[ONNX] QLinearConv Support #8007
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mbrookhart
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May 10, 2021
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| # For QLinearConv tests in ONNX, scale and zero_point input are placeholders, | ||
| # but qnn.conv2d requires scale and zero_point input to be scalar |
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I have tried to work around this issue but failed. For ONNX test model of QLinearConv, y_scale is input node and will be parsed to free_var in relay. It will cause an error while lowering requantize because it requires output_scale (y_scale) to be constant expr:
E 1: tvm::relay::qnn::RequantizeLower(tvm::RelayExpr const&, tvm::RelayExpr const&, tvm::RelayExpr const&, tvm::RelayExpr const&, tvm::RelayExpr const&, tvm::relay::qnn::RequantizeAttrs const*, tvm::r
untime::Array<tvm::PrimExpr, void> const&, tvm::runtime::DataType const&)
E at /home/liuliang/Desktop/tvms/tvm/src/relay/qnn/op/requantize.cc:148
E 0: float tvm::relay::GetScalarFromConstant<float>(tvm::RelayExpr)
E at /home/liuliang/Desktop/tvms/tvm/src/relay/qnn/op/../../transforms/pattern_utils.h:514
E File "/home/liuliang/Desktop/tvms/tvm/src/relay/quantize/../transforms/pattern_utils.h", line 514
E TVMError:
E ---------------------------------------------------------------
E An error occurred during the execution of TVM.
E For more information, please see: https://tvm.apache.org/docs/errors.html
E ---------------------------------------------------------------
E Check failed: (n) is false: Expr must be a constant expr - #[version = "0.0.5"]
E free_var %y_scale: float32;
E cast(%y_scale, dtype="float32") /* ty=float32 */
Do you have some suggestions to solve it?
|
Hmm, what do you think about checking to see if the scale is constant, and if it's not, doing dequantize -> quantize instead of requantize? |
|
@mbrookhart, thanks! The idea looks good, it could solve the issue! |
mbrookhart
approved these changes
May 12, 2021
|
Thanks @huochaitiantang ! |
mehrdadh
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to mehrdadh/tvm
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May 19, 2021
* Add QLinearConv for onnx frontend * Reformat * Squeeze 1D tensor for weight_scale & weight_zero_point * Doing dequatize -> quantize if y_scale is not constant
trevor-m
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Jun 17, 2021
* Add QLinearConv for onnx frontend * Reformat * Squeeze 1D tensor for weight_scale & weight_zero_point * Doing dequatize -> quantize if y_scale is not constant
trevor-m
pushed a commit
to neo-ai/tvm
that referenced
this pull request
Jun 17, 2021
* Add QLinearConv for onnx frontend * Reformat * Squeeze 1D tensor for weight_scale & weight_zero_point * Doing dequatize -> quantize if y_scale is not constant
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