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Fix a 'Squeeze' related issue in symbolic_shape_infer.py (#7380)

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* Update symbolic_shape_infer.py

don't rely on static code infer in _infer_Squeeze_

* checking if dorpped axes might be =! 1

* Checking opset. Logging assumption that symbolic dimensions are unequal to 1.

* more checks
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thilow 2021-04-28 22:13:04 +02:00 committed by GitHub
parent 674915208a
commit 22d7cde725
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1 changed files with 38 additions and 1 deletions
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39
onnxruntime/python/tools/symbolic_shape_infer.py
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@ -1142,7 +1142,44 @@ class SymbolicShapeInference:
def _infer_SplitToSequence(self, node):
self._infer_Split_Common(node, helper.make_sequence_value_info)
def _infer_Squeeze(self, node):
def _infer_Squeeze(self, node):
input_shape = self._get_shape(node, 0)
op_set = get_opset(self.out_mp_)
# Depending on op-version 'axes' are provided as attribute or via 2nd input
if op_set < 13:
axes = get_attribute(node, 'axes')
assert self._try_get_value(node, 1) is None
else:
axes = self._try_get_value(node, 1)
assert get_attribute(node, 'axes') is None
if axes is None:
# No axes have been provided (neither via attribute nor via input).
# In this case the 'Shape' op should remove all axis with dimension 1.
# For symbolic dimensions we guess they are !=1.
output_shape = [s for s in input_shape if s != 1]
if self.verbose_ > 0:
symbolic_dimensions = [s for s in input_shape if type(s) != int]
if len(symbolic_dimensions) > 0:
print(f"Symbolic dimensions in input shape of op: '{node.op_type}' node: '{node.name}'. " +
f"Assuming the following dimensions are never equal to 1: {symbolic_dimensions}")
else:
axes = [handle_negative_axis(a, len(input_shape)) for a in axes]
output_shape = []
for i in range(len(input_shape)):
if i not in axes:
output_shape.append(input_shape[i])
else:
assert input_shape[i] == 1 or type(input_shape[i]) != int
if self.verbose_ > 0 and type(input_shape[i]) != int:
print(f"Symbolic dimensions in input shape of op: '{node.op_type}' node: '{node.name}'. " +
f"Assuming the dimension '{input_shape[i]}' at index {i} of the input to be equal to 1.")
vi = self.known_vi_[node.output[0]]
vi.CopyFrom(
helper.make_tensor_value_info(node.output[0], self.known_vi_[node.input[0]].type.tensor_type.elem_type,
output_shape))
self._pass_on_sympy_data(node)
def _infer_Tile(self, node):