From 21a6eaeed229fa4aaf923679d00a175ec185949c Mon Sep 17 00:00:00 2001
From: HamzaEzzRa <hamzaezzaouirahali@gmail.com>
Date: Tue, 11 Aug 2026 22:25:22 -0400
Subject: [PATCH] fix(vivado): Derive softmax layer config name from activation
 attribute

---
 .../backends/vivado/passes/core_templates.py   |  2 +-
 test/pytest/test_softmax.py                    | 18 ++++++++++++++----
 2 files changed, 15 insertions(+), 5 deletions(-)

diff --git a/hls4ml/backends/vivado/passes/core_templates.py b/hls4ml/backends/vivado/passes/core_templates.py
index 755eb6de44..777a435ab0 100644
--- a/hls4ml/backends/vivado/passes/core_templates.py
+++ b/hls4ml/backends/vivado/passes/core_templates.py
@@ -347,7 +347,7 @@ def format(self, node):
         use_multidim = node.get_attr('n_inner', 1) > 1 or node.get_attr('n_outer', 1) > 1
         use_multidim = use_multidim and node.model.config.get_config_value('IOType') == 'io_parallel'
         params['activation'] = 'softmax' if not use_multidim else 'softmax_multidim'
-        params['config'] = f'softmax_config{node.index}'
+        params['config'] = '{}_config{}'.format(node.get_attr('activation'), node.index)
 
         return self.template.format(**params)
 
diff --git a/test/pytest/test_softmax.py b/test/pytest/test_softmax.py
index 418f64b558..894d8bc4f0 100644
--- a/test/pytest/test_softmax.py
+++ b/test/pytest/test_softmax.py
@@ -19,6 +19,7 @@ def generate_data(input_shape):
     return np.clip(d, -32, 31)
 
 
+@pytest.mark.parametrize('softmax_impl', ['activation', 'standalone'])
 @pytest.mark.parametrize('backend', ['Vivado', 'Vitis', 'Quartus', 'Catapult'])
 @pytest.mark.parametrize('strategy', ['stable', 'latency', 'argmax'])
 @pytest.mark.parametrize(
@@ -35,10 +36,15 @@ def generate_data(input_shape):
         ('16,6', (8, 8, 3), '18,8', 'io_stream', False),
     ],
 )
-def test_softmax(test_case_id, backend, strategy, generate_data, input_bits, input_shape, table_bits, io_type, custom_accum):
+def test_softmax(
+    test_case_id, softmax_impl, backend, strategy, generate_data, input_bits, input_shape, table_bits, io_type, custom_accum
+):
     X = generate_data
     model = tf.keras.models.Sequential()
-    model.add(tf.keras.layers.Activation(input_shape=input_shape, activation='softmax', name='softmax'))
+    if softmax_impl == 'activation':
+        model.add(tf.keras.layers.Activation(input_shape=input_shape, activation='softmax', name='softmax'))
+    else:
+        model.add(tf.keras.layers.Softmax(input_shape=input_shape, name='softmax'))
     model.compile()
 
     table_type = f'fixed<{table_bits}, RND, SAT>'
@@ -73,12 +79,16 @@ def test_softmax(test_case_id, backend, strategy, generate_data, input_bits, inp
     assert acc_hls4ml >= 0.98
 
 
+@pytest.mark.parametrize('softmax_impl', ['activation', 'standalone'])
 @pytest.mark.parametrize('backend', ['Vivado', 'Vitis', 'Quartus', 'Catapult'])
 @pytest.mark.parametrize('io_type', ['io_parallel', 'io_stream'])
-def test_softmax_skipped(test_case_id, backend, io_type):
+def test_softmax_skipped(test_case_id, softmax_impl, backend, io_type):
     X = np.random.rand(100, 10)
     dense = tf.keras.layers.Dense(14, input_shape=(10,), name='dense')
-    softmax = tf.keras.layers.Activation(activation='softmax', name='softmax')
+    if softmax_impl == 'activation':
+        softmax = tf.keras.layers.Activation(activation='softmax', name='softmax')
+    else:
+        softmax = tf.keras.layers.Softmax(name='softmax')
     model = tf.keras.models.Sequential([dense, softmax])
     model.compile()