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Delete tensor initializer #165

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merged 3 commits into from
Dec 20, 2024
Merged

Delete tensor initializer #165

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e5bb71c
Addded del_initializer to modelwrapper.
Aug 23, 2024
5269aa6
[Test] factor out ModelWrapper init get/set tests, add init rm test
maltanar Dec 20, 2024
504c14e
[Core] refactor ModelWrapper.del_initializer to use get_by_name
maltanar Dec 20, 2024
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7 changes: 7 additions & 0 deletions src/qonnx/core/modelwrapper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -367,6 +367,13 @@ def get_initializer(self, tensor_name, return_dtype=False):
else:
return None

def del_initializer(self, initializer_name):
"""Deletes an initializer from the model."""
graph = self._model_proto.graph
init = util.get_by_name(graph.initializer, initializer_name)
if not (init is None):
graph.initializer.remove(init)

def find_producer(self, tensor_name):
"""Finds and returns the node that produces the tensor with given name."""
for x in self._model_proto.graph.node:
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20 changes: 15 additions & 5 deletions tests/core/test_modelwrapper.py
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Expand Up @@ -54,11 +54,6 @@ def test_modelwrapper():
assert first_conv_iname != "" and (first_conv_iname is not None)
assert first_conv_wname != "" and (first_conv_wname is not None)
assert first_conv_oname != "" and (first_conv_oname is not None)
first_conv_weights = model.get_initializer(first_conv_wname)
assert first_conv_weights.shape == (8, 1, 5, 5)
first_conv_weights_rand = np.random.randn(8, 1, 5, 5)
model.set_initializer(first_conv_wname, first_conv_weights_rand)
assert (model.get_initializer(first_conv_wname) == first_conv_weights_rand).all()
inp_cons = model.find_consumer(first_conv_iname)
assert inp_cons == first_conv
out_prod = model.find_producer(first_conv_oname)
Expand All @@ -75,6 +70,21 @@ def test_modelwrapper():
assert model.get_tensor_sparsity(first_conv_iname) == inp_sparsity


def test_modelwrapper_set_get_rm_initializer():
raw_m = get_data("qonnx.data", "onnx/mnist-conv/model.onnx")
model = ModelWrapper(raw_m)
conv_nodes = model.get_nodes_by_op_type("Conv")
first_conv = conv_nodes[0]
first_conv_wname = first_conv.input[1]
first_conv_weights = model.get_initializer(first_conv_wname)
assert first_conv_weights.shape == (8, 1, 5, 5)
first_conv_weights_rand = np.random.randn(8, 1, 5, 5)
model.set_initializer(first_conv_wname, first_conv_weights_rand)
assert (model.get_initializer(first_conv_wname) == first_conv_weights_rand).all()
model.del_initializer(first_conv_wname)
assert model.get_initializer(first_conv_wname) is None


def test_modelwrapper_graph_order():
# create small network with properties to be tested
Neg_node = onnx.helper.make_node("Neg", inputs=["in1"], outputs=["neg1"])
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