gluon.Block¶
-
class
mxnet.gluon.
Block
(prefix=None, params=None)[source]¶ Bases:
object
Base class for all neural network layers and models. Your models should subclass this class.
Block
can be nested recursively in a tree structure. You can create and assign childBlock
as regular attributes:from mxnet.gluon import Block, nn from mxnet import ndarray as F class Model(Block): def __init__(self, **kwargs): super(Model, self).__init__(**kwargs) # use name_scope to give child Blocks appropriate names. with self.name_scope(): self.dense0 = nn.Dense(20) self.dense1 = nn.Dense(20) def forward(self, x): x = F.relu(self.dense0(x)) return F.relu(self.dense1(x)) model = Model() model.initialize(ctx=mx.cpu(0)) model(F.zeros((10, 10), ctx=mx.cpu(0)))
Methods
apply
(fn)Applies
fn
recursively to every child block as well as self.cast
(dtype)Cast this Block to use another data type.
collect_params
([select])Returns a
ParameterDict
containing thisBlock
and all of its children’s Parameters(default), also can returns the selectParameterDict
which match some given regular expressions.forward
(*args)Overrides to implement forward computation using
NDArray
.hybridize
([active])Please refer description of HybridBlock hybridize().
initialize
([init, ctx, verbose, force_reinit])Initializes
Parameter
s of thisBlock
and its children.load
(prefix)Load a model saved using the save API
load_parameters
(filename[, ctx, …])Load parameters from file previously saved by save_parameters.
load_params
(filename[, ctx, allow_missing, …])[Deprecated] Please use load_parameters.
Returns a name space object managing a child
Block
and parameter names.register_child
(block[, name])Registers block as a child of self.
register_forward_hook
(hook)Registers a forward hook on the block.
Registers a forward pre-hook on the block.
register_op_hook
(callback[, monitor_all])Install callback monitor.
save
(prefix)Save the model architecture and parameters to load again later
save_parameters
(filename[, deduplicate])Save parameters to file.
save_params
(filename)[Deprecated] Please use save_parameters. Note that if you want load
summary
(*inputs)Print the summary of the model’s output and parameters.
Attributes
Name of this
Block
, without ‘_’ in the end.Returns this
Block
’s parameter dictionary (does not include its children’s parameters).Prefix of this
Block
.Child
Block
assigned this way will be registered andcollect_params()
will collect their Parameters recursively. You can also manually register child blocks withregister_child()
.- Parameters
prefix (str) – Prefix acts like a name space. All children blocks created in parent block’s
name_scope()
will have parent block’s prefix in their name. Please refer to naming tutorial for more info on prefix and naming.params (ParameterDict or None) –
ParameterDict
for sharing weights with the newBlock
. For example, if you wantdense1
to sharedense0
’s weights, you can do:dense0 = nn.Dense(20) dense1 = nn.Dense(20, params=dense0.collect_params())
-
apply
(fn)[source]¶ Applies
fn
recursively to every child block as well as self.- Parameters
fn (callable) – Function to be applied to each submodule, of form fn(block).
- Returns
- Return type
this block
-
cast
(dtype)[source]¶ Cast this Block to use another data type.
- Parameters
dtype (str or numpy.dtype) – The new data type.
-
collect_params
(select=None)[source]¶ Returns a
ParameterDict
containing thisBlock
and all of its children’s Parameters(default), also can returns the selectParameterDict
which match some given regular expressions.For example, collect the specified parameters in [‘conv1_weight’, ‘conv1_bias’, ‘fc_weight’, ‘fc_bias’]:
model.collect_params('conv1_weight|conv1_bias|fc_weight|fc_bias')
or collect all parameters whose names end with ‘weight’ or ‘bias’, this can be done using regular expressions:
model.collect_params('.*weight|.*bias')
- Parameters
select (str) – regular expressions
- Returns
- Return type
The selected
ParameterDict
-
forward
(*args)[source]¶ Overrides to implement forward computation using
NDArray
. Only accepts positional arguments.- Parameters
*args (list of NDArray) – Input tensors.
-
initialize
(init=<mxnet.initializer.Uniform object>, ctx=None, verbose=False, force_reinit=False)[source]¶ Initializes
Parameter
s of thisBlock
and its children. Equivalent toblock.collect_params().initialize(...)
- Parameters
init (Initializer) – Global default Initializer to be used when
Parameter.init()
isNone
. Otherwise,Parameter.init()
takes precedence.ctx (Context or list of Context) – Keeps a copy of Parameters on one or many context(s).
verbose (bool, default False) – Whether to verbosely print out details on initialization.
force_reinit (bool, default False) – Whether to force re-initialization if parameter is already initialized.
-
load
(prefix)[source]¶ Load a model saved using the save API
Reconfigures a model using the saved configuration. This function does not regenerate the model architecture. It resets the children’s names as they were when saved in order to match the names of the saved parameters.
