msb-public
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PaddleSpeech
mirror of https://github.com/PaddlePaddle/PaddleSpeech
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not change decoder

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pull/735/head
huangyuxin 3 years ago
parent 6c484923a4
commit 2f64ae6495
2 changed files with 52 additions and 52 deletions
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7
deepspeech/models/ds2_online/deepspeech2.py
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@ -295,7 +295,7 @@ class DeepSpeech2ModelOnline(nn.Layer):
probs.numpy(), eouts_len, vocab_list, decoding_method,
lang_model_path, beam_alpha, beam_beta, beam_size, cutoff_prob,
cutoff_top_n, num_processes)
"""
@paddle.no_grad()
def decode_by_chunk(self, eouts_prefix, eouts_len_prefix, chunk_state_list,
audio_chunk, audio_len_chunk, vocab_list,
@ -349,14 +349,14 @@ class DeepSpeech2ModelOnline(nn.Layer):
probs.numpy(), eouts_len, vocab_list, decoding_method,
lang_model_path, beam_alpha, beam_beta, beam_size, cutoff_prob,
cutoff_top_n, num_processes)
"""
"""
decocd_prob,
decode_prob_chunk_by_chunk
decode_prob_by_chunk
is only used for test
"""
"""
@paddle.no_grad()
def decode_prob(self, audio, audio_len):
eouts, eouts_len, final_state_list = self.encoder(audio, audio_len)
@ -385,6 +385,7 @@ class DeepSpeech2ModelOnline(nn.Layer):
eouts_lens = eouts_chunk_lens
probs = self.decoder.softmax(eouts)
return probs, eouts, eouts_lens, final_state_list
"""
@classmethod
def from_pretrained(cls, dataloader, config, checkpoint_path):

