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duality-group / torch python
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Version:
1.12.1+cpu ▾
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ít LêLöDÿAÿÜHÃH9ëuêHÄ[]A\A]A^A_Ðf. óÃ HìHÄÃ ? _ @@ MALFORMED INPUT: UNKNOWN_SCALAR Char Short Int Long Half Float Double ComplexHalf ComplexFloat ComplexDouble QUInt2x4 Byte QUInt8 QUInt4x2 BFloat16 QInt32 QInt8 Bool ../c10/core/ScalarType.h promoteTypes
x Tensor expression: a b c A j Store statement: Nested for loops: B Compound Block statement: C D LoopNest root stmt: Stmt after inlining: Stmt after simplification: Stmt after splitWithTail: *** Codegen *** X func A[10] = B[10] = X[10] = A[10] + B[10] = Generated LLVM IR: ir Generated assembly: asm R[2][2] = vector::reserve i vector::_M_realloc_insert fused lanes dont match scalar type doesn't match vector::_M_range_insert mismatch between reduce body and arg size (2) promoteTypes with quantized numbers is not handled yet; figure out what the correct rules should be, offending types: cannot create std::vector larger than max_size() *** Structure of tensor expressions and statements *** Stmt produced by 'Compute' API: Stmt produced by 'Reduce' API: *** Loopnests transformations *** *** Lowering TorchScript IR to TensorExpr IR ***
graph(%A : Float(5, 3, strides=[3, 1], device=cpu),
%B : Float(5, 3, strides=[3, 1], device=cpu)):
%AB : Float(5, 3, strides=[3, 1]) = aten::mul(%A, %B)
%one : int = prim::Constant[value=1]()
%AAB : Float(5, 3, strides=[3, 1]) = aten::mul(%A, %AB)
%AAB_plus_B: Float(5, 3, strides=[3, 1]) = aten::add(%AAB, %B, %one)
return (%AAB_plus_B) TE Stmt constructed from TorchScript: xÿÿxÿÿkzÿÿwzÿÿzÿÿzÿÿzÿÿ§zÿÿ³zÿÿ¿zÿÿËzÿÿqxÿÿ×zÿÿãzÿÿïzÿÿûzÿÿ_zÿÿ¤xÿÿØzÿÿÈzÿÿ¸{ÿÿÈ{ÿÿx{ÿÿ{ÿÿ{ÿÿ¨{ÿÿøzÿÿ{ÿÿ{ÿÿ({ÿÿ8{ÿÿH{ÿÿX{ÿÿh{ÿÿèzÿÿÉxÿÿzxÿÿxÿÿÛyÿÿçyÿÿóyÿÿÿyÿÿ zÿÿzÿÿ#zÿÿ/zÿÿ;zÿÿáwÿÿGzÿÿSzÿÿ_zÿÿkzÿÿÏyÿÿxÿÿ *Z4mainEUlRKN5torch3jit10tensorexpr9VarHandleES4_E_ *Z4mainEUlRKN5torch3jit10tensorexpr9VarHandleES4_E1_ *Z4mainEUlRKN5torch3jit10tensorexpr9VarHandleES4_E2_ *Z4mainEUlRKN5torch3jit10tensorexpr9VarHandleES4_E3_ *Z4mainEUlRKN5torch3jit10tensorexpr9VarHandleES4_E0_
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