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60d606094c
Summary: Exporting meshgrid op in opset 9 symbolics Pull Request resolved: https://github.com/pytorch/pytorch/pull/26037 Reviewed By: hl475 Differential Revision: D17452325 Pulled By: houseroad fbshipit-source-id: d556b78e46594a232cdefd8c257cccd8b98221d6
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
from torch.onnx.symbolic_helper import _black_list_in_opset
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import torch.onnx.symbolic_opset9 as sym_opset9
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import warnings
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# Note [ONNX operators that are added/updated from opset 7 to opset 8]
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# New operators:
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# Expand
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#
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# Updated operators:
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# Min, Max, Sum, Mean: supports multidirectional broadcasting.
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# MaxPool: added optional indices output.
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# Scan
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black_listed_operators = [
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"scan", "expand", "expand_as", "meshgrid",
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"adaptive_max_pool1d", "adaptive_max_pool2d", "adaptive_max_pool3d",
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"max_pool1d_with_indices", "max_pool2d_with_indices", "max_pool3d_with_indices"
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]
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# NOTE: max, min, sum, mean: broadcasting is not supported in opset 7.
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# torch.max (same for torch.min) actually has two interfaces smashed together:
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# torch.max(x, dim, keepdim) and torch.max(x, y)
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def max(g, self, dim_or_y=None, keepdim=None):
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# torch.max(input, other)
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if keepdim is None and dim_or_y is not None:
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warnings.warn("Multidirectional broadcasting is not supported in opset 7. "
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"This might cause the onnx model to be incorrect, if inputs to max operators "
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"have different shapes")
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return sym_opset9.max(g, self, dim_or_y, keepdim)
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def min(g, self, dim_or_y=None, keepdim=None):
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# torch.min(input, other)
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if keepdim is None and dim_or_y is not None:
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warnings.warn("Multidirectional broadcasting is not supported in opset 7. "
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"This might cause the onnx model to be incorrect, if inputs to min operators "
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"have different shapes")
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return sym_opset9.min(g, self, dim_or_y, keepdim)
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for black_listed_op in black_listed_operators:
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vars()[black_listed_op] = _black_list_in_opset(black_listed_op)
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