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Make rewriters use get_tensor when needed to avoid subtle bugs #1526

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Merged
merged 3 commits into from
May 20, 2021
Merged

Make rewriters use get_tensor when needed to avoid subtle bugs #1526

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2284d0d
Make rewriters use get_tensor when needed to avoid subtle bugs
TomWildenhain-Microsoft May 19, 2021
050da94
Merge branch 'master' into tom/fix_rewriters_get_tensor
guschmue May 20, 2021
6059514
Merge branch 'master' into tom/fix_rewriters_get_tensor
guschmue May 20, 2021
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10 changes: 5 additions & 5 deletions tf2onnx/rewriter/layer_normalization_rewriter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,10 +86,10 @@ def rewrite_layer_normalization(g, ops):
match_results = list(matcher.match_ops(ops))
if match_results:
for match in match_results:
inp_node = match.get_op('input')
rank = g.get_rank(inp_node.output[0])
input_tensor = match.get_tensor('input')
rank = g.get_rank(input_tensor)
node = match.get_op('bias_add')
if inp_node.name != match.get_op('input_r2').name or inp_node.name != match.get_op('input_r3').name:
if input_tensor != match.get_tensor('input_r2') or input_tensor != match.get_tensor('input_r3'):
continue
if match.get_op('mean').name != match.get_op('mean_r2').name:
continue
Expand All @@ -105,8 +105,8 @@ def rewrite_layer_normalization(g, ops):
epsilon = match.get_op('epsilon').get_tensor_value(as_list=False).flatten().tolist()
if len(epsilon) != 1:
continue
scale = match.get_op('scale').output[0]
bias = match.get_op('bias').output[0]
scale = match.get_tensor('scale')
bias = match.get_tensor('bias')
shape = g.make_node("Shape", [inp]).output[0]
dim_2_shape = GraphBuilder(g).make_slice(
{"data": shape, "ends": [2], "starts": [1], "axes": [0]})
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15 changes: 2 additions & 13 deletions tf2onnx/rewriter/leakyrelu_rewriter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,12 +28,10 @@ def rewrite_leakyrelu(g, ops):
match_results = list(matcher.match_ops(ops))
for match in match_results:
max_node = match.get_op('max')
max_input_node = match.get_op('max_input')
mul_node = match.get_op("mul")
mul_input_node = match.get_op('mul_input')

max_input_edge_name = _find_edge_name_between_nodes(max_input_node, max_node)
mul_input_edge_name = _find_edge_name_between_nodes(mul_input_node, mul_node)
max_input_edge_name = match.get_tensor('max_input')
mul_input_edge_name = match.get_tensor('mul_input')
if max_input_edge_name == mul_input_edge_name:
alpha = match.get_op("alpha").get_tensor_value()
if alpha >= 1:
Expand All @@ -46,12 +44,3 @@ def rewrite_leakyrelu(g, ops):
g.safe_remove_nodes(to_delete)

return ops


def _find_edge_name_between_nodes(src_node, consumer_node):
# find the first edge connection between two nodes.
for consumer_end in consumer_node.input:
for src_end in src_node.output:
if consumer_end == src_end:
return consumer_end
return None
8 changes: 2 additions & 6 deletions tf2onnx/rewriter/thresholded_relu_rewriter.py
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Expand Up @@ -6,7 +6,6 @@
"""

from tf2onnx.graph_matcher import OpTypePattern, GraphMatcher
from tf2onnx.rewriter.leakyrelu_rewriter import _find_edge_name_between_nodes


# pylint: disable=missing-docstring
Expand All @@ -30,14 +29,11 @@ def rewrite_thresholded_relu(g, ops):
match_results = list(matcher.match_ops(ops))

for match in match_results:
greater_node = match.get_op('greater')
greater_input_node = match.get_op('greater_input')
mul_node = match.get_op("mul")
mul_input_node = match.get_op('mul_input')
cast_node = match.get_op('cast')

greater_input_edge_name = _find_edge_name_between_nodes(greater_input_node, greater_node)
mul_input_edge_name = _find_edge_name_between_nodes(mul_input_node, mul_node)
greater_input_edge_name = match.get_tensor('greater_input')
mul_input_edge_name = match.get_tensor('mul_input')
if greater_input_edge_name == mul_input_edge_name:
theta = match.get_op('theta').get_tensor_value()
thresholded_relu = g.make_node("ThresholdedRelu", inputs=[mul_input_edge_name], attr={"alpha": theta},
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