Synchronizing local compiler cache.
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.gitattributes
CHANGED
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neuronxcc-2.21.18209.0+043b1bf7/MODULE_74c11479e8406b0ab839+a9d440f5/model.neff filter=lfs diff=lfs merge=lfs -text
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neuronxcc-2.21.18209.0+043b1bf7/0_REGISTRY/0.4.1.dev0/qwen3/Qwen/Qwen3-32B/1ae184e7b95dac097684.json
ADDED
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neuronxcc-2.21.18209.0+043b1bf7/0_REGISTRY/0.4.1.dev0/qwen3/Qwen/Qwen3-32B/2bb6e5edef9a6e488094.json
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{
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Failed compilation with ['neuronx-cc', 'compile', '--framework=XLA', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_00d39c882e9e437ead19+747527b0.hlo_module.pb', '--output', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_00d39c882e9e437ead19+747527b0.neff', '--target=trn2', '--auto-cast=none', '--model-type=transformer', '--tensorizer-options=--enable-ccop-compute-overlap --cc-pipeline-tiling-factor=2 --vectorize-strided-dma ', '-O2', '--lnc=2', '--logfile=/tmp/nxd_model/token_generation_model/_tp0_bk0/log-neuron-cc.txt', '--enable-internal-neff-wrapper', '--verbose=35']: 2025-10-17T07:11:57Z 2025-10-17 07:11:57.671531: F hilo/hlo_passes/NeuronHloVerifier.cc:504] [ERROR] [NCC_VRF009] Memory requirement exceeds target architecture's HBM limit. Needed 17455884400 bytes (16 GB) vs. available 17179869184 bytes (16 GB). TIP: Consider using smaller batches or applying model parallelism
|
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Failed compilation with ['neuronx-cc', 'compile', '--framework=XLA', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_0a59544d8a22ab5b06a0+747527b0.hlo_module.pb', '--output', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_0a59544d8a22ab5b06a0+747527b0.neff', '--target=trn2', '--auto-cast=none', '--model-type=transformer', '--tensorizer-options=--enable-ccop-compute-overlap --cc-pipeline-tiling-factor=2 --vectorize-strided-dma ', '-O2', '--lnc=2', '--logfile=/tmp/nxd_model/token_generation_model/_tp0_bk0/log-neuron-cc.txt', '--enable-internal-neff-wrapper', '--verbose=35']: 2025-10-17T07:13:35Z 2025-10-17 07:13:34.954102: F hilo/hlo_passes/NeuronHloVerifier.cc:504] [ERROR] [NCC_VRF009] Memory requirement exceeds target architecture's HBM limit. Needed 17187432532 bytes (16 GB) vs. available 17179869184 bytes (16 GB). TIP: Consider using smaller batches or applying model parallelism
|
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Failed compilation with ['neuronx-cc', 'compile', '--framework=XLA', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_3c45b7d14d093b6eb821+747527b0.hlo_module.pb', '--output', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_3c45b7d14d093b6eb821+747527b0.neff', '--target=trn2', '--auto-cast=none', '--model-type=transformer', '--tensorizer-options=--enable-ccop-compute-overlap --cc-pipeline-tiling-factor=2 --vectorize-strided-dma ', '-O2', '--lnc=2', '--logfile=/tmp/nxd_model/token_generation_model/_tp0_bk0/log-neuron-cc.txt', '--enable-internal-neff-wrapper', '--verbose=35']: 2025-10-17T07:08:48Z 2025-10-17 07:08:48.115351: F hilo/hlo_passes/NeuronHloVerifier.cc:504] [ERROR] [NCC_VRF009] Memory requirement exceeds target architecture's HBM limit. Needed 20677306816 bytes (19 GB) vs. available 17179869184 bytes (16 GB). TIP: Consider using smaller batches or applying model parallelism
|
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neuronxcc-2.21.18209.0+043b1bf7/MODULE_ffe3bb712e8a45b20f93+747527b0/model.log
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Failed compilation with ['neuronx-cc', 'compile', '--framework=XLA', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_ffe3bb712e8a45b20f93+747527b0.hlo_module.pb', '--output', '/tmp/nxd_model/token_generation_model/_tp0_bk0/model.MODULE_ffe3bb712e8a45b20f93+747527b0.neff', '--target=trn2', '--auto-cast=none', '--model-type=transformer', '--tensorizer-options=--enable-ccop-compute-overlap --cc-pipeline-tiling-factor=2 --vectorize-strided-dma ', '-O2', '--lnc=2', '--logfile=/tmp/nxd_model/token_generation_model/_tp0_bk0/log-neuron-cc.txt', '--enable-internal-neff-wrapper', '--verbose=35']: 2025-10-17T07:10:25Z 2025-10-17 07:10:25.765334: F hilo/hlo_passes/NeuronHloVerifier.cc:504] [ERROR] [NCC_VRF009] Memory requirement exceeds target architecture's HBM limit. Needed 18529691872 bytes (17 GB) vs. available 17179869184 bytes (16 GB). TIP: Consider using smaller batches or applying model parallelism
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