gpt-5.5-priority
l12_default_gpt · original · 200 trajectories
← all variants← originalgenerated 2026-05-28 03:33:16 UTC
L1 P1 1_Square_matrix_multiplication_.
correct 1.00x 2.6μs
L1 P2 2_Standard_matrix_multiplication
correct 8.19x 0.3μs
L1 P3 3_Batched_matrix_multiplication.
correct 5.76x 0.9μs
L1 P4 4_Matrix_vector_multiplication_.
correct 0.97x 3.0μs
L1 P5 5_Matrix_scalar_multiplication.p
correct 0.66x 4.3μs
L1 P6 6_Matmul_with_large_K_dimension_
error —
L1 P7 7_Matmul_with_small_K_dimension_
correct 0.84x 5.0μs
L1 P8 8_Matmul_with_irregular_shapes_.
error —
L1 P9 9_Tall_skinny_matrix_multiplicat
correct 0.42x 11.5μs
L1 P10 10_3D_tensor_matrix_multiplicati
correct 1.00x 1.0μs
L1 P11 11_4D_tensor_matrix_multiplicati
correct 1.00x 11.0μs
L1 P12 12_Matmul_with_diagonal_matrices
correct 1.23x 0.1μs
L1 P13 13_Matmul_for_symmetric_matrices
correct 1.00x 2.7μs
L1 P14 14_Matmul_for_upper_triangular_m
correct 3.23x 0.8μs
L1 P15 15_Matmul_for_lower_triangular_m
correct 1.82x 1.5μs
L1 P16 16_Matmul_with_transposed_A.py
correct 0.18x 14.4μs
L1 P17 17_Matmul_with_transposed_B.py
error —
L1 P18 18_Matmul_with_transposed_both.p
correct 1.00x 2.8μs
L1 P19 19_ReLU.py
error —
L1 P20 20_LeakyReLU.py
correct 833.33x 0.0μs
L1 P21 21_Sigmoid.py
correct 0.92x 4.7μs
L1 P22 22_Tanh.py
correct 0.95x 4.5μs
L1 P23 23_Softmax.py
error —
L1 P24 24_LogSoftmax.py
correct 0.99x 8.8μs
L1 P25 25_Swish.py
correct 2.26x 4.7μs
L1 P26 26_GELU_.py
correct 0.92x 4.7μs
L1 P27 27_SELU_.py
error —
L1 P28 28_HardSigmoid.py
correct 0.93x 4.6μs
L1 P29 29_Softplus.py
correct 0.92x 4.7μs
L1 P30 30_Softsign.py
correct 3.28x 4.5μs
L1 P31 31_ELU.py
correct 1303.03x 0.0μs
L1 P32 32_HardTanh.py
error —
L1 P33 33_BatchNorm.py
correct 1.95x 4.6μs
L1 P34 34_InstanceNorm.py
correct 0.89x 10.9μs
L1 P35 35_GroupNorm_.py
error —
L1 P36 36_RMSNorm_.py
correct 1.69x 8.4μs
L1 P37 37_FrobeniusNorm_.py
error —
L1 P38 38_L1Norm_.py
correct 1.39x 11.3μs
L1 P39 39_L2Norm_.py
correct 0.78x 12.8μs
L1 P40 40_LayerNorm.py
correct 28.87x 0.3μs
L1 P41 41_Max_Pooling_1D.py
correct 4.63x 2.3μs
L1 P42 42_Max_Pooling_2D.py
correct 2.53x 4.3μs
L1 P43 43_Max_Pooling_3D.py
correct 1.24x 3.2μs
L1 P44 44_Average_Pooling_1D.py
correct 3.10x 1.8μs
L1 P45 45_Average_Pooling_2D.py
correct 1.15x 5.7μs
L1 P46 46_Average_Pooling_3D.py
correct 1.00x 8.6μs
L1 P47 47_Sum_reduction_over_a_dimensio
correct 0.88x 3.4μs
L1 P48 48_Mean_reduction_over_a_dimensi
error —
L1 P49 49_Max_reduction_over_a_dimensio
correct 0.90x 4.1μs
L1 P50 50_conv_standard_2D__square_inpu
error —
L1 P51 51_Argmax_over_a_dimension.py
correct 0.92x 3.5μs
L1 P52 52_Argmin_over_a_dimension.py
error —
L1 P53 53_Min_reduction_over_a_dimensio
error —
L1 P54 54_conv_standard_3D__square_inpu
correct 0.28x 6.7μs
L1 P55 55_conv_standard_2D__asymmetric_
error —
