[Frontend][Relay] Keras softmax and prelu fix under NHWC #6278
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leandron
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Aug 14, 2020
leandron
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Aug 14, 2020
domin1985
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@kazum please also help to manage the PR |
jwfromm
approved these changes
Aug 22, 2020
kazum
approved these changes
Aug 24, 2020
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@domin1985 The change looks good. Could you rebase against the master to trigger the CI? |
* prelu and softmax with NHWC layout consideration * fix lint * fix lint
|
Thanks @domin1985 @leandron @jwfromm @yongwww ! |
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) * prelu and softmax with NHWC layout consideration * fix lint * fix lint Co-authored-by: Dongming Yang <[email protected]>
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) * prelu and softmax with NHWC layout consideration * fix lint * fix lint Co-authored-by: Dongming Yang <[email protected]>
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) * prelu and softmax with NHWC layout consideration * fix lint * fix lint Co-authored-by: Dongming Yang <[email protected]>
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) * prelu and softmax with NHWC layout consideration * fix lint * fix lint Co-authored-by: Dongming Yang <[email protected]>
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) * prelu and softmax with NHWC layout consideration * fix lint * fix lint Co-authored-by: Dongming Yang <[email protected]>
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Hi,
Tvm error occurred when I imported a pre-trained keras model with NHWC layout:
TVMError:
Error(s) have occurred. The program has been annotated with them:
In main:
%0 = negative(%v_param_3);
%1 = nn.conv2d(%input_1, %v_param_1, padding=[4, 4], channels=64, kernel_size=[9, 9], data_layout="NHWC", kernel_layout="HWIO");
%2 = nn.bias_add(%1, %v_param_2, axis=-1);
%3 = negative(%2);
%4 = nn.relu(%3);
%5 = multiply(%0, %4) Incompatible broadcast type TensorType([64, 1, 1], float32) and TensorType([1, (int64)96, (int64)96, 64], float32); ;
%6 = nn.relu(%2);
softmax and prelu convertion should take layout into consideration.
@siju-samuel @yongwww @jwfromm