support cpu, test=asr

demos/audio_searching/src/operations/load.py

@@ -26,8 +26,9 @@ def get_audios(path):
     """
     supported_formats = [".wav", ".mp3", ".ogg", ".flac", ".m4a"]
     return [
-        item for sublist in [[os.path.join(dir, file) for file in files]
-                             for dir, _, files in list(os.walk(path))]
+        item
+        for sublist in [[os.path.join(dir, file) for file in files]
+                        for dir, _, files in list(os.walk(path))]
         for item in sublist if os.path.splitext(item)[1] in supported_formats
     ]
 

examples/aishell/asr0/local/train.sh

@@ -20,11 +20,20 @@ if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--model_type ${model_type} \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --model_type ${model_type} \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic

examples/aishell/asr0/run.sh

@@ -2,7 +2,7 @@
 set -e
 source path.sh
 
-gpus=0,1,2,3
+gpus=1,2,3
 stage=0
 stop_stage=100
 conf_path=conf/deepspeech2.yaml    #conf/deepspeech2.yaml or conf/deepspeech2_online.yaml

examples/aishell/asr1/local/train.sh

@@ -27,6 +27,16 @@ ckpt_name=$2
 
 mkdir -p exp
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--seed ${seed} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--profiler-options "${profiler_options}" \
+--benchmark-batch-size ${benchmark_batch_size} \
+--benchmark-max-step ${benchmark_max_step}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --seed ${seed} \
 --config ${config_path} \
@@ -34,6 +44,7 @@ python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/t
 --profiler-options "${profiler_options}" \
 --benchmark-batch-size ${benchmark_batch_size} \
 --benchmark-max-step ${benchmark_max_step}
+fi
 
 
 if [ ${seed} != 0  ]; then

examples/callcenter/asr1/local/train.sh

@@ -21,10 +21,18 @@ if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic

examples/librispeech/asr0/local/train.sh

@@ -20,11 +20,20 @@ if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--model_type ${model_type} \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --model_type ${model_type} \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic

examples/librispeech/asr1/local/train.sh

@@ -22,10 +22,18 @@ fi
 # export FLAGS_cudnn_exhaustive_search=true
 # export FLAGS_conv_workspace_size_limit=4000
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic

examples/librispeech/asr2/local/train.sh

@@ -19,11 +19,20 @@ if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--model-name u2_kaldi \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --model-name u2_kaldi \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic

examples/tiny/asr0/local/train.sh

@@ -26,12 +26,22 @@ model_type=$3
 
 mkdir -p exp
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--model_type ${model_type} \
+--profiler-options "${profiler_options}" \
+--seed ${seed}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --config ${config_path} \
 --output exp/${ckpt_name} \
 --model_type ${model_type} \
 --profiler-options "${profiler_options}" \
 --seed ${seed}
+fi
 
 if [ ${seed} != 0  ]; then
     unset FLAGS_cudnn_deterministic

examples/tiny/asr1/local/train.sh

@@ -27,6 +27,16 @@ ckpt_name=$2
 
 mkdir -p exp
 
+if [ ${ngpu} == 0 ]; then
+python3 -u ${BIN_DIR}/train.py \
+--ngpu ${ngpu} \
+--seed ${seed} \
+--config ${config_path} \
+--output exp/${ckpt_name} \
+--profiler-options "${profiler_options}" \
+--benchmark-batch-size ${benchmark_batch_size} \
+--benchmark-max-step ${benchmark_max_step}
+else
 python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/train.py \
 --seed ${seed} \
 --config ${config_path} \
@@ -34,6 +44,7 @@ python3 -m paddle.distributed.launch --gpus=${CUDA_VISIBLE_DEVICES} ${BIN_DIR}/t
 --profiler-options "${profiler_options}" \
 --benchmark-batch-size ${benchmark_batch_size} \
 --benchmark-max-step ${benchmark_max_step}
+fi
 
 
 if [ ${seed} != 0  ]; then

paddlespeech/s2t/exps/deepspeech2/bin/train.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Trainer for DeepSpeech2 model."""
-from paddle import distributed as dist
 from yacs.config import CfgNode
 
 from paddlespeech.s2t.exps.deepspeech2.model import DeepSpeech2Trainer as Trainer

paddlespeech/s2t/exps/u2/bin/train.py

@@ -15,7 +15,6 @@
 import cProfile
 import os
 
-from paddle import distributed as dist
 from yacs.config import CfgNode
 
 from paddlespeech.s2t.exps.u2.model import U2Trainer as Trainer

paddlespeech/s2t/exps/u2_kaldi/bin/train.py

@@ -15,7 +15,6 @@
 import cProfile
 import os
 
-from paddle import distributed as dist
 from yacs.config import CfgNode
 
 from paddlespeech.s2t.training.cli import default_argument_parser

paddlespeech/s2t/exps/u2_st/bin/train.py

@@ -15,7 +15,6 @@
 import cProfile
 import os
 
-from paddle import distributed as dist
 from yacs.config import CfgNode
 
 from paddlespeech.s2t.exps.u2_st.model import U2STTrainer as Trainer

paddlespeech/s2t/io/sampler.py

@@ -51,7 +51,7 @@ def _batch_shuffle(indices, batch_size, epoch, clipped=False):
     """
     rng = np.random.RandomState(epoch)
     shift_len = rng.randint(0, batch_size - 1)
-    batch_indices = list(zip(* [iter(indices[shift_len:])] * batch_size))
+    batch_indices = list(zip(*[iter(indices[shift_len:])] * batch_size))
     rng.shuffle(batch_indices)
     batch_indices = [item for batch in batch_indices for item in batch]
     assert clipped is False

paddlespeech/t2s/modules/transformer/repeat.py

@@ -36,4 +36,4 @@ def repeat(N, fn):
     Returns:
         MultiSequential: Repeated model instance.
     """
-    return MultiSequential(* [fn(n) for n in range(N)])
+    return MultiSequential(*[fn(n) for n in range(N)])