L1 P56 56_conv_standard_2D__asymmetric_
error —
L1 P57 57_conv_transposed_2D__square_in
correct 0.03x 191.0μs
L1 P58 58_conv_transposed_3D__asymmetri
error —
L1 P59 59_conv_standard_3D__asymmetric_
correct 0.42x 6.6μs
L1 P60 60_conv_standard_3D__square_inpu
correct 0.49x 20.3μs
L1 P61 61_conv_transposed_3D__square_in
correct 1.00x 9.1μs
L1 P62 62_conv_standard_2D__square_inpu
error —
L1 P63 63_conv_standard_2D__square_inpu
error —
L1 P64 64_conv_transposed_1D.py
incorrect —
L1 P65 65_conv_transposed_2D__square_in
correct 0.05x 51.5μs
L1 P66 66_conv_standard_3D__asymmetric_
correct 1.04x 4.7μs
L1 P67 67_conv_standard_1D.py
error —
L1 P68 68_conv_transposed_3D__square_in
correct 1.00x 36.9μs
L1 P69 69_conv_transposed_2D__asymmetri
correct 0.03x 101.0μs
L1 P70 70_conv_transposed_3D__asymmetri
correct 0.17x 169.0μs
L1 P71 71_conv_transposed_2D__asymmetri
error —
L1 P72 72_conv_transposed_3D_asymmetric
error —
L1 P73 73_conv_transposed_3D_asymmetric
error —
L1 P74 74_conv_transposed_1D_dilated.py
correct 0.06x 37.5μs
L1 P75 75_conv_transposed_2D_asymmetric
error —
L1 P76 76_conv_standard_1D_dilated_stri
correct 0.11x 115.0μs
L1 P77 77_conv_transposed_3D_square_inp
error —
L1 P78 78_conv_transposed_2D_asymmetric
correct 0.78x 14.7μs
L1 P79 79_conv_transposed_1D_asymmetric
compile_fail —
L1 P80 80_conv_standard_2D_square_input
correct 0.10x 170.0μs
L1 P81 81_conv_transposed_2D_asymmetric
incorrect —
L1 P82 82_conv_depthwise_2D_square_inpu
correct 2.73x 0.9μs
L1 P83 83_conv_depthwise_2D_square_inpu
correct 3.75x 0.4μs
L1 P84 84_conv_depthwise_2D_asymmetric_
correct 2.60x 3.9μs
L1 P85 85_conv_depthwise_2D_asymmetric_
error —
L1 P86 86_conv_depthwise_separable_2D.p
correct 1.30x 2.8μs
L1 P87 87_conv_pointwise_2D.py
correct 0.58x 8.1μs
L1 P88 88_MinGPTNewGelu.py
correct 8.80x 0.2μs
L1 P89 89_cumsum.py
error —
L1 P90 90_cumprod.py
correct 3.30x 1.4μs
L1 P91 91_cumsum_reverse.py
correct 3.35x 3.4μs
L1 P92 92_cumsum_exclusive.py
correct 3.73x 3.5μs
L1 P93 93_masked_cumsum.py
correct 1.87x 4.8μs
L1 P94 94_MSELoss.py
correct 2.94x 2.9μs
L1 P95 95_CrossEntropyLoss.py
incorrect —
L1 P96 96_HuberLoss.py
correct 1.94x 2.9μs
L1 P97 97_ScaledDotProductAttention.py
correct 0.14x 185.0μs
L1 P98 98_KLDivLoss.py
correct 5.41x 0.7μs
L1 P99 99_TripletMarginLoss.py
correct 4.02x 1.1μs
L1 P100 100_HingeLoss.py
correct 6.93x 1.5μs
L2 P1 1_Conv2D_ReLU_BiasAdd.py
correct 1.60x 2.7μs
L2 P2 2_ConvTranspose2d_BiasAdd_Clamp_
correct 1.76x 7.2μs
L2 P3 3_ConvTranspose3d_Sum_LayerNorm_
correct 3.01x 3.4μs
L2 P4 4_Conv2d_Mish_Mish.py
correct 1.14x 7.6μs
L2 P5 5_ConvTranspose2d_Subtract_Tanh.
error —
L2 P6 6_Conv3d_Softmax_MaxPool_MaxPool
error —
L2 P7 7_Conv3d_ReLU_LeakyReLU_GELU_Sig
correct 1.54x 4.2μs
L2 P8 8_Conv3d_Divide_Max_GlobalAvgPoo
correct 1.08x 4.1μs
L2 P9 9_Matmul_Subtract_Multiply_ReLU.
