paddlespeech.s2t.modules.embedding module
Positonal Encoding Module.
- class paddlespeech.s2t.modules.embedding.NoPositionalEncoding(d_model: int, dropout_rate: float, max_len: int = 5000, reverse: bool = False)[source]
Bases:
Layer
,PositionalEncodingInterface
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[, offset])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.
position_encoding
(offset, size)For getting encoding in a streaming fashion Args: offset (int): start offset size (int): requried size of position encoding Returns: paddle.Tensor: Corresponding position encoding
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.s2t.modules.embedding.PositionalEncoding(d_model: int, dropout_rate: float, max_len: int = 5000, reverse: bool = False)[source]
Bases:
Layer
,PositionalEncodingInterface
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[, offset])Add positional encoding. Args: x (paddle.Tensor): Input. Its shape is (batch, time, ...) offset (int): position offset Returns: paddle.Tensor: Encoded tensor. Its shape is (batch, time, ...) paddle.Tensor: for compatibility to RelPositionalEncoding, (batch=1, time, ...).
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.
position_encoding
(offset, size)For getting encoding in a streaming fashion Attention!!!!! we apply dropout only once at the whole utterance level in a none streaming way, but will call this function several times with increasing input size in a streaming scenario, so the dropout will be applied several times. Args: offset (int): start offset size (int): requried size of position encoding Returns: paddle.Tensor: Corresponding position encoding, #[1, T, D].
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
- forward(x: Tensor, offset: int = 0) Tuple[Tensor, Tensor] [source]
Add positional encoding. Args:
x (paddle.Tensor): Input. Its shape is (batch, time, ...) offset (int): position offset
- Returns:
paddle.Tensor: Encoded tensor. Its shape is (batch, time, ...) paddle.Tensor: for compatibility to RelPositionalEncoding, (batch=1, time, ...)
- position_encoding(offset: int, size: int) Tensor [source]
For getting encoding in a streaming fashion Attention!!!!! we apply dropout only once at the whole utterance level in a none streaming way, but will call this function several times with increasing input size in a streaming scenario, so the dropout will be applied several times. Args:
offset (int): start offset size (int): requried size of position encoding
- Returns:
paddle.Tensor: Corresponding position encoding, #[1, T, D].
- class paddlespeech.s2t.modules.embedding.PositionalEncodingInterface[source]
Bases:
object
Methods
forward
(x[, offset])Compute positional encoding. Args: x (paddle.Tensor): Input tensor (batch, time, *). Returns: paddle.Tensor: Encoded tensor (batch, time, *). paddle.Tensor: Positional embedding tensor (1, time, *).
position_encoding
(offset, size)For getting encoding in a streaming fashion Args: offset (int): start offset size (int): requried size of position encoding Returns: paddle.Tensor: Corresponding position encoding
- class paddlespeech.s2t.modules.embedding.RelPositionalEncoding(d_model: int, dropout_rate: float, max_len: int = 5000)[source]
Bases:
PositionalEncoding
Relative positional encoding module. See : Appendix B in https://arxiv.org/abs/1901.02860
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[, offset])Compute positional encoding. Args: x (paddle.Tensor): Input tensor (batch, time, *). Returns: paddle.Tensor: Encoded tensor (batch, time, *). paddle.Tensor: Positional embedding tensor (1, time, *).
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.
position_encoding
(offset, size)For getting encoding in a streaming fashion Attention!!!!! we apply dropout only once at the whole utterance level in a none streaming way, but will call this function several times with increasing input size in a streaming scenario, so the dropout will be applied several times. Args: offset (int): start offset size (int): requried size of position encoding Returns: paddle.Tensor: Corresponding position encoding, #[1, T, D].
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