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-rw-r--r--ethosu/vela/tflite_supported_operators.py11
1 files changed, 1 insertions, 10 deletions
diff --git a/ethosu/vela/tflite_supported_operators.py b/ethosu/vela/tflite_supported_operators.py
index ada2136..48813fe 100644
--- a/ethosu/vela/tflite_supported_operators.py
+++ b/ethosu/vela/tflite_supported_operators.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
+# SPDX-FileCopyrightText: Copyright 2020-2024 Arm Limited and/or its affiliates <open-source-office@arm.com>
#
# SPDX-License-Identifier: Apache-2.0
#
@@ -58,7 +58,6 @@ class TFLiteSupportedOperators:
depthwise_convolution_ops = set((Op.DepthwiseConv2DBias,))
transpose_convolution_ops = set((Op.Conv2DBackpropInput,))
convolution_like_ops = convolution_ops | depthwise_convolution_ops | transpose_convolution_ops
- conv_depth_fc_op = convolution_ops | depthwise_convolution_ops | set((Op.FullyConnected,))
max_pooling_ops = Op.op_set(Op.is_maxpool_op)
avg_pooling_ops = Op.op_set(Op.is_avgpool_op)
pooling_ops = set((Op.ReduceSum,)) | max_pooling_ops | avg_pooling_ops
@@ -239,8 +238,6 @@ class TFLiteSupportedOperators:
self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_bias_shape)
self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_bias_type)
self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_bias_40bit)
- for op_type in TFLiteSupportedOperators.conv_depth_fc_op:
- self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_no_quantized_bias_type)
# Transpose Conv specific checks:
for op_type in TFLiteSupportedOperators.transpose_convolution_ops:
self.specific_constraints[op_type].append(TFLiteSupportedOperators.constraint_tconv_stride)
@@ -534,12 +531,6 @@ class TFLiteSupportedOperators:
return valid, f"Tensor '{bias.name}' has values larger than 40-bits"
return True, "Op has no bias tensor, or it fits in 40-bit"
- def constraint_no_quantized_bias_type(op):
- "Attribute quantized_bias_type must not be set"
- quantized_bias_type = op.attrs.get("quantized_bias_type", False)
- valid = quantized_bias_type == 0
- return valid, f"Op has quantized_bias_type={quantized_bias_type}"
-
@staticmethod
def constraint_batch_size(op):
"IFM Tensor batch size must be 1"