# MIT License
#
# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
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from omegaconf import DictConfig
from openspeech.models import register_model
from openspeech.models import OpenspeechCTCModel
from openspeech.encoders import Jasper
from openspeech.models.jasper.configurations import Jasper5x3Config, Jasper10x5Config
from openspeech.tokenizers.tokenizer import Tokenizer
[docs]@register_model('jasper5x3', dataclass=Jasper5x3Config)
class Jasper5x3Model(OpenspeechCTCModel):
r"""
Jasper: An End-to-End Convolutional Neural Acoustic Model
Paper: https://arxiv.org/pdf/1904.03288.pdf
Args:
configs (DictConfig): configuration set.
tokenizer (Tokenizer): tokenizer is in charge of preparing the inputs for a model.
Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded `FloatTensor` of size ``(batch, seq_length, dimension)``.
input_lengths (torch.LongTensor): The length of input tensor. ``(batch)``
Returns:
outputs (dict): Result of model predictions that contains `y_hats`, `logits`, `output_lengths`
"""
def __init__(self, configs: DictConfig, tokenizer: Tokenizer) -> None:
super(Jasper5x3Model, self).__init__(configs, tokenizer)
def build_model(self):
self.encoder = Jasper(
configs=self.configs,
input_dim=self.configs.audio.num_mels,
num_classes=self.num_classes,
)
[docs]@register_model('jasper10x5', dataclass=Jasper10x5Config)
class Jasper10x5Model(Jasper5x3Model):
r"""
Jasper: An End-to-End Convolutional Neural Acoustic Model
Paper: https://arxiv.org/pdf/1904.03288.pdf
Args:
configs (DictConfig): configuration set.
tokenizer (Tokeizer): tokenizer is in charge of preparing the inputs for a model.
Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded `FloatTensor` of size ``(batch, seq_length, dimension)``.
input_lengths (torch.LongTensor): The length of input tensor. ``(batch)``
Returns:
outputs (dict): Result of model predictions that contains `y_hats`, `logits`, `output_lengths`
"""
def __init__(self, configs: DictConfig, tokenizer: Tokenizer) -> None:
super(Jasper10x5Model, self).__init__(configs, tokenizer)