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fix the bug, disable the fast1x1 when padding is not 0.
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@ -456,7 +456,8 @@ void runFastConv(InputArray _input, OutputArray _output, const Ptr<FastConv>& co
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int dilation_d = conv->dilation_d, dilation_h = conv->dilation_h, dilation_w = conv->dilation_w;
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int ksize = Dk*Hk*Wk;
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bool fast_1x1 = ksize == 1 && stride_d == 1 && stride_w == 1 && stride_h == 1;
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bool fast_1x1 = ksize == 1 && stride_d == 1 && stride_w == 1 && stride_h == 1
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&& pad_front == 0 && pad_left == 0 && pad_top == 0;
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int DkHkWkCg = Dk*Hk*Wk*Cg;
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std::vector<int> ofstab_(Hk*Wk*Dk*4, 0);
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@ -502,7 +503,7 @@ void runFastConv(InputArray _input, OutputArray _output, const Ptr<FastConv>& co
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}
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}
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int MAX_STRIPES = (56 + CONV_NR - 1)/CONV_NR;
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int MAX_STRIPES = conv->conv_type == CONV_TYPE_DEPTHWISE_REMAIN ? 1 : (56 + CONV_NR - 1)/CONV_NR;
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// Friendly to L1 cache
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const int K_BLOCK_SIZE = conv->conv_type == CONV_TYPE_DEPTHWISE_REMAIN ? 1 : 32;
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@ -256,6 +256,7 @@ TEST_P(Test_ONNX_layers, Convolution3D_bias)
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applyTestTag(CV_TEST_TAG_DNN_SKIP_CUDA_FP16);
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}
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testONNXModels("conv3d_bias");
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testONNXModels("conv3d_depthwise_bias"); // kernel 1x1
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}
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TEST_P(Test_ONNX_layers, Two_convolution)
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