Fix activation in matmul sub (sony#884)

1. Fix MatMul->Dense substitution to include an activation attribute 2. Add warning to ActivationDecomposition substitution if node's activation attribute is missing
reuvenperetz · Dec 10, 2023 · 0eac225 · 0eac225
1 parent fd740d2
commit 0eac225
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Showing 2 changed files with 8 additions and 2 deletions.
diff --git a/...pression_toolkit/core/keras/graph_substitutions/substitutions/activation_decomposition.py b/...pression_toolkit/core/keras/graph_substitutions/substitutions/activation_decomposition.py
@@ -16,6 +16,7 @@
 
 from tensorflow.keras.layers import Dense, DepthwiseConv2D, Conv2D, Conv2DTranspose, Activation, SeparableConv2D
 
+from model_compression_toolkit.logger import Logger
 from model_compression_toolkit.core import common
 from model_compression_toolkit.constants import FLOAT_32, DATA_TYPE
 from model_compression_toolkit.core.common.graph.base_graph import Graph
@@ -62,6 +63,11 @@ def substitute(self,
             Graph after applying the substitution.
         """
 
+        if ACTIVATION not in op2d_node.framework_attr:
+            Logger.warning(f'Op2d node {op2d_node.name} of type {op2d_node.type} is missing an "{ACTIVATION}"'
+                           f' attribute -> Skipping substitution ActivationDecomposition')  # pragma: no cover
+            return graph
+
         activation_node_name = op2d_node.name + '_post_activation'
 
         activation_fw_attr = {

diff --git a/...l_compression_toolkit/core/keras/graph_substitutions/substitutions/matmul_substitution.py b/...l_compression_toolkit/core/keras/graph_substitutions/substitutions/matmul_substitution.py
@@ -22,7 +22,7 @@
 from model_compression_toolkit.core.common.graph.base_node import BaseNode
 from model_compression_toolkit.core.common.graph.functional_node import FunctionalNode
 from model_compression_toolkit.core.keras.constants import TRANSPOSE_A, TRANSPOSE_B, \
-    ADJOINT_A, ADJOINT_B, UNITS, USE_BIAS, KERNEL
+    ADJOINT_A, ADJOINT_B, UNITS, USE_BIAS, KERNEL, ACTIVATION, LINEAR
 
 
 class MatmulToDenseSubstitution(common.BaseSubstitution):
@@ -89,7 +89,7 @@ def substitute(self,
             w = w.transpose()
 
         dense_node = BaseNode(matmul_node.name,
-                              {UNITS: w.shape[1], USE_BIAS: False},
+                              {UNITS: w.shape[1], USE_BIAS: False, ACTIVATION: LINEAR},
                               matmul_node.input_shape, matmul_node.output_shape,
                               {KERNEL: w}, tf.keras.layers.Dense,
                               reuse=matmul_node.reuse, reuse_group=matmul_node.reuse_group)