python/FunASR-XL.git

			@@ -353,11 +353,6 @@
			"""
			if self.criterion_transducer is None:
			try:
			# from warprnnt_pytorch import RNNTLoss
			# self.criterion_transducer = RNNTLoss(
			# reduction="mean",
			# fastemit_lambda=self.fastemit_lambda,
			# )
			from warp_rnnt import rnnt_loss as RNNTLoss
			self.criterion_transducer = RNNTLoss

			@@ -368,12 +363,6 @@
			)
			exit(1)

			# loss_transducer = self.criterion_transducer(
			# joint_out,
			# target,
			# t_len,
			# u_len,
			# )
			log_probs = torch.log_softmax(joint_out, dim=-1)

			loss_transducer = self.criterion_transducer(
			@@ -637,7 +626,6 @@

			batch_size = speech.shape[0]
			text = text[:, : text_lengths.max()]
			#print(speech.shape)
			# 1. Encoder
			encoder_out, encoder_out_chunk, encoder_out_lens = self.encode(speech, speech_lengths)

			@@ -709,7 +697,7 @@

			loss_trans = loss_trans_utt + loss_trans_chunk
			loss_ctc = loss_ctc + loss_ctc_chunk
			loss_ctc = loss_att + loss_att_chunk
			loss_att = loss_att + loss_att_chunk

			loss = (
			self.transducer_weight * loss_trans
			@@ -854,11 +842,6 @@
			"""
			if self.criterion_transducer is None:
			try:
			# from warprnnt_pytorch import RNNTLoss
			# self.criterion_transducer = RNNTLoss(
			# reduction="mean",
			# fastemit_lambda=self.fastemit_lambda,
			# )
			from warp_rnnt import rnnt_loss as RNNTLoss
			self.criterion_transducer = RNNTLoss

			@@ -869,12 +852,6 @@
			)
			exit(1)

			# loss_transducer = self.criterion_transducer(
			# joint_out,
			# target,
			# t_len,
			# u_len,
			# )
			log_probs = torch.log_softmax(joint_out, dim=-1)

			loss_transducer = self.criterion_transducer(
			@@ -1013,4 +990,4 @@
			ignore_label=self.ignore_id,
			)

			return loss_att, acc_att
			return loss_att, acc_att