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def | __init__ (self, alpha=1.0, epsilon=1e-9, policy="fixed", sparse_dedup_aggregator=None, engine='', moment_init=100.0, lars=None, output_effective_lr=False, output_effective_lr_and_update=False, kwargs) |
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def | scale_learning_rate (self, scale) |
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def | __init__ (self) |
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def | __call__ (self, net, param_init_net, param, grad=None) |
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def | get_cpu_blob_name (self, base_str, node_name='') |
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def | get_gpu_blob_name (self, base_str, gpu_id, node_name) |
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def | make_unique_blob_name (self, base_str) |
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def | build_lr (self, net, param_init_net, base_learning_rate, learning_rate_blob=None, policy="fixed", iter_val=0, kwargs) |
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def | add_lr_multiplier (self, lr_multiplier) |
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def | get_auxiliary_parameters (self) |
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def | scale_learning_rate (self, args, kwargs) |
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def | create_lars_inputs (self, param_init_net, weight_decay, trust, lr_max) |
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| alpha |
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| epsilon |
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| policy |
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| sparse_dedup_aggregator |
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| engine |
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| moment_init |
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| lars |
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| output_effective_lr |
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| output_effective_lr_and_update |
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| init_kwargs |
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def | dedup (net, sparse_dedup_aggregator, grad) |
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Definition at line 651 of file optimizer.py.
The documentation for this class was generated from the following file: