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A10G
Running
on
A10G
| # @package __global__ | |
| # WARNING: This is a base configuration file shared across ALL solvers in AudioCraft | |
| # Please don't update this file directly. Instead use distinct configuration files | |
| # to override the below configuration. | |
| solver: ??? | |
| fsdp: | |
| use: false # should we use FSDP. | |
| param_dtype: float16 # equivalent to autocast_dtype for FSDP. | |
| reduce_dtype: float32 # gradient averaging dtype, float32 will give max stability. | |
| buffer_dtype: float32 # dtype used for buffers, we don't have much buffers, so let's leave it. | |
| sharding_strategy: shard_grad_op # can be shard_grad_op or full_shard. | |
| # full_shard will use less memory but slower ?? | |
| per_block: true # If True, uses nested FSDP. | |
| profiler: | |
| enabled: false | |
| deadlock: | |
| use: false | |
| timeout: 600 | |
| dataset: | |
| batch_size: ??? | |
| num_workers: 10 | |
| segment_duration: null | |
| num_samples: null | |
| return_info: false | |
| shuffle: false | |
| sample_on_duration: true | |
| sample_on_weight: true | |
| min_segment_ratio: 0.5 | |
| train: | |
| num_samples: null | |
| shuffle: true | |
| shuffle_seed: 0 # if you want to sample the data differently. | |
| permutation_on_files: false | |
| valid: | |
| num_samples: null | |
| evaluate: | |
| num_samples: null | |
| generate: | |
| num_samples: null | |
| return_info: true | |
| checkpoint: | |
| save_last: true | |
| save_every: null | |
| keep_last: null | |
| keep_every_states: null | |
| generate: | |
| every: null | |
| path: 'samples' | |
| audio: | |
| format: 'mp3' | |
| strategy: 'clip' | |
| sample_rate: null | |
| lm: | |
| use_sampling: false | |
| temp: 1.0 | |
| top_k: 0 | |
| top_p: 0.0 | |
| evaluate: | |
| every: null | |
| num_workers: 5 | |
| truncate_audio: null | |
| fixed_generation_duration: null # in secs | |
| metrics: | |
| base: true # run default evaluation (e.g. like train/valid stage) | |
| optim: | |
| epochs: ??? | |
| updates_per_epoch: null | |
| lr: ??? | |
| optimizer: ??? | |
| adam: | |
| betas: [0.9, 0.999] | |
| weight_decay: 0. | |
| ema: | |
| use: false # whether to use EMA or not | |
| updates: ${optim.updates_per_epoch} # frequency of updates of the EMA | |
| device: cpu # device for EMA, can be put on GPU if more frequent updates | |
| decay: 0.99 # EMA decay value, if null, no EMA is used | |
| schedule: | |
| lr_scheduler: null | |
| step: | |
| step_size: null | |
| gamma: null | |
| exponential: | |
| lr_decay: null | |
| cosine: | |
| warmup: null | |
| lr_min_ratio: 0.0 | |
| cycle_length: 1.0 | |
| polynomial_decay: | |
| warmup: null | |
| zero_lr_warmup_steps: 0 | |
| end_lr: 0.0 | |
| power: 1 | |
| inverse_sqrt: | |
| warmup: null | |
| warmup_init_lr: 0.0 | |
| linear_warmup: | |
| warmup: null | |
| warmup_init_lr: 0.0 | |