Create minimize_weight_bit_width.py

src/finn/transformation/fpgadataflow/minimize_weight_bit_width.py

+# Copyright (c) 2023, Xilinx
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+#
+# * Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# * Neither the name of FINN nor the names of its
+#   contributors may be used to endorse or promote products derived from
+#   this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+from qonnx.custom_op.registry import getCustomOp
+from qonnx.transformation.base import Transformation
+
+from finn.util.fpgadataflow import is_fpgadataflow_node
+
+
+class MinimizeWeightBitWidth(Transformation):
+    """For relevant nodes, call the weight bit width minimization
+    functions to save on resources. May alter tensor weightDataType
+    if the node does not have runtime writeable weights."""
+
+    def __init__(self):
+        super().__init__()
+
+    def apply(self, model):
+        for node in model.graph.node:
+            if is_fpgadataflow_node(node) is True:
+                inst = getCustomOp(node)
+                if hasattr(inst, "minimize_weight_bit_width"):
+                    inst.minimize_weight_bit_width(model)
+        return (model, False)
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