make conv_same_pad also trigger on depthwise, varius bug fixes

Author: jmitrevs

hls4ml/backends/vivado/passes/conv_same_pad.py

@@ -1,4 +1,4 @@
-from hls4ml.model.layers import Conv1D, Conv2D, SeparableConv1D, SeparableConv2D
+from hls4ml.model.layers import Conv1D, Conv2D, DepthwiseConv1D, DepthwiseConv2D, SeparableConv1D, SeparableConv2D
 from hls4ml.model.optimizer import OptimizerPass
 
 
@@ -7,7 +7,7 @@ class InsertZeroPaddingBeforeConv1D(OptimizerPass):
 
     def match(self, node):
         is_match = (
-            isinstance(node, (Conv1D, SeparableConv1D))
+            isinstance(node, (Conv1D, DepthwiseConv1D, SeparableConv1D))
             and ((node.get_attr('padding') == 'same') or (node.get_attr('padding') == 'causal'))
             and node.get_attr('filt_width') != 1
         )
@@ -55,7 +55,7 @@ class InsertZeroPaddingBeforeConv2D(OptimizerPass):
 
     def match(self, node):
         is_match = (
-            isinstance(node, (Conv2D, SeparableConv2D))
+            isinstance(node, (Conv2D, DepthwiseConv2D, SeparableConv2D))
             and node.get_attr('padding') == 'same'
             and node.get_attr('filt_height') != 1
             and node.get_attr('filt_width') != 1

hls4ml/model/layers.py

@@ -100,7 +100,6 @@ def __init__(self, model, name, attributes, inputs, outputs=None):
 
         layer_config = self.model.config.get_layer_config(self)
         for config_key, config_value in layer_config.items():
-            print(f'{config_key=}, {config_value=}')
             config_key = convert_to_snake_case(config_key)
             if config_key in self.attributes:
                 print(
@@ -494,9 +493,9 @@ class DepthwiseConv1D(Conv1D):
         Attribute('stride_width'),
         Attribute('pad_left'),
         Attribute('pad_right'),
-        WeightAttribute('depthwise'),
+        WeightAttribute('weight'),
         WeightAttribute('bias'),
-        TypeAttribute('depthwise'),
+        TypeAttribute('weight'),
         TypeAttribute('bias'),
     ]
 

hls4ml/model/optimizer/passes/seperable_to_dw_conv.py

@@ -33,6 +33,7 @@ class SeperableToDepthwiseAndConv(OptimizerPass):
         'data_format',
         'depthwise_data',
         'depthwise_quantizer',
+        'padding',
     )
 
     _pw_attributes = ('out_width', 'n_filt', 'dilation_width', 'out_height', 'dilation_height', 'data_format', 'use_bias')

test/pytest/test_sepconv2d.py

@@ -10,7 +10,6 @@
 
 padds_options = ['same', 'valid']
 chans_options = ['channels_last']
-io_type_options = ['io_parallel', 'io_stream']
 strides_options = [(1, 1), (2, 2)]
 kernel_options = [(2, 2), (3, 3)]
 bias_options = [False]
@@ -50,7 +49,9 @@ def test_sepconv2d(chans, padds, strides, kernels, bias, io_type, backend):
     model.compile(optimizer='adam', loss='mse')
     X_input = np.random.rand(100, *input_shape)
     keras_prediction = model.predict(X_input)
-    config = hls4ml.utils.config_from_keras_model(model, default_precision='ap_fixed<32,16>')
+    config = hls4ml.utils.config_from_keras_model(
+        model, default_precision='ap_fixed<32,16>', granularity="name", backend=backend
+    )
     stride_cfg = str(strides).replace(', ', '_').replace('(', '').replace(')', '')
     kernel_cfg = str(kernels).replace(', ', '_').replace('(', '').replace(')', '')
     output_dir = str(