Ntm#
Implementation of Neural Turing Machine
- class ivy_memory.learnt.ntm.NTM(input_dim, output_dim, ctrl_output_size, ctrl_layers, memory_size, memory_vector_dim, read_head_num, write_head_num, v=None, usage=None, addressing_mode='content_and_location', shift_range=1, clip_value=20, init_value=1e-06, sequential_writing=False, retroactive_updates=False, retroactive_discount=0.96, with_erase=True)[source]#
Bases:
Module
- __init__(input_dim, output_dim, ctrl_output_size, ctrl_layers, memory_size, memory_vector_dim, read_head_num, write_head_num, v=None, usage=None, addressing_mode='content_and_location', shift_range=1, clip_value=20, init_value=1e-06, sequential_writing=False, retroactive_updates=False, retroactive_discount=0.96, with_erase=True)[source]#
Initialize Ivy layer, which is a stateful object consisting of trainable variables.
- Parameters:
device – device on which to create the module’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None)
v – Ivy container of trainable variables. Created internally by default.
build_mode – How the Module is built, either on initialization (now), explicitly by the user by calling build(), or the first time the __call__ method is run. Default is on initialization.
compile_on_next_step – Whether to compile the network on the next forward pass. Default is
False
.store_vars – Whether or not to store the variables created. Default is
True
.stateful – The constant id stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.arg_stateful_idxs – The nested argument indices of stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.kwarg_stateful_idxs – The nested keyword argument indices of stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.fallback_to_non_compiled – Whether to fall back to non-compiled forward call in the case that an error is raised during the compiled forward pass. Default is
True
.with_partial_v – Whether to allow partial specification of variables. Default is
False
.devices – devices on which to distribute the module’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None)
- class ivy_memory.learnt.ntm.NTMCell(controller, controller_proj, output_proj, output_dim, ctrl_input_size, ctrl_output_size, total_parameter_num, memory_size, memory_vector_dim, read_head_num, write_head_num, v=None, usage=None, addressing_mode='content_and_location', shift_range=1, clip_value=20, init_value=1e-06, sequential_writing=False, retroactive_updates=False, retroactive_discount=0.96, with_erase=True, seed=0)[source]#
Bases:
Module
- __init__(controller, controller_proj, output_proj, output_dim, ctrl_input_size, ctrl_output_size, total_parameter_num, memory_size, memory_vector_dim, read_head_num, write_head_num, v=None, usage=None, addressing_mode='content_and_location', shift_range=1, clip_value=20, init_value=1e-06, sequential_writing=False, retroactive_updates=False, retroactive_discount=0.96, with_erase=True, seed=0)[source]#
Initialize Ivy layer, which is a stateful object consisting of trainable variables.
- Parameters:
device – device on which to create the module’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None)
v – Ivy container of trainable variables. Created internally by default.
build_mode – How the Module is built, either on initialization (now), explicitly by the user by calling build(), or the first time the __call__ method is run. Default is on initialization.
compile_on_next_step – Whether to compile the network on the next forward pass. Default is
False
.store_vars – Whether or not to store the variables created. Default is
True
.stateful – The constant id stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.arg_stateful_idxs – The nested argument indices of stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.kwarg_stateful_idxs – The nested keyword argument indices of stateful items to track as part of the forward pass. Used when graph compiling, default is
None
.fallback_to_non_compiled – Whether to fall back to non-compiled forward call in the case that an error is raised during the compiled forward pass. Default is
True
.with_partial_v – Whether to allow partial specification of variables. Default is
False
.devices – devices on which to distribute the module’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. (Default value = None)
- class ivy_memory.learnt.ntm.NTMControllerState(controller_state, read_vector_list, w_list, usage_indicator, M)[source]#
Bases:
tuple
- M#
Alias for field number 4
- controller_state#
Alias for field number 0
- read_vector_list#
Alias for field number 1
- usage_indicator#
Alias for field number 3
- w_list#
Alias for field number 2