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Hotfix binary elementwise (for broadcast on fastest axis) (#254)
* Support different length of ScalarPerVector * Add example of broadcast on fastest axis * Typo * Refine fastest example * Add dimension check * Modify fastest broadcast example to 3d * Enforce users give scalarPerVector explicitely * 1. Add CscalarPerVedctor 2. Not only broadcast on fastest need to set scalarPerVector to 1 * Rename var * Move IsScalarPerVectorValid() inside IsSupportedArgument() * Separate GridDesc_M0 into A, B and C * rename var * Rename var of length Co-authored-by: rocking <chunylai@amd.com>
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@@ -19,8 +19,17 @@ using EltwiseComputeDataType = F32;
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using Add = ck::tensor_operation::binary_element_wise::Add;
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using DeviceElementwiseAddInstance = ck::tensor_operation::device::
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DeviceBinaryElementwise<ABDataType, ABDataType, CDataType, EltwiseComputeDataType, Add, 1, 8>;
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using DeviceElementwiseAddInstance =
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ck::tensor_operation::device::DeviceBinaryElementwise<ABDataType,
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ABDataType,
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CDataType,
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EltwiseComputeDataType,
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Add,
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1,
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8,
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8,
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8,
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8>;
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template <typename HostTensorA,
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typename HostTensorB,
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@@ -81,7 +90,7 @@ int main()
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if(!broadcastAdd.IsSupportedArgument(argument.get()))
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{
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throw std::runtime_error("The runtime parameters seems not supported by the "
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"DeviceBinaryElementwise_2D instance, exiting!");
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"DeviceBinaryElementwise instance, exiting!");
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};
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auto broadcastAdd_invoker_ptr = broadcastAdd.MakeInvokerPointer();
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@@ -103,7 +112,7 @@ int main()
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Add>(host_c_m, a_m, b_m, M, Add{});
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pass &= ck::utils::check_err(
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c_m.mData, host_c_m.mData, "Error: Incorrect results d1", 1e-3, 1e-3);
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c_m.mData, host_c_m.mData, "Error: Incorrect results c", 1e-3, 1e-3);
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}
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return pass ? 0 : 1;
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