def compute_output_shape(
self,
seq_len: Optional[int] = None,
batch_size: Optional[int] = None) -> Sequence[Union[int, None]]:
""" finished, checked,
Parameters:
-----------
seq_len: int,
length of the 1d sequence
batch_size: int, optional,
the batch size, can be None
Returns:
--------
output_shape: sequence,
the output shape of this block, given `seq_len` and `batch_size`
"""
_seq_len = seq_len
for module in self:
if type(module).__name__ == "MaxPool1d":
output_shape = compute_conv_output_shape(
input_shape=(batch_size, self.config.init_filter_length,
_seq_len),
num_filters=self.config.init_filter_length,
kernel_size=self.config.init_pool_size,
stride=self.config.init_pool_stride,
padding=(self.config.init_pool_size - 1) // 2,
)
else:
output_shape = module.compute_output_shape(
_seq_len, batch_size)
_, _, _seq_len = output_shape
return output_shape
def compute_output_shape(
self,
seq_len: Optional[int] = None,
batch_size: Optional[int] = None) -> Sequence[Union[int, None]]:
""" finished, checked,
Parameters:
-----------
seq_len: int,
length of the 1d sequence
batch_size: int, optional,
the batch size, can be None
Returns:
--------
output_shape: sequence,
the output shape of this block, given `seq_len` and `batch_size`
"""
num_layers = 0
for module in self:
if num_layers < self.__num_convs:
output_shape = module.compute_output_shape(seq_len, batch_size)
_, _, seq_len = output_shape
else:
output_shape = compute_conv_output_shape(
input_shape=[batch_size, self.__out_channels, seq_len],
num_filters=self.__out_channels,
kernel_size=self.config.pool_size,
stride=self.config.pool_size,
channel_last=False,
)
num_layers += 1
return output_shape