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May 27, 2026 18:58
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cubectl attempt to add with overflow
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| 2026-05-27T13:07:14.930910Z INFO burn_train::learner::supervised::strategies::single::epoch: Executing training step for epoch 1 | |
| 2026-05-27T13:07:17.801889Z INFO burn_train::learner::supervised::strategies::single::epoch: Iteration 1 | |
| 2026-05-27T13:07:17.812587Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:07:17.812683Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:07:17.812752Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [2, 2], padding: [3, 3], dilation: [1, 1], groups: 1, in_channels: 4, out_channels: 64, shape: [256, 256], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:20.100380Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:07:20.100519Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:07:20.100547Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 1024, VectorCount: 64 | |
| 2026-05-27T13:07:22.070540Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 4, lhs_stride_align: 8, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:23.824131Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:07:23.824221Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:07:23.824248Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 131072, n: 64, k: 64, lhs_pow2_factor: 4, lhs_stride_factor: 8, rhs_pow2_factor: 4, rhs_stride_factor: 8, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:28.180744Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:29.191849Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 256, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:29.664589Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 131072, n: 256, k: 64, lhs_pow2_factor: 4, lhs_stride_factor: 8, rhs_pow2_factor: 4, rhs_stride_factor: 8, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:30.490833Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 1024, VectorCount: 512 | |
| 2026-05-27T13:07:31.540799Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 256, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 4, lhs_stride_align: 8, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:32.313713Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:32.834649Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 131072, n: 64, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:33.424197Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:33.680158Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 131072, n: 128, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:33.947814Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:34.476024Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 512, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:35.497817Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32768, n: 512, k: 128, lhs_pow2_factor: 4, lhs_stride_factor: 9, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:36.556879Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 512, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:37.347845Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:37.764812Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32768, n: 128, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:38.781566Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:39.022533Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:39.470757Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32768, n: 256, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:39.737774Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:40.065794Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 1024, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:41.258125Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 8192, n: 1024, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:47.031826Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 1024, VectorCount: 4096 | |
| 2026-05-27T13:07:47.316802Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 1024, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:48.429493Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:49.223274Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 8192, n: 256, k: 1024, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:50.317327Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:50.900883Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:51.564414Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 8192, n: 512, k: 1024, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:51.823381Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:52.134445Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 2048, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:53.030966Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 2048, n: 2048, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:56.257024Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 2048, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:57.529546Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 2048, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:07:58.070360Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 2048, n: 512, k: 2048, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:07:58.296648Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:07:58.912712Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32, n: 4, k: 2048, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 0, rhs_stride_factor: 4, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:02.827108Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 16, VectorCount: 64 | |
| 2026-05-27T13:08:03.786640Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 64, VectorCount: 1 | |
| 2026-05-27T13:08:04.391803Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32, n: 2048, k: 4, lhs_pow2_factor: 0, lhs_stride_factor: 2, rhs_pow2_factor: 0, rhs_stride_factor: 4, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:08.896990Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 2048, n: 4, k: 32, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 0, rhs_stride_factor: 2, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: MildlyPermuted { transposed: true, batch_swap: false }, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:11.363983Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 64, VectorCount: 8 | |
| 2026-05-27T13:08:11.966917Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 64, VectorCount: 32768 | |
| 2026-05-27T13:08:12.969607Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 16, VectorCount: 32768 | |
| 2026-05-27T13:08:13.577429Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 16, VectorCount: 4096 | |
| 2026-05-27T13:08:14.214095Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:08:14.214212Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:08:14.214239Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 2048, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:08:16.156719Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:08:16.156815Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:08:16.156848Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 2048, out_channels: 2048, height: 8, width: 8, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:18.264613Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 512, n: 2048, k: 2048, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 7, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:21.821361Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:08:21.821445Z INFO cubecl_runtime::tune::tune_cache: Loaded 0 autotune cached entries | |
| 2026-05-27T13:08:21.821469Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 2048, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:21.823737Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 2048, shape: [8, 8], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:22.322235Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 16, VectorCount: 4096 | |
| 2026-05-27T13:08:22.557443Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 16, VectorCount: 512 | |
