the sign of the input datatype could not be infered "
+ f"from upstream nodes. And traversal further up the graph was "
+ f"disallowed, since the next node type {next_node.op_type} "
+ f"is not in the list of "
+ f"sign preserving ops {sign_preserving_ops}."
+ )
+ curr_node = next_node
+
+ if signed is None:
+ raise RuntimeError(
+ "Could not infere the Datatype for the Trunc node, "
+ "because the sign of the input datatype could not be infered "
+ "from upstream nodes."
+ )
+
+ return signed
+
+
class AvgPoolAndTruncToQuantAvgPool(Transformation):
"""
Convert a section of nodes of the pattern:
@@ -159,8 +233,7 @@ class AvgPoolAndTruncToQuantAvgPool(Transformation):
math.log(2 ** trunc_in_bits / (k_s * k_s), 2)
)
# Get sign
- t_inst = getCustomOp(t_node)
- signed = t_inst._get_signed_from_upstream(model)
+ signed = _get_signed_from_upstream(model, t_node)
# ToDo: Change this to NHWC,
# when the channels last layout comes around.
data_layout = "NCHW"
--
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