correct 7.91x 0.3μs
L2 P10 10_ConvTranspose2d_MaxPool_Hardt
correct 1.18x 8.3μs
L2 P11 11_ConvTranspose2d_BatchNorm_Tan
correct 1.09x 2.4μs
L2 P12 12_Gemm_Multiply_LeakyReLU.py
correct 0.98x 2.8μs
L2 P13 13_ConvTranspose3d_Mean_Add_Soft
correct 1.34x 7.4μs
L2 P14 14_Gemm_Divide_Sum_Scaling.py
correct 1.01x 2.8μs
L2 P15 15_ConvTranspose3d_BatchNorm_Sub
correct 1.68x 1.2μs
L2 P16 16_ConvTranspose2d_Mish_Add_Hard
error —
L2 P17 17_Conv2d_InstanceNorm_Divide.py
correct 1.22x 4.0μs
L2 P18 18_Matmul_Sum_Max_AvgPool_LogSum
correct 95.85x 0.0μs
L2 P19 19_ConvTranspose2d_GELU_GroupNor
correct 1.04x 16.2μs
L2 P20 20_ConvTranspose3d_Sum_ResidualA
correct 2.18x 1.7μs
L2 P21 21_Conv2d_Add_Scale_Sigmoid_Grou
error —
L2 P22 22_Matmul_Scale_ResidualAdd_Clam
correct 1.06x 2.7μs
L2 P23 23_Conv3d_GroupNorm_Mean.py
correct 230.22x 0.0μs
L2 P24 24_Conv3d_Min_Softmax.py
correct 0.51x 1.9μs
L2 P25 25_Conv2d_Min_Tanh_Tanh.py
correct 1.04x 6.3μs
L2 P26 26_ConvTranspose3d_Add_HardSwish
error —
L2 P27 27_Conv3d_HardSwish_GroupNorm_Me
correct 0.26x 46.7μs
L2 P28 28_BMM_InstanceNorm_Sum_Residual
correct 1.03x 2.7μs
L2 P29 29_Matmul_Mish_Mish.py
correct —
L2 P30 30_Gemm_GroupNorm_Hardtanh.py
correct 1.04x 2.7μs
L2 P31 31_Conv2d_Min_Add_Multiply.py
correct 1.34x 3.8μs
L2 P32 32_Conv2d_Scaling_Min.py
correct 1.23x 6.5μs
L2 P33 33_Gemm_Scale_BatchNorm.py
correct 1.00x 2.8μs
L2 P34 34_ConvTranspose3d_LayerNorm_GEL
error —
L2 P35 35_Conv2d_Subtract_HardSwish_Max
correct 1.57x 3.3μs
L2 P36 36_ConvTranspose2d_Min_Sum_GELU_
correct 245.00x 0.0μs
L2 P37 37_Matmul_Swish_Sum_GroupNorm.py
error —
L2 P38 38_ConvTranspose3d_AvgPool_Clamp
error —
L2 P39 39_Gemm_Scale_BatchNorm.py
correct 1.03x 11.2μs
L2 P40 40_Matmul_Scaling_ResidualAdd.py
correct 1.04x 11.1μs
L2 P41 41_Gemm_BatchNorm_GELU_ReLU.py
error —
L2 P42 42_ConvTranspose2d_GlobalAvgPool
correct 13.84x 0.5μs
L2 P43 43_Conv3d_Max_LogSumExp_ReLU.py
correct 0.24x 11.0μs
L2 P44 44_ConvTranspose2d_Multiply_Glob
correct 29.93x 0.1μs
L2 P45 45_Gemm_Sigmoid_LogSumExp.py
correct 1.01x 8.5μs
L2 P46 46_Conv2d_Subtract_Tanh_Subtract
error —
L2 P47 47_Conv3d_Mish_Tanh.py
correct 0.62x 4.1μs
L2 P48 48_Conv3d_Scaling_Tanh_Multiply_
correct 2.42x 1.4μs
L2 P49 49_ConvTranspose3d_Softmax_Sigmo
correct 0.20x 14.7μs
L2 P50 50_ConvTranspose3d_Scaling_AvgPo
correct 19.00x 0.3μs
L2 P51 51_Gemm_Subtract_GlobalAvgPool_L
correct 77.15x 0.1μs
L2 P52 52_Conv2d_Activation_BatchNorm.p
correct 1.03x 3.4μs
L2 P53 53_Gemm_Scaling_Hardtanh_GELU.py
correct 1.02x 5.4μs
L2 P54 54_Conv2d_Multiply_LeakyReLU_GEL