| 2026-05-27T13:08:22.594995Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:22.597542Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 8, width: 8, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:23.006230Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 8192, n: 2048, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 7, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:24.568578Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:24.571477Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 512, shape: [8, 8], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:25.074126Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 2048, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:08:25.099113Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 8, width: 8, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:25.262808Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 2048, n: 2048, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 7, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:26.311195Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 2048, out_channels: 512, shape: [8, 8], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:26.523326Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 512, shape: [8, 8], batch_size: 2048, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:26.856454Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:26.874081Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 8, width: 8, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:27.392600Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:27.395340Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [1, 1], padding: [1, 1], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 512, shape: [16, 16], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:28.580882Z ERROR burn_train::learner::application_logger: PANIC => panicked at /home/jeandudey/.cargo/registry/src/index.crates.io-1949cf8c6b5b557f/burn-train-0.21.0/src/renderer/tui/metric_numeric.rs:163:25: | |
| attempt to calculate the remainder with a divisor of zero | |
| 2026-05-27T13:08:29.027196Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 2048, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:08:30.046754Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 2048, out_channels: 2048, height: 8, width: 8, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:30.105551Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 1024, n: 2048, k: 2048, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 7, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:08:31.094405Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 2048, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:31.097114Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [1, 1], padding: [0, 0], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 2048, shape: [16, 16], batch_size: 1024, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:08:32.787585Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:08:32.988041Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:08:33.298418Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 1024, n: 8192, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:09:12.211785Z INFO burn_train::learner::supervised::strategies::single::epoch: Executing training step for epoch 1 | |
| 2026-05-27T13:09:14.480600Z INFO burn_train::learner::supervised::strategies::single::epoch: Iteration 1 | |
| 2026-05-27T13:09:14.505433Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:14.505627Z INFO cubecl_runtime::tune::tune_cache: Loaded 29 autotune cached entries | |
| 2026-05-27T13:09:14.508023Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:14.508128Z INFO cubecl_runtime::tune::tune_cache: Loaded 11 autotune cached entries | |
| 2026-05-27T13:09:16.945811Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:16.945930Z INFO cubecl_runtime::tune::tune_cache: Loaded 19 autotune cached entries | |
| 2026-05-27T13:09:37.941061Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:37.941180Z INFO cubecl_runtime::tune::tune_cache: Loaded 5 autotune cached entries | |
| 2026-05-27T13:09:37.941530Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:37.941610Z INFO cubecl_runtime::tune::tune_cache: Loaded 5 autotune cached entries | |
| 2026-05-27T13:09:41.599453Z INFO cubecl_runtime::tune::tune_cache: Load autotune cache ... | |
| 2026-05-27T13:09:41.599566Z INFO cubecl_runtime::tune::tune_cache: Loaded 5 autotune cached entries | |
| 2026-05-27T13:09:47.452218Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:09:49.268530Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:09:49.794996Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 1024, n: 8192, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:09:53.577471Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 512, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:09:53.774086Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 512, shape: [16, 16], batch_size: 1024, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:09:54.224793Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 1024, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:09:54.227360Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 1024, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:09:54.374051Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 256, n: 8192, k: 1024, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:09:57.649595Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 1024, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:09:57.651409Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 1024, shape: [16, 16], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:09:57.970754Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:09:57.985705Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:09:58.210128Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 4096, n: 8192, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:00.382185Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:00.384636Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 256, shape: [16, 16], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:00.831407Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:00.834227Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:00.984632Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 1024, n: 8192, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:01.818280Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 256, shape: [16, 16], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:02.019129Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 256, shape: [16, 16], batch_size: 1024, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:02.371586Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:02.382158Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:02.875202Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:02.888444Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [1, 1], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 256, shape: [32, 32], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:03.622394Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 64, VectorCount: 512 | |
| 2026-05-27T13:10:06.079826Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 1024, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:06.732206Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 1024, out_channels: 1024, height: 16, width: 16, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:06.804568Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 512, n: 8192, k: 1024, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 9, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:07.878358Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 1024, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:07.880949Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [14, 14], stride: [1, 1], padding: [0, 0], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 1024, shape: [32, 32], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:09.615790Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:09.870632Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:10.141351Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 512, n: 32768, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:10.408445Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 256, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:10.632941Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 256, shape: [32, 32], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:10.995915Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 512, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:11.000535Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:11.451697Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 128, n: 32768, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:11.749934Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 512, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:11.751972Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 512, shape: [32, 32], batch_size: 128, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:12.092277Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 64, VectorCount: 4096 | |
