Merge branch 'main' into torch-profiler

fastmachinelearning · Jan 10, 2025 · f49c831 · f49c831
2 parents d1a6b35 + 3fa2902
commit f49c831
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Showing 5 changed files with 11 additions and 4 deletions.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -30,7 +30,7 @@ repos:
     args: ["--profile", "black", --line-length=125]
 
 - repo: https://github.com/asottile/pyupgrade
-  rev: v3.19.0
+  rev: v3.19.1
   hooks:
   - id: pyupgrade
     args: ["--py36-plus"]

diff --git a/hls4ml/model/optimizer/passes/convert_to_channels_last.py b/hls4ml/model/optimizer/passes/convert_to_channels_last.py
@@ -97,12 +97,17 @@ def transform(self, model, node):
             if (
                 isinstance(node, Reshape)
                 and len(node.attributes['target_shape']) == 1
-                and not model.config.config['HLSConfig']['Model']['ChannelsLastConversion'] == "internal"
+                and not model.config.config['HLSConfig']['Model']['ChannelsLastConversion'] == "off"
             ):
                 previous_node = node.get_input_node(node.inputs[0])
                 input = previous_node.name
                 outshape = previous_node.get_output_variable().shape
 
+                if (model.config.config['IOType'] == 'io_stream') and len(outshape) == 3:
+                    raise Exception(
+                        'No 3D transpose available in io_stream, this model cannot be converted to channels-last'
+                    )
+
                 if len(outshape) == 2:
                     attributes = {'perm': [1, 0]}
                 else:

diff --git a/hls4ml/utils/config.py b/hls4ml/utils/config.py
@@ -283,7 +283,7 @@ def config_from_pytorch_model(
     default_precision='ap_fixed<16,6>',
     default_reuse_factor=1,
     channels_last_conversion='full',
-    transpose_outputs=True,
+    transpose_outputs=False,
     max_precision=None,
 ):
     """Create an HLS conversion config given the PyTorch model.

diff --git a/hls4ml/writer/vivado_accelerator_writer.py b/hls4ml/writer/vivado_accelerator_writer.py
@@ -394,6 +394,8 @@ def write_board_script(self, model):
         f.write('set clock_uncertainty {}\n'.format(model.config.get_config_value('ClockUncertainty', '12.5%')))
         f.write('variable version\n')
         f.write('set version "{}"\n'.format(model.config.get_config_value('Version', '1.0.0')))
+        f.write('variable maximum_size\n')
+        f.write('set maximum_size {}\n'.format(model.config.get_config_value('MaximumSize', '4096')))
         if self.vivado_accelerator_config.get_interface() == 'axi_stream':
             in_bit, out_bit = self.vivado_accelerator_config.get_io_bitwidth()
             f.write(f'set bit_width_hls_output {in_bit}\n')

diff --git a/test/pytest/test_pytorch_api.py b/test/pytest/test_pytorch_api.py
@@ -498,7 +498,7 @@ def test_pooling(pooling, padds, backend):
     model.eval()
     pytorch_prediction = model(torch.Tensor(X_input)).detach().numpy()
 
-    config = config_from_pytorch_model(model, input_shape_forHLS)
+    config = config_from_pytorch_model(model, input_shape_forHLS, transpose_outputs=True)
     output_dir = str(test_root_path / f'hls4mlprj_pytorch_api_pooling_{pooling.__name__}_padds_{padds}_backend_{backend}')
     hls_model = convert_from_pytorch_model(model, hls_config=config, output_dir=output_dir, backend=backend)
     hls_model.compile()