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Mila 0.13.48
Deep Neural Network Library
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Configuration for StreamingSequenceLoader behavior. More...
Public Attributes | |
| uint32_t | batch_timeout_ms = 10000 |
| Timeout for subsequent batch preparation (milliseconds). | |
| uint32_t | initialization_timeout_ms = 5000 |
| Timeout for initial batch preparation (milliseconds). | |
| size_t | max_queue_size = 2 |
| DEPRECATED: No longer used in refactored implementation. | |
| size_t | token_window_size = 0 |
| Size of token window to load from disk (in tokens). | |
| bool | verbose_logging = false |
| Enable verbose logging during initialization and operation. | |
Configuration for StreamingSequenceLoader behavior.
| uint32_t Mila::Data::TokenSequenceLoaderConfig::batch_timeout_ms = 10000 |
Timeout for subsequent batch preparation (milliseconds).
How long to wait for each batch in nextBatch(). Should be generous enough to account for disk I/O variance.
Default: 10000ms (10 seconds)
| uint32_t Mila::Data::TokenSequenceLoaderConfig::initialization_timeout_ms = 5000 |
Timeout for initial batch preparation (milliseconds).
How long to wait for the first batch during construction/reset.
Default: 5000ms (5 seconds)
| size_t Mila::Data::TokenSequenceLoaderConfig::max_queue_size = 2 |
DEPRECATED: No longer used in refactored implementation.
The new architecture uses double buffering instead of a queue, so this parameter has no effect.
| size_t Mila::Data::TokenSequenceLoaderConfig::token_window_size = 0 |
Size of token window to load from disk (in tokens).
Set to 0 for automatic sizing based on memory constraints. Larger windows reduce I/O frequency but increase memory usage.
Default: 0 (automatic, typically ~25M tokens)
| bool Mila::Data::TokenSequenceLoaderConfig::verbose_logging = false |
Enable verbose logging during initialization and operation.
When true, prints dataset statistics, window sizes, and batch counts.
Default: false