paddlespeech.vector.models.ecapa_tdnn module
- class paddlespeech.vector.models.ecapa_tdnn.AttentiveStatisticsPooling(channels, attention_channels=128, global_context=True)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x[, lengths])Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.BatchNorm1d(input_size, eps=1e-05, momentum=0.9, weight_attr=None, bias_attr=None, data_format='NCL', use_global_stats=None)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x)Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.Conv1d(in_channels, out_channels, kernel_size, stride=1, padding='same', dilation=1, groups=1, bias=True, padding_mode='reflect')[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x)Do conv1d forward
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.EcapaTdnn(input_size, lin_neurons=192, activation=<class 'paddle.nn.layer.activation.ReLU'>, channels=[512, 512, 512, 512, 1536], kernel_sizes=[5, 3, 3, 3, 1], dilations=[1, 2, 3, 4, 1], attention_channels=128, res2net_scale=8, se_channels=128, global_context=True)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x[, lengths])Compute embeddings.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.Res2NetBlock(in_channels, out_channels, scale=8, dilation=1)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x)Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.SEBlock(in_channels, se_channels, out_channels)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x[, lengths])Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.SERes2NetBlock(in_channels, out_channels, res2net_scale=8, se_channels=128, kernel_size=1, dilation=1, activation=<class 'paddle.nn.layer.activation.ReLU'>)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x[, lengths])Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook
- class paddlespeech.vector.models.ecapa_tdnn.TDNNBlock(in_channels, out_channels, kernel_size, dilation, activation=<class 'paddle.nn.layer.activation.ReLU'>)[source]
Bases:
Layer
Methods
__call__
(*inputs, **kwargs)Call self as a function.
add_parameter
(name, parameter)Adds a Parameter instance.
add_sublayer
(name, sublayer)Adds a sub Layer instance.
apply
(fn)Applies
fn
recursively to every sublayer (as returned by.sublayers()
) as well as self.buffers
([include_sublayers])Returns a list of all buffers from current layer and its sub-layers.
children
()Returns an iterator over immediate children layers.
clear_gradients
()Clear the gradients of all parameters for this layer.
create_parameter
(shape[, attr, dtype, ...])Create parameters for this layer.
create_tensor
([name, persistable, dtype])Create Tensor for this layer.
create_variable
([name, persistable, dtype])Create Tensor for this layer.
eval
()Sets this Layer and all its sublayers to evaluation mode.
extra_repr
()Extra representation of this layer, you can have custom implementation of your own layer.
forward
(x)Defines the computation performed at every call.
full_name
()Full name for this layer, composed by name_scope + "/" + MyLayer.__class__.__name__
load_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
named_buffers
([prefix, include_sublayers])Returns an iterator over all buffers in the Layer, yielding tuple of name and Tensor.
named_children
()Returns an iterator over immediate children layers, yielding both the name of the layer as well as the layer itself.
named_parameters
([prefix, include_sublayers])Returns an iterator over all parameters in the Layer, yielding tuple of name and parameter.
named_sublayers
([prefix, include_self, ...])Returns an iterator over all sublayers in the Layer, yielding tuple of name and sublayer.
parameters
([include_sublayers])Returns a list of all Parameters from current layer and its sub-layers.
register_buffer
(name, tensor[, persistable])Registers a tensor as buffer into the layer.
register_forward_post_hook
(hook)Register a forward post-hook for Layer.
register_forward_pre_hook
(hook)Register a forward pre-hook for Layer.
set_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
set_state_dict
(state_dict[, use_structured_name])Set parameters and persistable buffers from state_dict.
state_dict
([destination, include_sublayers, ...])Get all parameters and persistable buffers of current layer and its sub-layers.
sublayers
([include_self])Returns a list of sub layers.
to
([device, dtype, blocking])Cast the parameters and buffers of Layer by the give device, dtype and blocking.
to_static_state_dict
([destination, ...])Get all parameters and buffers of current layer and its sub-layers.
train
()Sets this Layer and all its sublayers to training mode.
backward
register_state_dict_hook