| 2026-05-27T13:10:13.083046Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:16.089499Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:16.328779Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 2048, n: 32768, k: 128, lhs_pow2_factor: 4, lhs_stride_factor: 9, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:18.340808Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:18.343577Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 128, shape: [32, 32], batch_size: 128, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:18.654683Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:18.657625Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:18.809856Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 512, n: 32768, k: 128, lhs_pow2_factor: 4, lhs_stride_factor: 9, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:19.051928Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 128, shape: [32, 32], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:19.284991Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 128, shape: [32, 32], batch_size: 512, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:19.561357Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:19.563901Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:20.415572Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [2, 2], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:20.418682Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [1, 1], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 128, shape: [64, 64], batch_size: 128, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:21.559522Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 512, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:22.460157Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], padding_out: [1, 1], dilation: [1, 1], groups: 1, in_channels: 512, out_channels: 512, height: 32, width: 32, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:22.635908Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 256, n: 32768, k: 512, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:22.864415Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [2, 2], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 512, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:22.866506Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [28, 28], stride: [1, 1], padding: [0, 0], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 512, shape: [64, 64], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:24.863529Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:24.926182Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 128, out_channels: 128, height: 64, width: 64, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:25.398115Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 256, n: 131072, k: 128, lhs_pow2_factor: 4, lhs_stride_factor: 9, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:25.952452Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 128, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:26.135470Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [56, 56], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 128, shape: [64, 64], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:26.497868Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 256, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:26.510116Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 256, height: 64, width: 64, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:26.841868Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 64, n: 131072, k: 256, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:29.928225Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 256, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:29.930612Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [56, 56], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 256, shape: [64, 64], batch_size: 64, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:30.308462Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 64, VectorCount: 64 | |
| 2026-05-27T13:10:31.202218Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:31.846034Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, height: 64, width: 64, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:32.291752Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 1024, n: 131072, k: 64, lhs_pow2_factor: 4, lhs_stride_factor: 8, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:32.572257Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [3, 3], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:32.575288Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [56, 56], stride: [1, 1], padding: [1, 1], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 64, shape: [64, 64], batch_size: 64, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:32.853964Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:32.861456Z INFO cubecl_runtime::tune::tuner: Tuning ConvTranspose2dAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], padding_out: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, height: 64, width: 64, batch_size: 32, has_bias: false, dtype: F32 } | |
| 2026-05-27T13:10:33.007453Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 256, n: 131072, k: 64, lhs_pow2_factor: 4, lhs_stride_factor: 8, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:33.228904Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 256, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:33.231920Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [56, 56], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 64, shape: [64, 64], batch_size: 256, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:33.969775Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 256, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 4, rhs_stride_align: 8 } | |
| 2026-05-27T13:10:34.166326Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 2, rhs_stride_align: 2 } | |
| 2026-05-27T13:10:34.174785Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 64, n: 131072, k: 64, lhs_pow2_factor: 4, lhs_stride_factor: 8, rhs_pow2_factor: 4, rhs_stride_factor: 10, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:34.333635Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [1, 1], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 64, out_channels: 64, shape: [64, 64], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 4, rhs_stride_align: 8 } | |
| 2026-05-27T13:10:34.543187Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [56, 56], stride: [1, 1], padding: [0, 0], dilation: [1, 1], groups: 1, in_channels: 32, out_channels: 64, shape: [64, 64], batch_size: 64, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:34.817593Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: false, VectorSize: 256, VectorCount: 32768 | |
| 2026-05-27T13:10:35.063955Z INFO cubecl_runtime::tune::tuner: Tuning ReduceAutotuneKey - ElemInput: Float(F32), ElemOutput: Float(F32), ElemAcc: Float(F32), AxisIsContiguous: true, VectorSize: 256, VectorCount: 64 | |
| 2026-05-27T13:10:35.101478Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [7, 7], stride: [2, 2], padding: [3, 3], dilation: [1, 1], groups: 1, in_channels: 4, out_channels: 64, shape: [256, 256], batch_size: 32, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:35.105120Z INFO cubecl_runtime::tune::tuner: Tuning ConvAutotuneKey { kernel_size: [112, 112], stride: [1, 1], padding: [3, 3], dilation: [2, 2], groups: 1, in_channels: 32, out_channels: 64, shape: [256, 256], batch_size: 4, has_bias: false, dtype: F32, lhs_shape_align: 0, lhs_stride_align: 0, rhs_shape_align: 0, rhs_stride_align: 0 } | |
| 2026-05-27T13:10:41.161194Z INFO burn_train::learner::supervised::strategies::single::epoch: Iteration 2 | |
| 2026-05-27T13:10:44.683550Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32, n: 4, k: 2048, lhs_pow2_factor: 4, lhs_stride_factor: 10, rhs_pow2_factor: 0, rhs_stride_factor: 2, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: Contiguous }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
| 2026-05-27T13:10:49.457044Z INFO cubecl_runtime::tune::tuner: Tuning MatmulAutotuneKey - Definition: MatmulProblemDefinition { m: 32, n: 2048, k: 4, lhs_pow2_factor: 0, lhs_stride_factor: 2, rhs_pow2_factor: 0, rhs_stride_factor: 2, elem_lhs: Scalar(Float(F32)), elem_rhs: Scalar(Float(F32)), elem_out: Scalar(Float(F32)), matrix_layout_lhs: Contiguous, matrix_layout_rhs: MildlyPermuted { transposed: true, batch_swap: false } }, Analysis: MatmulAutotuneAnalysis { scale_global: Large, kind: General } | |
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| 2026-05-27T13:13:10.891882Z ERROR burn_train::learner::application_logger: PANIC => panicked at /home/jeandudey/.cargo/registry/src/index.crates.io-1949cf8c6b5b557f/cubecl-runtime-0.10.0/src/memory_management/drop_queue/policy.rs:36:9: | |
| attempt to add with overflow |
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