From f9f6f60fad59d061f9075c7ae2de4c757b121522 Mon Sep 17 00:00:00 2001
From: Hendrik Borras <hendrikborras@web.de>
Date: Fri, 8 Oct 2021 15:14:15 +0100
Subject: [PATCH] Small refactoring for QONNX activation handlers.
---
.../qonnx/qonnx_activation_handlers.py | 20 ++++++++++---------
1 file changed, 11 insertions(+), 9 deletions(-)
diff --git a/src/finn/transformation/qonnx/qonnx_activation_handlers.py b/src/finn/transformation/qonnx/qonnx_activation_handlers.py
index 1e1ad7184..02c156e14 100644
--- a/src/finn/transformation/qonnx/qonnx_activation_handlers.py
+++ b/src/finn/transformation/qonnx/qonnx_activation_handlers.py
@@ -96,7 +96,7 @@ class QuantActBaseHandler(ABC):
def _extract_output_datatype(self):
"""Get the output datatype for the MultiThreshold node."""
dtype = self._model.get_tensor_datatype(self._q_node.output[0]).name
- if "SCALED" in dtype:
+ if dtype is not None:
dtype = dtype.replace("SCALED", "")
return dtype
@@ -104,9 +104,8 @@ class QuantActBaseHandler(ABC):
"""Calculate all parameters required for replacing the QONNX style activation
with a FINN style one.
"""
- out_dtype = self._extract_output_datatype()
return {
- "out_dtype": out_dtype,
+ "out_dtype": self._extract_output_datatype(),
"thresholds": self._calculate_thresholds(),
"adder_bias": self._calculate_act_bias(),
"mul_scale": self._calculate_act_scale(),
@@ -159,9 +158,9 @@ class QuantActBaseHandler(ABC):
# If these values are scalar then they can be set as attributes
# of the MultiThreshold node, if not they get inserted as adder and mul nodes
# behind the MultiTrheshold nodes.
- bias_compatible = adder_bias.shape == (1,) or len(adder_bias.shape) == 0
- scale_compatible = mul_scale.shape == (1,) or len(mul_scale.shape) == 0
- if scale_compatible and bias_compatible and True:
+ bias_scalar = adder_bias.shape == (1,) or len(adder_bias.shape) == 0
+ scale_scalar = mul_scale.shape == (1,) or len(mul_scale.shape) == 0
+ if scale_scalar and bias_scalar and True:
# Get Quant parameters
mul_scale = np.atleast_1d(mul_scale)
# ONNX only accepts 64bit floats as attributes
@@ -184,7 +183,7 @@ class QuantActBaseHandler(ABC):
# Set bias
zero_bias = False
- if bias_compatible:
+ if bias_scalar:
adder_bias = np.atleast_1d(adder_bias)
# ONNX only accepts 64bit floats as attributes
adder_bias = adder_bias.astype(dtype=np.float64)[0]
@@ -228,7 +227,7 @@ class QuantActBaseHandler(ABC):
# Set scale
# Insert Mul node
unity_scale = False
- if scale_compatible:
+ if scale_scalar:
mul_scale = np.atleast_1d(mul_scale)
mul_scale = mul_scale.astype(dtype=np.float64)[0]
mul_shape = tuple()
@@ -369,7 +368,10 @@ class QuantReluHandler(QuantActBaseHandler):
class QuantIdentityHandler(QuantActBaseHandler):
"""Class for converting a quantized identity operation expressed in the QONNX
- dialect to the FINN ONNX dialect."""
+ dialect to the FINN ONNX dialect.
+ This handler also takes care of quantized HardTanh activations, because
+ these are equivalent to quantized identity activations.
+ """
valid_predecessor_op_types = [
"BatchNormalization",
--
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