This function assumes the Blocks in the model were created in the same order they were when the model was saved. This is because each Block is uniquely identified by Block class name and a unique ID in order (since its an OrderedDict) and uses the unique ID to denote that specific Block. Assumes that the model is created in an identical order every time. If the model is not able to be recreated deterministically do not use this set of APIs to save/load your model.
For HybridBlocks, the cached_graph (Symbol & inputs) and settings are restored if it had been hybridized before saving.
- Parameters
prefix (str) – The prefix to use in filenames for loading this model: <prefix>-model.json and <prefix>-model.params
-
load_parameters
(filename, ctx=None, allow_missing=False, ignore_extra=False, cast_dtype=False, dtype_source='current')[source]¶ Load parameters from file previously saved by save_parameters.
- Parameters
filename (str) – Path to parameter file.
ctx (Context or list of Context, default cpu()) – Context(s) to initialize loaded parameters on.
allow_missing (bool, default False) – Whether to silently skip loading parameters not represents in the file.
ignore_extra (bool, default False) – Whether to silently ignore parameters from the file that are not present in this Block.
cast_dtype (bool, default False) – Cast the data type of the NDArray loaded from the checkpoint to the dtype provided by the Parameter if any.
dtype_source (str, default 'current') – must be in {‘current’, ‘saved’} Only valid if cast_dtype=True, specify the source of the dtype for casting the parameters
References
-
load_params
(filename, ctx=None, allow_missing=False, ignore_extra=False)[source]¶ [Deprecated] Please use load_parameters.
Load parameters from file.
- filenamestr
Path to parameter file.
- ctxContext or list of Context, default cpu()
Context(s) to initialize loaded parameters on.
- allow_missingbool, default False
Whether to silently skip loading parameters not represents in the file.
- ignore_extrabool, default False
Whether to silently ignore parameters from the file that are not present in this Block.
-
name_scope
()[source]¶ Returns a name space object managing a child
Block
and parameter names. Should be used within awith
statement:with self.name_scope(): self.dense = nn.Dense(20)
Please refer to the naming tutorial for more info on prefix and naming.
-
property
params
¶ Returns this
Block
’s parameter dictionary (does not include its children’s parameters).
-
register_child
(block, name=None)[source]¶ Registers block as a child of self.
Block
s assigned to self as attributes will be registered automatically.
-
register_forward_hook
(hook)[source]¶ Registers a forward hook on the block.
The hook function is called immediately after
forward()
. It should not modify the input or output.- Parameters
hook (callable) – The forward hook function of form hook(block, input, output) -> None.
- Returns
- Return type
mxnet.gluon.utils.HookHandle
-
register_forward_pre_hook
(hook)[source]¶ Registers a forward pre-hook on the block.
The hook function is called immediately before
forward()
. It should not modify the input or output.- Parameters
hook (callable) – The forward hook function of form hook(block, input) -> None.
- Returns
- Return type
mxnet.gluon.utils.HookHandle
-
register_op_hook
(callback, monitor_all=False)[source]¶ Install callback monitor.
- Parameters
callback (function) – Takes a string and a NDArrayHandle.
monitor_all (bool, default False) – If true, monitor both input and output, otherwise monitor output only.
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save
(prefix)[source]¶ Save the model architecture and parameters to load again later
Saves the model architecture as a nested dictionary where each Block in the model is a dictionary and its children are sub-dictionaries.
Each Block is uniquely identified by Block class name and a unique ID. We save the child’s name that that parent uses for it to restore later in order to match the saved parameters.
Recursively traverses a Block’s children in order (since its an OrderedDict) and uses the unique ID to denote that specific Block. Assumes that the model is created in an identical order every time. If the model is not able to be recreated deterministically do not use this set of APIs to save/load your model.
For HybridBlocks, the cached_graph (Symbol & inputs) is saved if it has already been hybridized.
- Parameters
prefix (str) – The prefix to use in filenames for saving this model: <prefix>-model.json and <prefix>-model.params
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save_parameters
(filename, deduplicate=False)[source]¶ Save parameters to file.
Saved parameters can only be loaded with load_parameters. Note that this method only saves parameters, not model structure. If you want to save model structures, please use
HybridBlock.export()
.- Parameters
filename (str) – Path to file.
deduplicate (bool, default False) – If True, save shared parameters only once. Otherwise, if a Block contains multiple sub-blocks that share parameters, each of the shared parameters will be separately saved for every sub-block.
References
-
save_params
(filename)[source]¶ [Deprecated] Please use save_parameters. Note that if you want load from SymbolBlock later, please use export instead.
Save parameters to file.
- filenamestr
Path to file.
-
summary
(*inputs)[source]¶ Print the summary of the model’s output and parameters.
The network must have been initialized, and must not have been hybridized.
- Parameters
inputs (object) – Any input that the model supports. For any tensor in the input, only
mxnet.ndarray.NDArray
is supported.