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Fixed a bug in the optimization process for arithmetic operations #686

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merged 1 commit into from
Sep 1, 2024
Merged

Fixed a bug in the optimization process for arithmetic operations #686

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4 changes: 2 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -299,15 +299,15 @@ Video speed is adjusted approximately 50 times slower than actual speed.
docker run --rm -it \
-v `pwd`:/workdir \
-w /workdir \
ghcr.io/pinto0309/onnx2tf:1.25.8
ghcr.io/pinto0309/onnx2tf:1.25.9

or

# Authentication is not required for pulls from Docker Hub.
docker run --rm -it \
-v `pwd`:/workdir \
-w /workdir \
docker.io/pinto0309/onnx2tf:1.25.8
docker.io/pinto0309/onnx2tf:1.25.9

or

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2 changes: 1 addition & 1 deletion onnx2tf/__init__.py
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@@ -1,3 +1,3 @@
from onnx2tf.onnx2tf import convert, main

__version__ = '1.25.8'
__version__ = '1.25.9'
21 changes: 14 additions & 7 deletions onnx2tf/utils/common_functions.py
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Expand Up @@ -5202,7 +5202,19 @@ def merge_two_consecutive_identical_ops_into_one(
tf_type = tf.math.divide

elif tf_func == 'Sub':
if (
if isinstance(input_tensor_1, np.ndarray) or hasattr(input_tensor_1, 'numpy'):
tf_layers_dict[graph_node_output.name]['tf_node'] = \
tf.math.subtract(
x=input_tensor_1 \
if not isinstance(input_tensor_1, np.ndarray) \
else tf.convert_to_tensor(input_tensor_1),
y=input_tensor_2 \
if not isinstance(input_tensor_2, np.ndarray) \
else tf.convert_to_tensor(input_tensor_2),
name=graph_node.name,
)
tf_type = tf.math.subtract
elif (
not isinstance(graph_node_input_1, np.ndarray) \
and 'merge_sub' in tf_layers_dict[graph_node_input_1.name] \
and tf_layers_dict[graph_node_input_1.name]['merge_sub']
Expand Down Expand Up @@ -5411,12 +5423,7 @@ def merge_two_consecutive_identical_ops_into_one(
elif next_graph_node_o_op == 'Sub':
# 8. `Add` -> `Sub` to `Single-Add` : `10 + 5 - 8 -> 10 - 3`
if isinstance(next_graph_node_input_1, np.ndarray) or hasattr(next_graph_node_input_1, 'numpy'):
if isinstance(input_tensor_1, np.ndarray) or hasattr(input_tensor_1, 'numpy'):
input_tensor_1 = (input_tensor_1 - next_graph_node_input_1)
elif isinstance(input_tensor_2, np.ndarray) or hasattr(input_tensor_2, 'numpy'):
input_tensor_2 = (input_tensor_2 - next_graph_node_input_1)
tf_layers_dict[graph_node_output.name]['merge_add'] = True
tf_type = tf.identity
tf_type = tf.math.add
elif isinstance(next_graph_node_input_2, np.ndarray) or hasattr(next_graph_node_input_2, 'numpy'):
if isinstance(input_tensor_1, np.ndarray) or hasattr(input_tensor_1, 'numpy'):
input_tensor_1 = (input_tensor_1 - next_graph_node_input_2)
Expand Down
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