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model = train_and_evaluate(batch_size=32, lrate=0.0001, l1=0, l2=0, num_hidden=128) | |
===== | |
[Output] | |
2021-12-03 08:48:43.805276: W tensorflow/core/common_runtime/bfc_allocator.cc:457] Allocator (GPU_0_bfc) ran out of memory trying to allocate 73.50MiB (rounded to 77070336)requested by op Mul | |
If the cause is memory fragmentation maybe the environment variable 'TF_GPU_ALLOCATOR=cuda_malloc_async' will improve the situation. | |
Current allocation summary follows. | |
Current allocation summary follows. | |
2021-12-03 08:48:43.805401: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] BFCAllocator dump for GPU_0_bfc | |
2021-12-03 08:48:43.805463: I tensorflow/core/common_runtime/bfc_allocator.cc:1011] Bin (256): Total Chunks: 33, Chunks in use: 32. 8.2KiB allocated for chunks. 8.0KiB in use in bin. 217B client-requested in use in bin. | |
2021-12-03 08:48:43.805473: I tensorflow/core/common_runtime/bfc_allocator.cc:1011] Bin (512): Total Chunks: 3, Chunks in use: 3. 1.5KiB allocated for chunks. 1.5KiB in use in bin. 1.5KiB c |