correct 1.28x 4.8μs
L2 P55 55_Matmul_MaxPool_Sum_Scale.py
error —
L2 P56 56_Matmul_Sigmoid_Sum.py
correct 3.46x 1.6μs
L2 P57 57_Conv2d_ReLU_HardSwish.py
error —
L2 P58 58_ConvTranspose3d_LogSumExp_Har
correct 7.22x 1.0μs
L2 P59 59_Matmul_Swish_Scaling.py
correct 1.01x 5.3μs
L2 P60 60_ConvTranspose3d_Swish_GroupNo
error —
L2 P61 61_ConvTranspose3d_ReLU_GroupNor
error —
L2 P62 62_Matmul_GroupNorm_LeakyReLU_Su
correct 1.14x 2.7μs
L2 P63 63_Gemm_ReLU_Divide.py
correct 0.99x 2.8μs
L2 P64 64_Gemm_LogSumExp_LeakyReLU_Leak
error —
L2 P65 65_Conv2d_AvgPool_Sigmoid_Sum.py
correct 2.14x 5.7μs
L2 P66 66_Matmul_Dropout_Softmax.py
error —
L2 P67 67_Conv2d_GELU_GlobalAvgPool.py
error —
L2 P68 68_Matmul_Min_Subtract.py
correct 1.01x 1.4μs
L2 P69 69_Conv2d_HardSwish_ReLU.py
error —
L2 P70 70_Gemm_Sigmoid_Scaling_Residual
correct 0.99x 2.8μs
L2 P71 71_Conv2d_Divide_LeakyReLU.py
correct 1.38x 1.3μs
L2 P72 72_ConvTranspose3d_BatchNorm_Avg
incorrect —
L2 P73 73_Conv2d_BatchNorm_Scaling.py
correct 0.71x 3.7μs
L2 P74 74_ConvTranspose3d_LeakyReLU_Mul
correct 0.85x 1.7μs
L2 P75 75_Gemm_GroupNorm_Min_BiasAdd.py
correct 1.13x 2.7μs
L2 P76 76_Gemm_Add_ReLU.py
correct 1.02x 2.7μs
L2 P77 77_ConvTranspose3d_Scale_BatchNo
correct 1.08x 5.0μs
L2 P78 78_ConvTranspose3d_Max_Max_Sum.p
error —
L2 P79 79_Conv3d_Multiply_InstanceNorm_
correct 1.06x 0.9μs
L2 P80 80_Gemm_Max_Subtract_GELU.py
correct 504.64x 0.0μs
L2 P81 81_Gemm_Swish_Divide_Clamp_Tanh_
correct 1.05x 2.7μs
L2 P82 82_Conv2d_Tanh_Scaling_BiasAdd_M
correct 1.79x 5.5μs
L2 P83 83_Conv3d_GroupNorm_Min_Clamp_Dr
correct 25.95x 0.2μs
L2 P84 84_Gemm_BatchNorm_Scaling_Softma
correct 1.02x 2.8μs
L2 P85 85_Conv2d_GroupNorm_Scale_MaxPoo
correct 1.68x 1.5μs
L2 P86 86_Matmul_Divide_GELU.py
error —
L2 P87 87_Conv2d_Subtract_Subtract_Mish
correct 0.65x 13.3μs
L2 P88 88_Gemm_GroupNorm_Swish_Multiply
error —
L2 P89 89_ConvTranspose3d_MaxPool_Softm
correct 12.33x 0.5μs
L2 P90 90_Conv3d_LeakyReLU_Sum_Clamp_GE
correct 1.42x 8.0μs
L2 P91 91_ConvTranspose2d_Softmax_BiasA
correct 2.30x 4.0μs
L2 P92 92_Conv2d_GroupNorm_Tanh_HardSwi
correct 1.20x 3.5μs
L2 P93 93_ConvTranspose2d_Add_Min_GELU_
correct 1.71x 3.4μs
L2 P94 94_Gemm_BiasAdd_Hardtanh_Mish_Gr
correct 1.08x 2.7μs
L2 P95 95_Matmul_Add_Swish_Tanh_GELU_Ha
correct 1.03x 2.8μs
L2 P96 96_ConvTranspose3d_Multiply_Max_
correct 18.75x 0.3μs
L2 P97 97_Matmul_BatchNorm_BiasAdd_Divi
error —
L2 P98 98_Matmul_AvgPool_GELU_Scale_Max
correct 14.34x 0.2μs
L2 P99 99_Matmul_GELU_Softmax.py
correct 1.00x 2.7μs
L2 P100 100_ConvTranspose3d_Clamp_Min_Di
correct 1.30x 10.4μs