97
tests/deepspeech2_online_model_test.py
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@ -105,6 +105,51 @@ class TestDeepSpeech2ModelOnline(unittest.TestCase):
loss = model(self.audio, self.audio_len, self.text, self.text_len)
self.assertEqual(loss.numel(), 1)
def test_ds2_6(self):
model = DeepSpeech2ModelOnline(
feat_size=self.feat_dim,
dict_size=10,
num_conv_layers=2,
num_rnn_layers=1,
rnn_size=1024,
num_fc_layers=2,
fc_layers_size_list=[512, 256],
use_gru=True)
model.eval()
paddle.device.set_device("cpu")
de_ch_size = 9
eouts, eouts_lens, final_state_list = model.encoder(
self.audio, self.audio_len)
eouts_by_chk_list, eouts_lens_by_chk_list, final_state_list_by_chk = model.encoder.forward_chunk_by_chunk(
self.audio, self.audio_len, de_ch_size)
eouts_by_chk = paddle.concat(eouts_by_chk_list, axis = 1)
eouts_lens_by_chk = paddle.add_n(eouts_lens_by_chk_list)
decode_max_len = eouts.shape[1]
print ("dml", decode_max_len)
eouts_by_chk = eouts_by_chk[:, :decode_max_len, :]
self.assertEqual(
paddle.sum(
paddle.abs(paddle.subtract(eouts_lens, eouts_lens_by_chk))), 0)
self.assertEqual(
paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))), 0)
self.assertEqual(paddle.allclose(eouts_by_chk, eouts), True)
"""
print ("conv_x", conv_x)
print ("conv_x_by_chk", conv_x_by_chk)
print ("final_state_list", final_state_list)
#print ("final_state_list_by_chk", final_state_list_by_chk)
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,:de_ch_size,:], eouts_by_chk[:,:de_ch_size,:]))))
print (paddle.allclose(eouts[:,:de_ch_size,:], eouts_by_chk[:,:de_ch_size,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,de_ch_size:de_ch_size*2,:], eouts_by_chk[:,de_ch_size:de_ch_size*2,:]))))
print (paddle.allclose(eouts[:,de_ch_size:de_ch_size*2,:], eouts_by_chk[:,de_ch_size:de_ch_size*2,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,de_ch_size*2:de_ch_size*3,:], eouts_by_chk[:,de_ch_size*2:de_ch_size*3,:]))))
print (paddle.allclose(eouts[:,de_ch_size*2:de_ch_size*3,:], eouts_by_chk[:,de_ch_size*2:de_ch_size*3,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))))
print (paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))))
print (paddle.allclose(eouts[:,:,:], eouts_by_chk[:,:,:]))
"""
"""
def split_into_chunk(self, x, x_lens, decoder_chunk_size, subsampling_rate,
receptive_field_length):
chunk_size = (decoder_chunk_size - 1
@ -134,7 +179,7 @@ class TestDeepSpeech2ModelOnline(unittest.TestCase):
return x_chunk_list, x_chunk_lens_list
def test_ds2_6(self):
def test_ds2_7(self):
model = DeepSpeech2ModelOnline(
feat_size=self.feat_dim,
dict_size=10,
@ -157,7 +202,7 @@ class TestDeepSpeech2ModelOnline(unittest.TestCase):
chunk_state_list = [None] * model.encoder.num_rnn_layers
for i, audio_chunk in enumerate(audio_chunk_list):
audio_chunk_lens = audio_chunk_lens_list[i]
probs_pre_chunks, eouts_prefix, eouts_lens_prefix, chunk_state_list = model.decode_prob_by_chunk(
eouts_prefix, eouts_lens_prefix, chunk_state_list = model.decode_prob_by_chunk(
audio_chunk, audio_chunk_lens, eouts_prefix, eouts_lens_prefix,
chunk_state_list)
# print (i, probs_pre_chunks.shape)
@ -168,53 +213,7 @@ class TestDeepSpeech2ModelOnline(unittest.TestCase):
decode_max_len = probs.shape[1]
probs_pre_chunks = probs_pre_chunks[:, :decode_max_len, :]
self.assertEqual(paddle.allclose(probs, probs_pre_chunks), True)
def test_ds2_7(self):
model = DeepSpeech2ModelOnline(
feat_size=self.feat_dim,
dict_size=10,
num_conv_layers=2,
num_rnn_layers=1,
rnn_size=1024,
num_fc_layers=2,
fc_layers_size_list=[512, 256],
use_gru=True)
model.eval()
paddle.device.set_device("cpu")
de_ch_size = 9
probs, eouts, eouts_lens, final_state_list = model.decode_prob(
self.audio, self.audio_len)
probs_by_chk, eouts_by_chk, eouts_lens_by_chk, final_state_list_by_chk = model.decode_prob_chunk_by_chunk(
self.audio, self.audio_len, de_ch_size)
decode_max_len = probs.shape[1]
probs_by_chk = probs_by_chk[:, :decode_max_len, :]
eouts_by_chk = eouts_by_chk[:, :decode_max_len, :]
self.assertEqual(
paddle.sum(
paddle.abs(paddle.subtract(eouts_lens, eouts_lens_by_chk))), 0)
self.assertEqual(
paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))), 0)
self.assertEqual(
paddle.sum(
paddle.abs(paddle.subtract(probs, probs_by_chk))).numpy(), 0)
self.assertEqual(paddle.allclose(eouts_by_chk, eouts), True)
self.assertEqual(paddle.allclose(probs_by_chk, probs), True)
"""
print ("conv_x", conv_x)
print ("conv_x_by_chk", conv_x_by_chk)
print ("final_state_list", final_state_list)
#print ("final_state_list_by_chk", final_state_list_by_chk)
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,:de_ch_size,:], eouts_by_chk[:,:de_ch_size,:]))))
print (paddle.allclose(eouts[:,:de_ch_size,:], eouts_by_chk[:,:de_ch_size,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,de_ch_size:de_ch_size*2,:], eouts_by_chk[:,de_ch_size:de_ch_size*2,:]))))
print (paddle.allclose(eouts[:,de_ch_size:de_ch_size*2,:], eouts_by_chk[:,de_ch_size:de_ch_size*2,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts[:,de_ch_size*2:de_ch_size*3,:], eouts_by_chk[:,de_ch_size*2:de_ch_size*3,:]))))
print (paddle.allclose(eouts[:,de_ch_size*2:de_ch_size*3,:], eouts_by_chk[:,de_ch_size*2:de_ch_size*3,:]))
print (paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))))
print (paddle.sum(paddle.abs(paddle.subtract(eouts, eouts_by_chk))))
print (paddle.allclose(eouts[:,:,:], eouts_by_chk[:,:,:]))
"""
"""
if __name__ == '__main__':

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